(define-module (guix-cran packages c)
  #:use-module (guix packages)
  #:use-module (guix download)
  #:use-module (guix build-system r)
  #:use-module ((guix licenses)
                #:prefix license:)
  #:use-module (gnu packages cran)
  #:use-module (gnu packages statistics)
  #:use-module (gnu packages python)
  #:use-module (gnu packages web)
  #:use-module (gnu packages bioconductor)
  #:use-module (gnu packages java)
  #:use-module (gnu packages gcc)
  #:use-module (gnu packages cmake)
  #:use-module (gnu packages check)
  #:use-module (gnu packages pkg-config)
  #:use-module (gnu packages geo)
  #:use-module (gnu packages maths)
  #:use-module (gnu packages machine-learning)
  #:use-module (gnu packages compression)
  #:use-module (gnu packages haskell-xyz)
  #:use-module (gnu packages bioinformatics)
  #:use-module (gnu packages photo)
  #:use-module (guix-cran packages z)
  #:use-module (guix-cran packages y)
  #:use-module (guix-cran packages x)
  #:use-module (guix-cran packages w)
  #:use-module (guix-cran packages v)
  #:use-module (guix-cran packages u)
  #:use-module (guix-cran packages t)
  #:use-module (guix-cran packages s)
  #:use-module (guix-cran packages r)
  #:use-module (guix-cran packages q)
  #:use-module (guix-cran packages p)
  #:use-module (guix-cran packages o)
  #:use-module (guix-cran packages n)
  #:use-module (guix-cran packages m)
  #:use-module (guix-cran packages l)
  #:use-module (guix-cran packages k)
  #:use-module (guix-cran packages j)
  #:use-module (guix-cran packages i)
  #:use-module (guix-cran packages h)
  #:use-module (guix-cran packages g)
  #:use-module (guix-cran packages f)
  #:use-module (guix-cran packages e)
  #:use-module (guix-cran packages d)
  #:use-module (guix-cran packages b)
  #:use-module (guix-cran packages a))

(define-public r-czso
  (package
    (name "r-czso")
    (version "0.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "czso" version))
       (sha256
        (base32 "0hsml601swdig8ky210c8w3n2zfgn3f14ai9l43ni1iplkcpcdxi"))))
    (properties `((upstream-name . "czso")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringi
                             r-rlang
                             r-readr
                             r-magrittr
                             r-lifecycle
                             r-jsonlite
                             r-httr
                             r-dplyr
                             r-curl
                             r-cli))
    (home-page "https://github.com/petrbouchal/czso")
    (synopsis "Use Open Data from the Czech Statistical Office in R")
    (description
     "Get programmatic access to the open data provided by the Czech Statistical
Office (CZSO, <https://czso.cz>).")
    (license license:expat)))

(define-public r-czechrates
  (package
    (name "r-czechrates")
    (version "0.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "czechrates" version))
       (sha256
        (base32 "176bhlgdyl8fv1nbfgh2vc7h65d8pib2c162dzcdy1zlm4hccc84"))))
    (properties `((upstream-name . "czechrates")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-readr
                             r-magrittr
                             r-httr
                             r-dplyr
                             r-curl))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jla-data/czechrates")
    (synopsis "Czech Interest & Foreign Exchange Rates")
    (description
     "Interface to interest and foreign exchange rates published by the Czech National
Bank.")
    (license license:expat)))

(define-public r-cytosimplex
  (package
    (name "r-cytosimplex")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CytoSimplex" version))
       (sha256
        (base32 "0zknsizsh860hyij5zxpm3izfsiwnp7mshrrnk4fmxsjv9fcxahr"))))
    (properties `((upstream-name . "CytoSimplex")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-rcpparmadillo
                             r-rcpp
                             r-plot3d
                             r-matrix
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://welch-lab.github.io/CytoSimplex/")
    (synopsis
     "Simplex Visualization of Cell Fate Similarity in Single-Cell Data")
    (description
     "Create simplex plots to visualize the similarity between single-cells and
selected clusters in a 1-/2-/3-simplex space.  Velocity information can be added
as an additional layer.  See Liu J, Wang Y et al (2023)
<doi:10.1101/2023.12.07.570655> for more details.")
    (license license:gpl3)))

(define-public r-cytopt
  (package
    (name "r-cytopt")
    (version "0.9.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CytOpT" version))
       (sha256
        (base32 "008qm2kzclp0sy4ys7y0dsc894qrn7mazz9216w97rs2sn7kcrzx"))))
    (properties `((upstream-name . "CytOpT")))
    (build-system r-build-system)
    (inputs (list python))
    (propagated-inputs (list r-testthat
                             r-reticulate
                             r-reshape2
                             r-patchwork
                             r-metbrewer
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://sistm.github.io/CytOpT-R/")
    (synopsis
     "Optimal Transport for Gating Transfer in Cytometry Data with Domain Adaptation")
    (description
     "Supervised learning from a source distribution (with known segmentation into
cell sub-populations) to fit a target distribution with unknown segmentation.
It relies regularized optimal transport to directly estimate the different cell
population proportions from a biological sample characterized with flow
cytometry measurements.  It is based on the regularized Wasserstein metric to
compare cytometry measurements from different samples, thus accounting for
possible mis-alignment of a given cell population across sample (due to
technical variability from the technology of measurements).  Supervised learning
technique based on the Wasserstein metric that is used to estimate an optimal
re-weighting of class proportions in a mixture model Details are presented in
Freulon P, Bigot J and Hejblum BP (2021) <@code{arXiv:2006.09003>}.")
    (license license:gpl2+)))

(define-public r-cytominer
  (package
    (name "r-cytominer")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cytominer" version))
       (sha256
        (base32 "1n9yimjhdziv1vzjyni6ssi38nxcnfr5jpmzgxcn6vysffh5s9pz"))))
    (properties `((upstream-name . "cytominer")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-rlang
                             r-purrr
                             r-matrix
                             r-magrittr
                             r-futile-logger
                             r-foreach
                             r-dplyr
                             r-doparallel
                             r-caret))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/cytomining/cytominer")
    (synopsis "Methods for Image-Based Cell Profiling")
    (description
     "Typical morphological profiling datasets have millions of cells and hundreds of
features per cell.  When working with this data, you must clean the data,
normalize the features to make them comparable across experiments, transform the
features, select features based on their quality, and aggregate the single-cell
data, if needed.  cytominer makes these steps fast and easy.  Methods used in
practice in the field are discussed in Caicedo (2017) <doi:10.1038/nmeth.4397>.
An overview of the field is presented in Caicedo (2016)
<doi:10.1016/j.copbio.2016.04.003>.")
    (license license:bsd-3)))

(define-public r-cytometree
  (package
    (name "r-cytometree")
    (version "2.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cytometree" version))
       (sha256
        (base32 "18g7av73lmnyga1kk24bf8jy599zn9n6qhr13mxsqgi0zdinicfa"))))
    (properties `((upstream-name . "cytometree")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo
                             r-rcpp
                             r-mclust
                             r-igraph
                             r-gofkernel
                             r-ggplot2
                             r-cowplot))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cytometree")
    (synopsis "Automated Cytometry Gating and Annotation")
    (description
     "Given the hypothesis of a bi-modal distribution of cells for each marker, the
algorithm constructs a binary tree, the nodes of which are subpopulations of
cells.  At each node, observed cells and markers are modeled by both a family of
normal distributions and a family of bi-modal normal mixture distributions.
Splitting is done according to a normalized difference of AIC between the two
families.  Method is detailed in: Commenges, Alkhassim, Gottardo, Hejblum &
Thiebaut (2018) <doi: 10.1002/cyto.a.23601>.")
    (license (list license:lgpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-cytofan
  (package
    (name "r-cytofan")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cytofan" version))
       (sha256
        (base32 "0gqs98mnwiawnyfb9hs5nlin8d1fj64bszn4b40gs8ajyh36r9pp"))))
    (properties `((upstream-name . "cytofan")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/yannabraham/cytofan")
    (synopsis "Plot Fan Plots for Cytometry Data using 'ggplot2'")
    (description
     "An implementation of Fan plots for cytometry data in ggplot2'.  For reference
see Britton, E.; Fisher, P. & J. Whitley (1998) The Inflation Report
Projections: Understanding the Fan Chart
<https://www.bankofengland.co.uk/quarterly-bulletin/1998/q1/the-inflation-report-projections-understanding-the-fan-chart>).")
    (license license:gpl3)))

(define-public r-cytobankapi
  (package
    (name "r-cytobankapi")
    (version "2.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CytobankAPI" version))
       (sha256
        (base32 "0zhvxgqlzwv98b6ccl33x6jp71a14ysdmcc5a3v0d97r8haq1g3v"))))
    (properties `((upstream-name . "CytobankAPI")))
    (build-system r-build-system)
    (propagated-inputs (list r-uuid
                             r-jsonlite
                             r-jose
                             r-httr
                             r-curl
                             r-aws-s3))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CytobankAPI")
    (synopsis "Cytobank API Wrapper for R")
    (description
     "This package provides tools to interface with Cytobank's API via R, organized by
endpoints that represent various areas of Cytobank functionality.  Learn more
about Cytobank at <https://www.beckman.com/flow-cytometry/software>.")
    (license license:gpl3)))

(define-public r-cystisim
  (package
    (name "r-cystisim")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cystiSim" version))
       (sha256
        (base32 "0pz8jxi4lgcwzrb4dh8xn63xhpaga5rzg5hwqicwv8isc16iqizd"))))
    (properties `((upstream-name . "cystiSim")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-knitr r-ggplot2))
    (home-page "https://github.com/brechtdv/cystiSim")
    (synopsis "Agent-Based Model for Taenia_solium Transmission and Control")
    (description
     "The @code{cystiSim} package provides an agent-based model for Taenia solium
transmission and control. @code{cystiSim} was developed within the framework of
CYSTINET, the European Network on taeniosis/cysticercosis, COST ACTION TD1302.")
    (license license:gpl2+)))

(define-public r-cyphr
  (package
    (name "r-cyphr")
    (version "1.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cyphr" version))
       (sha256
        (base32 "17lzkmbk4fds5z8jwd2rlpy8v611qr6pdybf575hlnh61w1nf99x"))))
    (properties `((upstream-name . "cyphr")))
    (build-system r-build-system)
    (propagated-inputs (list r-sodium r-openssl r-getpass))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://github.com/ropensci/cyphr")
    (synopsis "High Level Encryption Wrappers")
    (description
     "Encryption wrappers, using low-level support from sodium and openssl'.  cyphr
tries to smooth over some pain points when using encryption within applications
and data analysis by wrapping around differences in function names and arguments
in different encryption providing packages.  It also provides high-level
wrappers for input/output functions for seamlessly adding encryption to existing
analyses.")
    (license license:expat)))

(define-public r-cymruservices
  (package
    (name "r-cymruservices")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cymruservices" version))
       (sha256
        (base32 "1xhdvijybdy7312qdbp50881yix587pmym0hchnwb3h0vhjv553v"))))
    (properties `((upstream-name . "cymruservices")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi r-pingr r-memoise))
    (home-page "https://cran.r-project.org/package=cymruservices")
    (synopsis
     "Query 'Team Cymru' 'IP' Address, Autonomous System Number ('ASN'), Border Gateway Protocol ('BGP'), Bogon and 'Malware' Hash Data Services")
    (description
     "This package provides a toolkit for querying Team Cymru <http://team-cymru.org>
IP address, Autonomous System Number ('ASN'), Border Gateway Protocol ('BGP'),
Bogon and Malware Hash Data Services.")
    (license license:expat)))

(define-public r-cylcop
  (package
    (name "r-cylcop")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cylcop" version))
       (sha256
        (base32 "1kh1h7zmk2d2p81ih1xyf3rv1g9gpjrdwyj3j812kp0krz71km4n"))))
    (properties `((upstream-name . "cylcop")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis
                             r-transport
                             r-stringr
                             r-rlang
                             r-rgl
                             r-rdpack
                             r-purrr
                             r-plotly
                             r-movmf
                             r-mixr
                             r-mass
                             r-infotheo
                             r-gofkernel
                             r-ggplot2
                             r-dplyr
                             r-data-table
                             r-cowplot
                             r-copula
                             r-circular))
    (home-page "https://github.com/r-lib/devtools")
    (synopsis
     "Circular-Linear Copulas with Angular Symmetry for Movement Data")
    (description
     "This package provides classes (S4) of circular-linear, symmetric copulas with
corresponding methods, extending the copula package.  These copulas are
especially useful for modeling correlation in discrete-time movement data.
Methods for density, (conditional) distribution, random number generation,
bivariate dependence measures and fitting parameters using maximum likelihood
and other approaches.  The package also contains methods for visualizing
movement data and copulas.")
    (license license:gpl2+)))

(define-public r-cyjshiny
  (package
    (name "r-cyjshiny")
    (version "1.0.42")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cyjShiny" version))
       (sha256
        (base32 "1p3ifmaxbw5g57pp4v8hnvq3fsy7frpny9jgp0q1b3klg3dhsjwj"))))
    (properties `((upstream-name . "cyjShiny")))
    (build-system r-build-system)
    (arguments
     (list
      #:modules '((guix build r-build-system)
                  (guix build minify-build-system)
                  (guix build utils)
                  (ice-9 match))
      #:imported-modules `(,@%r-build-system-modules (guix build
                                                      minify-build-system))
      #:phases '(modify-phases %standard-phases
                  (add-after 'unpack 'process-javascript
                    (lambda* (#:key inputs #:allow-other-keys)
                      (with-directory-excursion "inst/"
                        (for-each (match-lambda
                                    ((source . target) (minify source
                                                               #:target target)))
                                  '())))))))
    (propagated-inputs (list r-shiny r-jsonlite r-htmlwidgets r-graph
                             r-base64enc))
    (native-inputs (list r-knitr esbuild))
    (home-page "https://cran.r-project.org/package=cyjShiny")
    (synopsis "Cytoscape.js Shiny Widget (cyjShiny)")
    (description
     "Wraps cytoscape.js as a shiny widget.  cytoscape.js <https://js.cytoscape.org/>
is a Javascript-based graph theory (network) library for visualization and
analysis.  This package supports the visualization of networks with custom
visual styles and several available layouts.  Demo Shiny applications are
provided in the package code.")
    (license license:expat)))

(define-public r-cyclotomic
  (package
    (name "r-cyclotomic")
    (version "1.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cyclotomic" version))
       (sha256
        (base32 "1r2z21d2fylifw39ascx73k4rlfa3b1zg2pdbm2j7hg7g7rsr8w5"))))
    (properties `((upstream-name . "cyclotomic")))
    (build-system r-build-system)
    (propagated-inputs (list r-verylargeintegers
                             r-numbers
                             r-memoise
                             r-maybe
                             r-intmap
                             r-gmp))
    (home-page "https://github.com/stla/cyclotomic")
    (synopsis "The Field of Cyclotomic Numbers")
    (description
     "The cyclotomic numbers are complex numbers that can be thought of as the
rational numbers extended with the roots of unity.  They are represented
exactly, enabling exact computations.  They contain the Gaussian rationals
(complex numbers with rational real and imaginary parts) as well as the square
roots of all rational numbers.  They also contain the sine and cosine of all
rational multiples of pi.  The algorithms implemented in this package are taken
from the Haskell package cyclotomic', whose algorithms are adapted from code by
Martin Schoenert and Thomas Breuer in the GAP project
(<https://www.gap-system.org/>).  Cyclotomic numbers have applications in number
theory, algebraic geometry, algebraic number theory, coding theory, and in the
theory of graphs and combinatorics.  They have connections to the theory of
modular functions and modular curves.")
    (license license:gpl3)))

(define-public r-cyclops
  (package
    (name "r-cyclops")
    (version "3.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Cyclops" version))
       (sha256
        (base32 "1zz6jgzsjswzafya43fabqcgfhwn65sk8lx023hhn33vw844sv5p"))))
    (properties `((upstream-name . "Cyclops")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-rlang
                             r-rcppparallel
                             r-rcppeigen
                             r-rcpp
                             r-matrix
                             r-dplyr
                             r-bit64
                             r-andromeda))
    (home-page "https://github.com/ohdsi/cyclops")
    (synopsis
     "Cyclic Coordinate Descent for Logistic, Poisson and Survival Analysis")
    (description
     "This model fitting tool incorporates cyclic coordinate descent and
majorization-minimization approaches to fit a variety of regression models found
in large-scale observational healthcare data.  Implementations focus on
computational optimization and fine-scale parallelization to yield efficient
inference in massive datasets.  Please see: Suchard, Simpson, Zorych, Ryan and
Madigan (2013) <doi:10.1145/2414416.2414791>.")
    (license license:asl2.0)))

(define-public r-cyclomort
  (package
    (name "r-cyclomort")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cyclomort" version))
       (sha256
        (base32 "0qmfwhrp7bq7av0yc95xnz2sd1jxfaiys9smrk1kpclnynnra9rr"))))
    (properties `((upstream-name . "cyclomort")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-scales
                             r-plyr
                             r-mvtnorm
                             r-magrittr
                             r-lubridate
                             r-flexsurv))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/EliGurarie/cyclomort")
    (synopsis "Survival Modeling with a Periodic Hazard Function")
    (description
     "Modeling periodic mortality (or other time-to event) processes from
right-censored data.  Given observations of a process with a known period (e.g.
365 days, 24 hours), functions determine the number, intensity, timing, and
duration of peaks of periods of elevated hazard within a period.  The underlying
model is a mixed wrapped Cauchy function fitted using maximum likelihoods
(details in Gurarie et al. (2020) <doi:10.1111/2041-210X.13305>).  The
development of these tools was motivated by the strongly seasonal mortality
patterns observed in many wild animal populations, such that the respective
periods of higher mortality can be identified as \"mortality seasons\".")
    (license license:gpl3+)))

(define-public r-cycloids
  (package
    (name "r-cycloids")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cycloids" version))
       (sha256
        (base32 "1smmqww84w94891p9q77f27zxkzy7a72h7y6imi9n9p84v0pakzz"))))
    (properties `((upstream-name . "cycloids")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cycloids")
    (synopsis
     "Tools for Calculating Hypocycloids, Epicycloids, Hypotrochoids, and Epitrochoids")
    (description
     "This package provides tools for calculating coordinate representations of
hypocycloids, epicyloids, hypotrochoids, and epitrochoids (altogether called
cycloids here) with different scaling and positioning options.  The cycloids can
be visualised with any appropriate graphics function in R.")
    (license license:gpl3)))

(define-public r-cyclestreets
  (package
    (name "r-cyclestreets")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cyclestreets" version))
       (sha256
        (base32 "0sci6bg9xb7044sm41ycykdwah9rn4227m9140dx0rhbn60i1y7m"))))
    (properties `((upstream-name . "cyclestreets")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-stringi
                             r-sf
                             r-readr
                             r-rcppsimdjson
                             r-progressr
                             r-magrittr
                             r-jsonlite
                             r-httr
                             r-geojsonsf
                             r-dplyr
                             r-data-table
                             r-curl
                             r-checkmate))
    (home-page "https://rpackage.cyclestreets.net/")
    (synopsis "Cycle Routing and Data for Cycling Advocacy")
    (description
     "An interface to the cycle routing/data services provided by
@code{CycleStreets}', a not-for-profit social enterprise and advocacy
organisation.  The application programming interfaces (APIs) provided by
@code{CycleStreets} are documented at (<https://www.cyclestreets.net/api/>).
The focus of this package is the journey planning API, which aims to emulate the
routes taken by a knowledgeable cyclist.  An innovative feature of the routing
service of its provision of fastest, quietest and balanced profiles.  These
represent routes taken to minimise time, avoid traffic and compromise between
the two, respectively.")
    (license license:gpl3)))

(define-public r-cyclertools
  (package
    (name "r-cyclertools")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cycleRtools" version))
       (sha256
        (base32 "1l7w2lm4s149ndd85v41pkdrdig6l3nmhl14bdx56aw8q57fxmb0"))))
    (properties `((upstream-name . "cycleRtools")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (propagated-inputs (list r-xml2 r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jmackie4/cycleRtools")
    (synopsis "Tools for Cycling Data Analysis")
    (description
     "This package provides a suite of functions for analysing cycling data.")
    (license license:expat)))

(define-public r-cxxfunplus
  (package
    (name "r-cxxfunplus")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cxxfunplus" version))
       (sha256
        (base32 "125lzra4mr4cw5j18nck1faa6jf4fiw4m5pc9mp1h39268c9va6v"))))
    (properties `((upstream-name . "cxxfunplus")))
    (build-system r-build-system)
    (propagated-inputs (list r-inline))
    (home-page "https://github.com/maverickg/cxxfunplus")
    (synopsis "Extend 'cxxfunction' by Saving the Dynamic Shared Objects")
    (description
     "Extend cxxfunction by saving the dynamic shared objects for reusing across R
sessions.")
    (license license:gpl3)))

(define-public r-cxr
  (package
    (name "r-cxr")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cxr" version))
       (sha256
        (base32 "197xbphvnhg05dwcs0p7iwg6j6bi223cxxqfvibx7yp2bnfsllm2"))))
    (properties `((upstream-name . "cxr")))
    (build-system r-build-system)
    (propagated-inputs (list r-optimx r-mvtnorm r-matrix))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/RadicalCommEcol/cxr")
    (synopsis "Toolbox for Modelling Species Coexistence in R")
    (description
     "Recent developments in modern coexistence theory have advanced our understanding
on how species are able to persist and co-occur with other species at varying
abundances.  However, applying this mathematical framework to empirical data is
still challenging, precluding a larger adoption of the theoretical tools
developed by empiricists.  This package provides a complete toolbox for
modelling interaction effects between species, and calculate fitness and niche
differences.  The functions are flexible, may accept covariates, and different
fitting algorithms can be used.  A full description of the underlying methods is
available in GarcÃ­a-Callejas, D., Godoy, O., and Bartomeus, I. (2020)
<doi:10.1111/2041-210X.13443>.  Furthermore, the package provides a series of
functions to calculate dynamics for stage-structured populations across sites.")
    (license license:expat)))

(define-public r-cxhull
  (package
    (name "r-cxhull")
    (version "0.7.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cxhull" version))
       (sha256
        (base32 "0jxr1fz7cyarcq50jkkc2f3f1zwmbljpdpl56hfcilb43z2rkzkj"))))
    (properties `((upstream-name . "cxhull")))
    (build-system r-build-system)
    (propagated-inputs (list r-rvcg r-rgl r-data-table))
    (home-page "https://github.com/stla/cxhull")
    (synopsis "Convex Hull")
    (description
     "Computes the convex hull in arbitrary dimension, based on the Qhull library
(<http://www.qhull.org>).  The package provides a complete description of the
convex hull: edges, ridges, facets, adjacencies.  Triangulation is optional.")
    (license license:gpl3)))

(define-public r-cwt
  (package
    (name "r-cwt")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CWT" version))
       (sha256
        (base32 "0xwvzbz81j5mqkzhb0qc1srm5k9ygnl81nbq5xp9rc4yfa4yw2wq"))))
    (properties `((upstream-name . "CWT")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-data-table))
    (home-page "https://github.com/Antguz/CWT")
    (synopsis "Continuous Wavelet Transformation for Spectroscopy")
    (description
     "Fast application of Continuous Wavelet Transformation ('CWT') on time series
with special attention to spectroscopy.  It is written using data.table and C++
language and in some functions it is possible to use parallel processing to
speed-up the computation over samples.  Currently, only the second derivative of
a Gaussian wavelet function is implemented.")
    (license license:gpl3+)))

(define-public r-cwot
  (package
    (name "r-cwot")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cwot" version))
       (sha256
        (base32 "1qg9aizkz40sfm65b8sxcmj1232zb3ds8gds45lv0prf8alc7az3"))))
    (properties `((upstream-name . "cwot")))
    (build-system r-build-system)
    (propagated-inputs (list r-spatest r-mvtnorm))
    (home-page "https://cran.r-project.org/package=cwot")
    (synopsis "Cauchy Weighted Joint Test for Pharmacogenetics Analysis")
    (description
     "This package provides a flexible and robust joint test of the single nucleotide
polymorphism (SNP) main effect and genotype-by-treatment interaction effect for
continuous and binary endpoints.  Two analytic procedures, Cauchy weighted joint
test (CWOT) and adaptively weighted joint test (AWOT), are proposed to
accurately calculate the joint test p-value.  The proposed methods are evaluated
through extensive simulations under various scenarios.  The results show that
the proposed AWOT and CWOT control type I error well and outperform existing
methods in detecting the most interesting signal patterns in pharmacogenetics
(PGx) association studies.  For reference, see Hong Zhang, Devan Mehrotra and
Judong Shen (2022) <doi:10.13140/RG.2.2.28323.53280>.")
    (license license:gpl2)))

(define-public r-cvwrapr
  (package
    (name "r-cvwrapr")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cvwrapr" version))
       (sha256
        (base32 "17h017p76y7sjcwik48ravygmyivj6kvkhqy5s9ch0nwzzcrzvj3"))))
    (properties `((upstream-name . "cvwrapr")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-foreach))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cvwrapr")
    (synopsis "Tools for Cross Validation")
    (description
     "This package provides tools for performing cross-validation (CV).  The main
function is a general purpose wrapper that performs k-fold CV for any tuning
parameter in any supervised learning method.  The package also has a function
that computes the loss incurred by a set of predictions for a variety of loss
functions and model families.")
    (license license:gpl3+)))

(define-public r-cvtools
  (package
    (name "r-cvtools")
    (version "0.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cvTools" version))
       (sha256
        (base32 "0vrlj0jrmy1dj5fy4cpfkls2l5a2r7c7kvfhlnibpy8cmdx1mhql"))))
    (properties `((upstream-name . "cvTools")))
    (build-system r-build-system)
    (propagated-inputs (list r-robustbase r-lattice))
    (home-page "https://cran.r-project.org/package=cvTools")
    (synopsis "Cross-Validation Tools for Regression Models")
    (description
     "This package provides tools that allow developers to write functions for
cross-validation with minimal programming effort and assist users with model
selection.")
    (license license:gpl2+)))

(define-public r-cvthresh
  (package
    (name "r-cvthresh")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CVThresh" version))
       (sha256
        (base32 "14fgm5kzp1sscklv2pra800p12ga2hlqmm8s6zs5hdhlyvf0kj6v"))))
    (properties `((upstream-name . "CVThresh")))
    (build-system r-build-system)
    (propagated-inputs (list r-wavethresh r-ebayesthresh))
    (home-page "https://cran.r-project.org/package=CVThresh")
    (synopsis "Level-Dependent Cross-Validation Thresholding")
    (description
     "The level-dependent cross-validation method is implemented for the selection of
thresholding value in wavelet shrinkage.  This procedure is implemented by
coupling a conventional cross validation with an imputation method due to a
limitation of data length, a power of 2.  It can be easily applied to classical
leave-one-out and k-fold cross validation.  Since the procedure is
computationally fast, a level-dependent cross validation can be performed for
wavelet shrinkage of various data such as a data with correlated errors.")
    (license license:gpl2+)))

(define-public r-cvsem
  (package
    (name "r-cvsem")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cvsem" version))
       (sha256
        (base32 "148v8axwxfr328l709b6q1fmqnzmiw9g7589zgwha4d6lrx4ak4i"))))
    (properties `((upstream-name . "cvsem")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-lavaan))
    (home-page "https://cran.r-project.org/package=cvsem")
    (synopsis "SEM Model Comparison with K-Fold Cross-Validation")
    (description
     "The goal of cvsem is to provide functions that allow for comparing Structural
Equation Models (SEM) using cross-validation.  Users can specify multiple SEMs
using lavaan syntax.  cvsem computes the Kullback Leibler (KL) Divergence
between 1) the model implied covariance matrix estimated from the training data
and 2) the sample covariance matrix estimated from the test data described in
Cudeck, Robert & Browne (1983) <doi:10.18637/jss.v048.i02>.  The KL Divergence
is computed for each of the specified SEMs allowing for the models to be
compared based on their prediction errors.")
    (license license:gpl3+)))

(define-public r-cvrisk
  (package
    (name "r-cvrisk")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CVrisk" version))
       (sha256
        (base32 "1krqg3w2yqbpisivyym98p6yvhw1dw6qga8xm1sqxdd75g982fhq"))))
    (properties `((upstream-name . "CVrisk")))
    (build-system r-build-system)
    (home-page "https://github.com/vcastro/CVrisk")
    (synopsis "Compute Risk Scores for Cardiovascular Diseases")
    (description
     "Calculate various cardiovascular disease risk scores from the Framingham Heart
Study (FHS), the American College of Cardiology (ACC), and the American Heart
Association (AHA) as described in Dâagostino, et al (2008)
<doi:10.1161/circulationaha.107.699579>, Goff, et al (2013)
<doi:10.1161/01.cir.0000437741.48606.98>, and Mclelland, et al (2015)
<doi:10.1016/j.jacc.2015.08.035>.")
    (license license:gpl3)))

(define-public r-cvr
  (package
    (name "r-cvr")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CVR" version))
       (sha256
        (base32 "1y8m9r409jq5h6xx1rvz7c7aj882jldfxly89zf3cvp2qg3jh7rj"))))
    (properties `((upstream-name . "CVR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-pma))
    (home-page "https://cran.r-project.org/package=CVR")
    (synopsis "Canonical Variate Regression")
    (description
     "Perform canonical variate regression (CVR) for two sets of covariates and a
univariate response, with regularization and weight parameters tuned by cross
validation.")
    (license license:gpl2+)))

(define-public r-cvms
  (package
    (name "r-cvms")
    (version "1.6.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cvms" version))
       (sha256
        (base32 "08l33vianqd7kdxy5mys54cqahnp10sdzs2pmpd3iq97cs1qx4qb"))))
    (properties `((upstream-name . "cvms")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-recipes
                             r-rearrr
                             r-purrr
                             r-proc
                             r-plyr
                             r-parameters
                             r-mumin
                             r-lme4
                             r-lifecycle
                             r-groupdata2
                             r-ggplot2
                             r-dplyr
                             r-data-table
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ludvigolsen/cvms")
    (synopsis "Cross-Validation for Model Selection")
    (description
     "Cross-validate one or multiple regression and classification models and get
relevant evaluation metrics in a tidy format.  Validate the best model on a test
set and compare it to a baseline evaluation.  Alternatively, evaluate
predictions from an external model.  Currently supports regression and
classification (binary and multiclass).  Described in chp.  5 of Jeyaraman, B.
P., Olsen, L. R., & Wambugu M. (2019, ISBN: 9781838550134).")
    (license license:expat)))

(define-public r-cvmortalitymult
  (package
    (name "r-cvmortalitymult")
    (version "1.0.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CvmortalityMult" version))
       (sha256
        (base32 "0khfgzs0disnh089pyca04660gj5h3ycm49pndchcwpc7kp8yz80"))))
    (properties `((upstream-name . "CvmortalityMult")))
    (build-system r-build-system)
    (propagated-inputs (list r-tmap r-stmomo r-sf r-gnm r-forecast))
    (home-page "https://github.com/davidAtance/CvmortalityMult")
    (synopsis "Cross-Validation for Multi-Population Mortality Models")
    (description
     "Implementation of cross-validation method for testing the forecasting accuracy
of several multi-population mortality models.  The family of multi-population
includes several multi-population mortality models proposed through the
actuarial and demography literature.  The package includes functions for fitting
and forecast the mortality rates of several populations.  Additionally, we
include functions for testing the forecasting accuracy of different
multi-population models.  References.  Atance, D., Debon, A., and Navarro, E.
(2020) <doi:10.3390/math8091550>.  Bergmeir, C. & Benitez, J.M. (2012)
<doi:10.1016/j.ins.2011.12.028>.  Debon, A., Montes, F., & Martinez-Ruiz, F.
(2011) <doi:10.1007/s13385-011-0043-z>.  Lee, R.D. & Carter, L.R. (1992)
<doi:10.1080/01621459.1992.10475265>.  Russolillo, M., Giordano, G., & Haberman,
S. (2011) <doi:10.1080/03461231003611933>.  Santolino, M. (2023)
<doi:10.3390/risks11100170>.")
    (license license:expat)))

(define-public r-cvmgof
  (package
    (name "r-cvmgof")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cvmgof" version))
       (sha256
        (base32 "0s78w8ivxzscn6jbwsw0m15n3xwgbbjdqwpp4dsy3gi0nsmngjyc"))))
    (properties `((upstream-name . "cvmgof")))
    (build-system r-build-system)
    (propagated-inputs (list r-lattice))
    (home-page "https://cran.r-project.org/package=cvmgof")
    (synopsis "Cramer-von Mises Goodness-of-Fit Tests")
    (description
     "It is devoted to Cramer-von Mises goodness-of-fit tests.  It implements three
statistical methods based on Cramer-von Mises statistics to estimate and test a
regression model.")
    (license license:cecill)))

(define-public r-cvmdisc
  (package
    (name "r-cvmdisc")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cvmdisc" version))
       (sha256
        (base32 "19b9kxqgbk1d631l3jph87pzhk4zf3xd5q5j2xsrbqz8zmm96sn9"))))
    (properties `((upstream-name . "cvmdisc")))
    (build-system r-build-system)
    (propagated-inputs (list r-compquadform))
    (home-page "https://cran.r-project.org/package=cvmdisc")
    (synopsis "Cramer von Mises Tests for Discrete or Grouped Distributions")
    (description
     "This package implements Cramer-von Mises Statistics for testing fit to (1) fully
specified discrete distributions as described in Choulakian, Lockhart and
Stephens (1994) <doi:10.2307/3315828> (2) discrete distributions with unknown
parameters that must be estimated from the sample data, see Spinelli & Stephens
(1997) <doi:10.2307/3315735> and Lockhart, Spinelli and Stephens (2007)
<doi:10.1002/cjs.5550350111> (3) grouped continuous distributions with Unknown
Parameters, see Spinelli (2001) <doi:10.2307/3316040>.  Maximum likelihood
estimation (MLE) is used to estimate the parameters.  The package computes the
Cramer-von Mises Statistics, Anderson-Darling Statistics and the Watson-Stephens
Statistics and their p-values.")
    (license license:expat)))

(define-public r-cvmaplfam
  (package
    (name "r-cvmaplfam")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cvmaPLFAM" version))
       (sha256
        (base32 "1qmd4zbh70z1vgc6mxfr9scvqw923y9qdxjf80i826bdh7sc4wq3"))))
    (properties `((upstream-name . "cvmaPLFAM")))
    (build-system r-build-system)
    (propagated-inputs (list r-quadprog r-mgcv r-mass r-fda))
    (home-page "https://cran.r-project.org/package=cvmaPLFAM")
    (synopsis
     "Cross-Validation Model Averaging for Partial Linear Functional Additive Models")
    (description
     "Produce an averaging estimate/prediction by combining all candidate models for
partial linear functional additive models, using multi-fold cross-validation
criterion.  More details can be referred to Shishi Liu and Jingxiao Zhang.
(2021) <@code{arXiv:2105.00966>}.")
    (license license:gpl3+)))

(define-public r-cvlm
  (package
    (name "r-cvlm")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cvLM" version))
       (sha256
        (base32 "1mbafa75l1y757nvcqlamr98vd5qnaxakx3bsvjwrknyq29z27fs"))))
    (properties `((upstream-name . "cvLM")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppparallel r-rcppeigen r-rcpp))
    (home-page "https://cran.r-project.org/package=cvLM")
    (synopsis "Cross-Validation for Linear & Ridge Regression Models")
    (description
     "Efficient implementations of cross-validation techniques for linear and ridge
regression models, leveraging C++ code with Rcpp', @code{RcppParallel}', and
Eigen libraries.  It supports leave-one-out, generalized, and K-fold
cross-validation methods, utilizing Eigen matrices for high performance.
Methodology references: Hastie, Tibshirani, and Friedman (2009)
<doi:10.1007/978-0-387-84858-7>.")
    (license license:expat)))

(define-public r-cvglasso
  (package
    (name "r-cvglasso")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CVglasso" version))
       (sha256
        (base32 "1bh09cd0yabhqv5yfahhvayx3f09yqapzl1yr9nc9xqwyx1d0cfd"))))
    (properties `((upstream-name . "CVglasso")))
    (build-system r-build-system)
    (propagated-inputs (list r-glasso r-ggplot2 r-foreach r-dplyr r-doparallel))
    (home-page "https://github.com/MGallow/CVglasso")
    (synopsis "Lasso Penalized Precision Matrix Estimation")
    (description
     "Estimates a lasso penalized precision matrix via the blockwise coordinate
descent (BCD).  This package is a simple wrapper around the popular glasso
package that extends and enhances its capabilities.  These enhancements include
built-in cross validation and visualizations.  See Friedman et al (2008)
<doi:10.1093/biostatistics/kxm045> for details regarding the estimation method.")
    (license license:gpl2+)))

(define-public r-cvgee
  (package
    (name "r-cvgee")
    (version "0.3-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cvGEE" version))
       (sha256
        (base32 "085qjm520l2441nakfxy851s6bfy5832b5fy54z5fp4xr1jn6snm"))))
    (properties `((upstream-name . "cvGEE")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://drizopoulos.github.io/cvGEE/")
    (synopsis "Cross-Validated Predictions from GEE")
    (description
     "Calculates predictions from generalized estimating equations and internally
cross-validates them using the logarithmic, quadratic and spherical proper
scoring rules; Kung-Yee Liang and Scott L. Zeger (1986)
<doi:10.1093/biomet/73.1.13>.")
    (license license:gpl3+)))

(define-public r-cvequality
  (package
    (name "r-cvequality")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cvequality" version))
       (sha256
        (base32 "1im839vzfqylphp2vr20avnzkyl02n88fngbs63d4ik7c72d9992"))))
    (properties `((upstream-name . "cvequality")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/benmarwick/cvequality")
    (synopsis
     "Tests for the Equality of Coefficients of Variation from Multiple Groups")
    (description
     "This package contains functions for testing for significant differences between
multiple coefficients of variation.  Includes Feltz and Miller's (1996)
<DOI:10.1002/(SICI)1097-0258(19960330)15:6%3C647::AID-SIM184%3E3.0.CO;2-P>
asymptotic test and Krishnamoorthy and Lee's (2014)
<DOI:10.1007/s00180-013-0445-2> modified signed-likelihood ratio test.  See the
vignette for more, including full details of citations.")
    (license license:expat)))

(define-public r-cvdprevent
  (package
    (name "r-cvdprevent")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cvdprevent" version))
       (sha256
        (base32 "15r9p55pa55qy7dzaffzi1fg4c7nm3fh3qfj7pi9mwm03crqk4dm"))))
    (properties `((upstream-name . "cvdprevent")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-purrr
                             r-jsonlite
                             r-httr2
                             r-glue
                             r-dplyr
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/craig-parylo/cvdprevent")
    (synopsis
     "Wrapper for the 'CVD Prevent' Application Programming Interface")
    (description
     "This package provides an R wrapper to the CVD Prevent application programming
interface (API).  Users can make API requests through built-in R functions.  The
Cardiovascular Disease Prevention Audit (CVDPREVENT) is an England-wide primary
care audit that automatically extracts routinely held GP health data.
<https://bmchealthdocs.atlassian.net/wiki/spaces/CP/pages/317882369/CVDPREVENT+API+Documentation>.")
    (license license:expat)))

(define-public r-cvd
  (package
    (name "r-cvd")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CVD" version))
       (sha256
        (base32 "0agb0liwbp4wvmxbyxgfb7471ki1agfb6ssh77kvwbkxqmrc8d96"))))
    (properties `((upstream-name . "CVD")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CVD")
    (synopsis "Color Vision Deficiencies")
    (description
     "This package provides methods for color vision deficiencies (CVD), to help
understanding and mitigating issues with CVDs and to generate tests for
diagnosis and interpretation.")
    (license license:gpl3+)))

(define-public r-cvcrand
  (package
    (name "r-cvcrand")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cvcrand" version))
       (sha256
        (base32 "02pdhaq0mm1vijdc0hwh4vpcvk5fhwq73lhkrrg2zr6bwq8q2syz"))))
    (properties `((upstream-name . "cvcrand")))
    (build-system r-build-system)
    (propagated-inputs (list r-tableone))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cvcrand")
    (synopsis "Efficient Design and Analysis of Cluster Randomized Trials")
    (description
     "Constrained randomization by Raab and Butcher (2001)
<doi:10.1002/1097-0258(20010215)20:3%3C351::AID-SIM797%3E3.0.CO;2-C> is suitable
for cluster randomized trials (CRTs) with a small number of clusters (e.g., 20
or fewer).  The procedure of constrained randomization is based on the baseline
values of some cluster-level covariates specified.  The intervention effect on
the individual outcome can then be analyzed through clustered permutation test
introduced by Gail, et al. (1996)
<doi:10.1002/(SICI)1097-0258(19960615)15:11%3C1069::AID-SIM220%3E3.0.CO;2-Q>.
Motivated from Li, et al. (2016) <doi:10.1002/sim.7410>, the package performs
constrained randomization on the baseline values of cluster-level covariates and
clustered permutation test on the individual-level outcomes for cluster
randomized trials.")
    (license license:gpl2+)))

(define-public r-cvcovest
  (package
    (name "r-cvcovest")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cvCovEst" version))
       (sha256
        (base32 "148qb2995h9an2zp6rn0lvy8c6x1iiqx4cdfhzx6jdixra3593im"))))
    (properties `((upstream-name . "cvCovEst")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-rspectra
                             r-rmtstat
                             r-rlang
                             r-rdpack
                             r-rcolorbrewer
                             r-purrr
                             r-origami
                             r-matrixstats
                             r-matrix
                             r-ggpubr
                             r-ggplot2
                             r-dplyr
                             r-coop
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/PhilBoileau/cvCovEst")
    (synopsis "Cross-Validated Covariance Matrix Estimation")
    (description
     "An efficient cross-validated approach for covariance matrix estimation,
particularly useful in high-dimensional settings.  This method relies upon the
theory of high-dimensional loss-based covariance matrix estimator selection
developed by Boileau et al. (2022) <doi:10.1080/10618600.2022.2110883> to
identify the optimal estimator from among a prespecified set of candidates.")
    (license license:expat)))

(define-public r-cvasi
  (package
    (name "r-cvasi")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cvasi" version))
       (sha256
        (base32 "0j4r92b8n4fqd16s2549a13098dwi76vsyb67n8jv6xcxy9yxw9w"))))
    (properties `((upstream-name . "cvasi")))
    (build-system r-build-system)
    (propagated-inputs (list r-units
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-lubridate
                             r-lifecycle
                             r-lemna
                             r-gridextra
                             r-glue
                             r-ggplot2
                             r-ggally
                             r-furrr
                             r-dplyr
                             r-desolve
                             r-cli
                             r-attempt))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/cvasi-tktd/cvasi")
    (synopsis "Calibration, Validation, and Simulation of TKTD Models")
    (description
     "Eases the use of ecotoxicological effect models.  Can simulate common
toxicokinetic-toxicodynamic (TK/TD) models such as General Unified Threshold
models of Survival (GUTS) and Lemna.  It can derive effects and effect profiles
(EPx) from scenarios.  It supports the use of tidyr workflows employing the pipe
symbol.  Time-consuming tasks can be parallelized.")
    (license license:gpl3+)))

(define-public r-cvar
  (package
    (name "r-cvar")
    (version "0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cvar" version))
       (sha256
        (base32 "066vn8flw9j0idmpi9wzvybgihdhwg3fjslx2isbrb11ldl1lwky"))))
    (properties `((upstream-name . "cvar")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-gbutils))
    (home-page "https://geobosh.github.io/cvar/")
    (synopsis
     "Compute Expected Shortfall and Value at Risk for Continuous Distributions")
    (description
     "Compute expected shortfall (ES) and Value at Risk (@code{VaR}) from a quantile
function, distribution function, random number generator or probability density
function.  ES is also known as Conditional Value at Risk (C@code{VaR}).
Virtually any continuous distribution can be specified.  The functions are
vectorized over the arguments.  The computations are done directly from the
definitions, see e.g. Acerbi and Tasche (2002) <doi:10.1111/1468-0300.00091>.
Some support for GARCH models is provided, as well.")
    (license license:gpl2+)))

(define-public r-cvap
  (package
    (name "r-cvap")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cvap" version))
       (sha256
        (base32 "02ixibmia4v6qdrn3rwi4qjgha920y8qp83as9acr797abahmnm8"))))
    (properties `((upstream-name . "cvap")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-rlang
                             r-readr
                             r-fs
                             r-dplyr
                             r-cli
                             r-censable))
    (home-page "https://github.com/christopherkenny/cvap")
    (synopsis "Citizen Voting Age Population")
    (description
     "Works with the Citizen Voting Age Population special tabulation from the US
Census Bureau
<https://www.census.gov/programs-surveys/decennial-census/about/voting-rights/cvap.html>.
 Provides tools to download and process raw data.  Also provides a downloading
interface to processed data.  Implements a very basic approach to estimate block
level citizen voting age population from block group data.")
    (license license:expat)))

(define-public r-cv
  (package
    (name "r-cv")
    (version "2.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cv" version))
       (sha256
        (base32 "0d0js2sfffb7k3dl89j166c90sk1a1zh1rsyx04y9grhspahiqli"))))
    (properties `((upstream-name . "cv")))
    (build-system r-build-system)
    (propagated-inputs (list r-nlme
                             r-mass
                             r-lme4
                             r-lattice
                             r-insight
                             r-gtools
                             r-glmmtmb
                             r-foreach
                             r-doparallel
                             r-car))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://gmonette.github.io/cv/")
    (synopsis "Cross-Validating Regression Models")
    (description
     "Cross-validation methods of regression models that exploit features of various
modeling functions to improve speed.  Some of the methods implemented in the
package are novel, as described in the package vignettes; for general
introductions to cross-validation, see, for example, Gareth James, Daniela
Witten, Trevor Hastie, and Robert Tibshirani (2021, ISBN 978-1-0716-1417-4,
Secs.  5.1, 5.3), \"An Introduction to Statistical Learning with Applications in
R, Second Edition\", and Trevor Hastie, Robert Tibshirani, and Jerome Friedman
(2009, ISBN 978-0-387-84857-0, Sec.  7.10), \"The Elements of Statistical
Learning, Second Edition\".")
    (license license:gpl2+)))

(define-public r-cutpointsoehr
  (package
    (name "r-cutpointsoehr")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CutpointsOEHR" version))
       (sha256
        (base32 "0r772zb7g10akcfnf2hnyvpvba4px9pgslyns7drmijdsh0ncnvj"))))
    (properties `((upstream-name . "CutpointsOEHR")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival))
    (home-page "https://cran.r-project.org/package=CutpointsOEHR")
    (synopsis
     "Optimal Equal-HR Method to Find Two Cutpoints for U-Shaped Relationships in Cox Model")
    (description
     "Use optimal equal-HR method to determine two optimal cutpoints of a continuous
predictor that has a U-shaped relationship with survival outcomes based on Cox
regression model.  The optimal equal-HR method estimates two optimal cut-points
that have approximately the same log hazard value based on Cox regression model
and divides individuals into different groups according to their HR values.")
    (license license:gpl3)))

(define-public r-cutoff
  (package
    (name "r-cutoff")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cutoff" version))
       (sha256
        (base32 "0anrvmlvcxah620il3fkq6ldp7hx4nwdnzcpmfc5mhlsry0lp178"))))
    (properties `((upstream-name . "cutoff")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-set r-rocit r-do))
    (home-page "https://github.com/yikeshu0611/cutoff")
    (synopsis "Seek the Significant Cutoff Value")
    (description
     "Seek the significant cutoff value for a continuous variable, which will be
transformed into a classification, for linear regression, logistic regression,
logrank analysis and cox regression.  First of all, all combinations will be
gotten by combn() function.  Then n.per argument, abbreviated of total number
percentage, will be used to remove the combination of smaller data group.  In
logistic, Cox regression and logrank analysis, we will also use p.per argument,
patient percentage, to filter the lower proportion of patients in each group.
Finally, p value in regression results will be used to get the significant
combinations and output relevant parameters.  In this package, there is no limit
to the number of cutoff points, which can be 1, 2, 3 or more.  Still, we provide
2 methods, typical Bonferroni and Duglas G (1994) <doi: 10.1093/jnci/86.11.829>,
to adjust the p value, Missing values will be deleted by na.omit() function
before analysis.")
    (license license:gpl3)))

(define-public r-cusumdesign
  (package
    (name "r-cusumdesign")
    (version "1.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CUSUMdesign" version))
       (sha256
        (base32 "1qxq1a8b5pnmlq6rpjzvcp32scn2qknafch3h7qjsy8499zzbxx8"))))
    (properties `((upstream-name . "CUSUMdesign")))
    (build-system r-build-system)
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=CUSUMdesign")
    (synopsis
     "Compute Decision Interval and Average Run Length for CUSUM Charts")
    (description
     "Computation of decision intervals (H) and average run lengths (ARL) for CUSUM
charts.  Details of the method are seen in Hawkins and Olwell (2012): Cumulative
sum charts and charting for quality improvement, Springer Science & Business
Media.")
    (license license:gpl2)))

(define-public r-cusumcharter
  (package
    (name "r-cusumcharter")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cusumcharter" version))
       (sha256
        (base32 "0ljprnn48nfl8n0zmvc547rcg4cwrfhq3zjkkimgdnf7z2d130q6"))))
    (properties `((upstream-name . "cusumcharter")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-ggplot2 r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/johnmackintosh/cusumcharter")
    (synopsis "Easier CUSUM Control Charts")
    (description
     "Create CUSUM (cumulative sum) statistics from a vector or dataframe.  Also
create single or faceted CUSUM control charts, with or without control limits.
Accepts vector, dataframe, tibble or data.table inputs.")
    (license license:gpl3+)))

(define-public r-cusum
  (package
    (name "r-cusum")
    (version "0.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cusum" version))
       (sha256
        (base32 "0vjq3slkjdgls41xm637xkrg8jhv6y75xiyfcgpwrp32ixmakpcd"))))
    (properties `((upstream-name . "cusum")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-data-table r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cusum")
    (synopsis
     "Cumulative Sum (CUSUM) Charts for Monitoring of Hospital Performance")
    (description
     "This package provides functions for constructing and evaluating CUSUM charts and
RA-CUSUM charts with focus on false signal probability.")
    (license license:gpl2)))

(define-public r-custosascensor
  (package
    (name "r-custosascensor")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CustosAscensor" version))
       (sha256
        (base32 "1axyhwf9rc9dvrrcrpmx69kp49nwb0an7csn9qbjmx9jwwav11l5"))))
    (properties `((upstream-name . "CustosAscensor")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CustosAscensor")
    (synopsis "Costs Allocation for the Installation of an Elevator")
    (description
     "Calculate the distribution of costs for the installation of an elevator based on
the different distribution rules.")
    (license license:gpl2+)))

(define-public r-customizedtraining
  (package
    (name "r-customizedtraining")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "customizedTraining" version))
       (sha256
        (base32 "0kjp22bzv7a3xynhm9xmabfcms21586p8caz1nk1w88qdvidqfqd"))))
    (properties `((upstream-name . "customizedTraining")))
    (build-system r-build-system)
    (propagated-inputs (list r-glmnet r-fnn))
    (home-page "https://cran.r-project.org/package=customizedTraining")
    (synopsis
     "Customized Training for Lasso and Elastic-Net Regularized Generalized Linear Models")
    (description
     "Customized training is a simple technique for transductive learning, when the
test covariates are known at the time of training.  The method identifies a
subset of the training set to serve as the training set for each of a few
identified subsets in the training set.  This package implements customized
training for the glmnet() and cv.glmnet() functions.")
    (license license:gpl2)))

(define-public r-customiser
  (package
    (name "r-customiser")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "customiser" version))
       (sha256
        (base32 "0rwky3nrg6xhxb07v24d9j4359rmsn78xfxnv57kay8n5pmmh1s0"))))
    (properties `((upstream-name . "customiser")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr r-rmarkdown r-rlang r-knitr r-fs))
    (home-page "https://github.com/jameslairdsmith/customiser")
    (synopsis "Use R Markdown to Write your \"Rprofile\"")
    (description
     "This package provides a simple way to write \".Rprofile\" code in an R Markdown
file and have it knit to the correct location for your operating system.")
    (license license:expat)))

(define-public r-customerscoringmetrics
  (package
    (name "r-customerscoringmetrics")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CustomerScoringMetrics" version))
       (sha256
        (base32 "166v0hbxy4xgbfqh7sx6zsrv4pghqpimx5xry3h2qwynnvr4ng1a"))))
    (properties `((upstream-name . "CustomerScoringMetrics")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CustomerScoringMetrics")
    (synopsis
     "Evaluation Metrics for Customer Scoring Models Depending on Binary Classifiers")
    (description
     "This package provides functions for evaluating and visualizing predictive model
performance (specifically: binary classifiers) in the field of customer scoring.
 These metrics include lift, lift index, gain percentage, top-decile lift,
F1-score, expected misclassification cost and absolute misclassification cost.
See Berry & Linoff (2004, ISBN:0-471-47064-3), Witten and Frank (2005,
0-12-088407-0) and Blattberg, Kim & Neslin (2008,
ISBN:978â0â387â72578â9) for details.  Visualization functions are
included for lift charts and gain percentage charts.  All metrics that require
class predictions offer the possibility to dynamically determine cutoff values
for transforming real-valued probability predictions into class predictions.")
    (license license:gpl2+)))

(define-public r-customderivative
  (package
    (name "r-customderivative")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CustomDerivative" version))
       (sha256
        (base32 "05jfv968mnbamzspvdd51pbwz5xpn3jhj3pwq2piwk18br824rn2"))))
    (properties `((upstream-name . "CustomDerivative")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6))
    (home-page "https://cran.r-project.org/package=CustomDerivative")
    (synopsis "Pricing Various Types of Custom Derivatives")
    (description
     "This package provides a versatile R package for creating and pricing custom
derivatives to suit your financial needs.")
    (license license:expat)))

(define-public r-custom-gauss-quad
  (package
    (name "r-custom-gauss-quad")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "custom.gauss.quad" version))
       (sha256
        (base32 "1rpg3wrpvmn24a8kmm3mwyqmrcx2pxhhrf40wp31nv8jfy7cfm7c"))))
    (properties `((upstream-name . "custom.gauss.quad")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmpfr))
    (home-page "https://cran.r-project.org/package=custom.gauss.quad")
    (synopsis "Custom Made Gauss Quadrature Nodes and Weights")
    (description
     "Use the high-precision arithmetic provided by the R package Rmpfr to compute a
custom-made Gauss quadrature nodes and weights, with up to 33 nodes, using a
moment-based method via moment determinants.  Paul Kabaila (2022)
<@code{arXiv:2211.04729>}.")
    (license license:expat)))

(define-public r-cusp
  (package
    (name "r-cusp")
    (version "2.3.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cusp" version))
       (sha256
        (base32 "010qb3asn3nml44xyn7ch2vm8fhjh3a28hqivvr1q7mdzqjq6v3x"))))
    (properties `((upstream-name . "cusp")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cusp")
    (synopsis "Cusp-Catastrophe Model Fitting Using Maximum Likelihood")
    (description
     "Cobb's maximum likelihood method for cusp-catastrophe modeling (Grasman, van der
Maas, and Wagenmakers (2009) <doi:10.18637/jss.v032.i08>; Cobb (1981),
Behavioral Science, 26(1), 75-78).  Includes a cusp() function for model
fitting, and several utility functions for plotting, and for comparing the model
to linear regression and logistic curve models.")
    (license license:gpl2)))

(define-public r-curvir
  (package
    (name "r-curvir")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "curvir" version))
       (sha256
        (base32 "132cqsya612k8mhrhwl0133nhj30p0fa43q819s7cq0rnwhnna64"))))
    (properties `((upstream-name . "curvir")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer
                             r-randomforest
                             r-quantregforest
                             r-qgam
                             r-pso
                             r-pbapply
                             r-mgcv
                             r-cvtools
                             r-abind))
    (home-page "https://cran.r-project.org/package=curvir")
    (synopsis "Specify Reserve Demand Curves")
    (description
     "Automatic specification and estimation of reserve demand curves for central bank
operations.  The package can help to choose the best demand curve and identify
additional explanatory variables.  Various plot and predict options are
included.  For more details, see Chen et al. (2023)
<https://www.imf.org/en/Publications/WP/Issues/2023/09/01/Modeling-the-Reserve-Demand-to-Facilitate-Central-Bank-Operations-538754>.")
    (license license:gpl3)))

(define-public r-curvhdr
  (package
    (name "r-curvhdr")
    (version "1.2-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "curvHDR" version))
       (sha256
        (base32 "05i4q6lrzm23nvs5wkxxpa9c4ldz3khgsk5sw3cgzdzn3cm6a0xf"))))
    (properties `((upstream-name . "curvHDR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgl
                             r-ptinpoly
                             r-misc3d
                             r-ks
                             r-kernsmooth
                             r-hdrcde
                             r-geometry
                             r-feature))
    (home-page "https://cran.r-project.org/package=curvHDR")
    (synopsis "Filtering of Flow Cytometry Samples")
    (description
     "Filtering, also known as gating, of flow cytometry samples using the
@code{curvHDR} method, which is described in Naumann, U., Luta, G. and Wand,
M.P. (2010) <DOI:10.1186/1471-2105-11-44>.")
    (license license:gpl2+)))

(define-public r-curvedepth
  (package
    (name "r-curvedepth")
    (version "0.1.0.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "curveDepth" version))
       (sha256
        (base32 "10mhy2nyll4d1q71qnlsal0raccz3awd0j0vi5w58di9wlv1c241"))))
    (properties `((upstream-name . "curveDepth")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-ddalpha))
    (home-page "https://cran.r-project.org/package=curveDepth")
    (synopsis "Tukey Curve Depth and Distance in the Space of Curves")
    (description
     "Data recorded as paths or trajectories may be suitably described by curves,
which are independent of their parametrization.  For the space of such curves,
the package provides functionalities for reading curves, sampling points on
curves, calculating distance between curves and for computing Tukey curve depth
of a curve w.r.t.  to a bundle of curves.  For details see Lafaye De Micheaux,
Mozharovskyi, and Vimond (2019) <@code{arXiv:1901.00180>}.")
    (license license:gpl2+)))

(define-public r-curvecomp
  (package
    (name "r-curvecomp")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "curvecomp" version))
       (sha256
        (base32 "0ykgbwnh32w61cjcg1nyqak42hx0jrsrpbra2wh3pgj9clg1qad2"))))
    (properties `((upstream-name . "curvecomp")))
    (build-system r-build-system)
    (propagated-inputs (list r-multcomp))
    (home-page "https://cran.r-project.org/package=curvecomp")
    (synopsis "Multiple Curve Comparisons Using Parametric Bootstrap")
    (description
     "This package performs multiple comparison procedures on curve observations among
different treatment groups.  The methods are applicable in a variety of
situations (such as independent groups with equal or unequal sample sizes, or
repeated measures) by using parametric bootstrap.  References to these
procedures can be found at Konietschke, Gel, and Brunner (2014)
<doi:10.1090/conm/622/12431> and Westfall (2011)
<doi:10.1080/10543406.2011.607751>.")
    (license license:gpl2)))

(define-public r-curtailment
  (package
    (name "r-curtailment")
    (version "0.2.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "curtailment" version))
       (sha256
        (base32 "0fdm619c7v0rik603hf44alw5lfr7fjphm5lady4cq21vwdakyac"))))
    (properties `((upstream-name . "curtailment")))
    (build-system r-build-system)
    (propagated-inputs (list r-pkgcond r-gridextra r-ggthemes r-ggplot2
                             r-data-table))
    (home-page "https://github.com/martinlaw/curtailment")
    (synopsis "Finds Binary Outcome Designs Using Stochastic Curtailment")
    (description
     "Finds single- and two-arm designs using stochastic curtailment, as described by
Law et al. (2022) <doi:10.1080/10543406.2021.2009498> and Law et al. (2021)
<doi:10.1002/pst.2067> respectively.  Designs can be single-stage or
multi-stage.  Non-stochastic curtailment is possible as a special case.  Desired
error-rates, maximum sample size and lower and upper anticipated response rates
are inputted and suitable designs are returned with operating characteristics.
Stopping boundaries and visualisations are also available.  The package can find
designs using other approaches, for example designs by Simon (1989)
<doi:10.1016/0197-2456(89)90015-9> and Mander and Thompson (2010)
<doi:10.1016/j.cct.2010.07.008>.  Other features: compare and visualise designs
using a weighted sum of expected sample sizes under the null and alternative
hypotheses and maximum sample size; visualise any binary outcome design.")
    (license license:gpl3+)))

(define-public r-curstatci
  (package
    (name "r-curstatci")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "curstatCI" version))
       (sha256
        (base32 "0igqdv0fzzji10gz3j3ir8qxpy7vdjfl137067rc28qzbrl2sy2c"))))
    (properties `((upstream-name . "curstatCI")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/kimhendrickx/curstatCI")
    (synopsis "Confidence Intervals for the Current Status Model")
    (description
     "Computes the maximum likelihood estimator, the smoothed maximum likelihood
estimator and pointwise bootstrap confidence intervals for the distribution
function under current status data.  Groeneboom and Hendrickx (2017)
<doi:10.1214/17-EJS1345>.")
    (license license:gpl3)))

(define-public r-cursr
  (package
    (name "r-cursr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cursr" version))
       (sha256
        (base32 "08051bnxags2arn296mxwc84j55shhsfym9hd062amdvm23nxd18"))))
    (properties `((upstream-name . "cursr")))
    (build-system r-build-system)
    (propagated-inputs (list r-keypress))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cursr")
    (synopsis "Cursor and Terminal Manipulation")
    (description
     "This package provides a toolbox for developing applications, games, simulations,
or agent-based models in the R terminal.  Included functions allow users to move
the cursor around the terminal screen, change text colors and attributes, clear
the screen, hide and show the cursor, map key presses to functions, draw shapes
and curves, among others.  Most functionalities require users to be in a
terminal (not the R GUI).")
    (license license:expat)))

(define-public r-currr
  (package
    (name "r-currr")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "currr" version))
       (sha256
        (base32 "0dfcgnv71cwzsglg725qsf3vg54yar3ps4f9njwa9183k1gypvqp"))))
    (properties `((upstream-name . "currr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-scales
                             r-rstudioapi
                             r-readr
                             r-purrr
                             r-pacman
                             r-job
                             r-dplyr
                             r-crayon
                             r-clisymbols
                             r-broom))
    (home-page "https://github.com/MarcellGranat/currr")
    (synopsis "Apply Mapping Functions in Frequent Saving")
    (description
     "Implementations of the family of map() functions with frequent saving of the
intermediate results.  The contained functions let you start the evaluation of
the iterations where you stopped (reading the already evaluated ones from
cache), and work with the currently evaluated iterations while remaining ones
are running in a background job.  Parallel computing is also easier with the
workers parameter.")
    (license license:expat)))

(define-public r-curricularanalytics
  (package
    (name "r-curricularanalytics")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CurricularAnalytics" version))
       (sha256
        (base32 "17hgdiwbr2pp5f51091l61qjl4rdl3qp5d417zxj4024sh93l21m"))))
    (properties `((upstream-name . "CurricularAnalytics")))
    (build-system r-build-system)
    (propagated-inputs (list r-visnetwork r-igraph r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Danyulll/CurricularAnalytics")
    (synopsis "Exploring and Analyzing Academic Curricula")
    (description
     "This package provides an implementation of âCurricular Analyticsâ, a
framework for analyzing and quantifying the complexity of academic curricula.
Curricula are modelled as directed acyclic graphs and analytics are provided
based on path lengths and edge density.  This work directly comes from Heileman
et al. (2018) <doi:10.48550/@code{arXiv.1811.09676>}.")
    (license license:expat)))

(define-public r-currentsurvival
  (package
    (name "r-currentsurvival")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "currentSurvival" version))
       (sha256
        (base32 "01rlm4n3qfa71wkd6pbkdhcgll0y13zrcbjqxy0gssvrgnwwcfsx"))))
    (properties `((upstream-name . "currentSurvival")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-cmprsk))
    (home-page "https://cran.r-project.org/package=currentSurvival")
    (synopsis "Estimation of CCI and CLFS Functions")
    (description
     "The @code{currentSurvival} package contains functions for the estimation of the
current cumulative incidence (CCI) and the current leukaemia-free survival
(CLFS).  The CCI is the probability that a patient is alive and in any disease
remission (e.g. complete cytogenetic remission in chronic myeloid leukaemia)
after initiating his or her therapy (e.g. tyrosine kinase therapy for chronic
myeloid leukaemia).  The CLFS is the probability that a patient is alive and in
any disease remission after achieving the first disease remission.")
    (license license:gpl2+)))

(define-public r-currencyapi
  (package
    (name "r-currencyapi")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "currencyapi" version))
       (sha256
        (base32 "1d21nsmnzd89j86rlhicplj6ryp9mvs2jky8p55jc33zn48sywb6"))))
    (properties `((upstream-name . "currencyapi")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://currencyapi.com")
    (synopsis "Client for the 'currencyapi.com' Currency Conversion API")
    (description
     "An R client for the currencyapi.com currency conversion API. The API requires
registration of an API key.  Basic features are free, some require a paid
subscription.  You can find the full API documentation at
<https://currencyapi.com/docs> .")
    (license license:expat)))

(define-public r-curesurv
  (package
    (name "r-curesurv")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "curesurv" version))
       (sha256
        (base32 "12c22m8slw0pj38yxphwf8j9lsjwsim4gmxgs4wqivcgycvjxbqc"))))
    (properties `((upstream-name . "curesurv")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-stringr
                             r-statmod
                             r-randtoolbox
                             r-optimx
                             r-numderiv
                             r-formula
                             r-deriv
                             r-bbmle))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=curesurv")
    (synopsis
     "Mixture and Non Mixture Parametric Cure Models to Estimate Cure Indicators")
    (description
     "Fits a variety of cure models using excess hazard modeling methodology such as
the mixture model proposed by Phillips et al. (2002) <doi:10.1002/sim.1101> The
Weibull distribution is used to represent the survival function of the uncured
patients; Fits also non-mixture cure model such as the time-to-null excess
hazard model proposed by Boussari et al. (2020) <doi:10.1111/biom.13361>.")
    (license license:gpl3+)))

(define-public r-cureplots
  (package
    (name "r-cureplots")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cureplots" version))
       (sha256
        (base32 "1ikjx4bhazqba9p9sd375mrn0321cwb84d7pj7kk1my6grkd123y"))))
    (properties `((upstream-name . "cureplots")))
    (build-system r-build-system)
    (propagated-inputs (list r-glue r-ggplot2 r-dplyr))
    (home-page "https://github.com/gbasulto/cureplots")
    (synopsis "CURE (Cumulative Residual) Plots")
    (description
     "This package creates ggplot2 Cumulative Residual (CURE) plots to check the
goodness-of-fit of a count model; or the tables to create a customized version.
A dataset of crashes in Washington state is available for illustrative purposes.")
    (license license:agpl3+)))

(define-public r-curephem
  (package
    (name "r-curephem")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "curephEM" version))
       (sha256
        (base32 "0c24xasgyr9dcbnmscfc9zj3lh1ja03xnzww0qd9rd5ax7hrciks"))))
    (properties `((upstream-name . "curephEM")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-matrix))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=curephEM")
    (synopsis "NPMLE for Logistic-Cox Cure-Rate Model")
    (description
     "Expectation-Maximization (EM) algorithm for point estimation and variance
estimation to the nonparametric maximum likelihood estimator (NPMLE) for
logistic-Cox cure-rate model with left truncation and right- censoring.  See
Hou, Chambers and Xu (2017) <doi:10.1007/s10985-017-9415-2>.")
    (license license:gpl2)))

(define-public r-curedepcens
  (package
    (name "r-curedepcens")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CureDepCens" version))
       (sha256
        (base32 "1i11yvh19zvv220d3jhnidjxq494wc3jg5054zq1pr09sxh2jnqn"))))
    (properties `((upstream-name . "CureDepCens")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rootsolve r-matrixstats r-formula
                             r-dlm))
    (home-page "https://github.com/GabrielGrandemagne/CureDepCens")
    (synopsis "Dependent Censoring Regression Models with Cure Fraction")
    (description
     "Cure dependent censoring regression models for long-term survival multivariate
data.  These models are based on extensions of the frailty models, capable to
accommodating the cure fraction and the dependence between failure and censoring
times, with Weibull and piecewise exponential marginal distributions.
Theoretical details regarding the models implemented in the package can be found
in Schneider et al. (2022) <doi:10.1007/s10651-022-00549-0>.")
    (license license:gpl3+)))

(define-public r-cureauxsp
  (package
    (name "r-cureauxsp")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CureAuxSP" version))
       (sha256
        (base32 "1aay2hhciq6f79dz5cnqsfrvw6hlfidw4gvy7hyrnbqqlnqjwyr2"))))
    (properties `((upstream-name . "CureAuxSP")))
    (build-system r-build-system)
    (propagated-inputs (list r-tcgabiolinks r-survival r-mvtnorm r-mass r-lars))
    (home-page "<https://github.com/biostat-jieding/CureAuxSP>")
    (synopsis
     "Mixture Cure Models with Auxiliary Subgroup Survival Probabilities")
    (description
     "Estimate mixture cure models with subgroup survival probabilities as auxiliary
information.  A reference of the underlying methods is Jie Ding, Jialiang Li and
Xiaoguang Wang (2024) <doi:10.1093/jrsssc/qlad106>.")
    (license license:gpl2+)))

(define-public r-cure
  (package
    (name "r-cure")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cuRe" version))
       (sha256
        (base32 "0h8vblhfydrama01yzfghcv5yw5ifs719rvq17sixkgj5iyaj910"))))
    (properties `((upstream-name . "cuRe")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-statmod
                             r-rstpm2
                             r-reshape2
                             r-relsurv
                             r-numderiv
                             r-date))
    (home-page "https://github.com/LasseHjort/cuRe")
    (synopsis "Parametric Cure Model Estimation")
    (description
     "This package contains functions for estimating generalized parametric mixture
and non-mixture cure models <doi:10.1016/j.cmpb.2022.107125>, loss of lifetime,
mean residual lifetime, and crude event probabilities.")
    (license license:gpl2+)))

(define-public r-cuperdec
  (package
    (name "r-cuperdec")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cuperdec" version))
       (sha256
        (base32 "1vvkbkb3dp38xzxxdm20n6vr8yifppn1clzzcvb2rhqk9d17cdiw"))))
    (properties `((upstream-name . "cuperdec")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rlang
                             r-readr
                             r-magrittr
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jfy133/cuperdec")
    (synopsis "Cumulative Percent Decay Curve Generator")
    (description
     "Calculates and visualises cumulative percent decay curves, which are typically
calculated from metagenomic taxonomic profiles.  These can be used to estimate
the level of expected endogenous taxa at different abundance levels retrieved
from metagenomic samples, when comparing to samples of known sampling site or
source.  Method described in Fellows Yates, J. A. et.  al. (2021) Proceedings of
the National Academy of Sciences USA <doi:10.1073/pnas.2021655118>.")
    (license license:expat)))

(define-public r-cumulocityr
  (package
    (name "r-cumulocityr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cumulocityr" version))
       (sha256
        (base32 "0ybvh5args3s1f3nra58bnfwgrlrdpw40by68az84s90v88bbz2q"))))
    (properties `((upstream-name . "cumulocityr")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://softwareag.github.io/cumulocityr/")
    (synopsis "Client for the 'Cumulocity' API")
    (description
     "Access the Cumulocity API and retrieve data on devices, measurements, and
events.  Documentation for the API can be found at
<https://www.cumulocity.com/guides/reference/rest-implementation/>.")
    (license license:gpl3)))

(define-public r-cumulcalib
  (package
    (name "r-cumulcalib")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cumulcalib" version))
       (sha256
        (base32 "0md2zvs0n7lrlfxh5208a69jg2wgdwd4jvivf3j50jhhwfclmsw5"))))
    (properties `((upstream-name . "cumulcalib")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/resplab/cumulcalib")
    (synopsis "Cumulative Calibration Assessment for Prediction Models")
    (description
     "This package provides tools for visualization of, and inference on, the
calibration of prediction models on the cumulative domain.  This provides a
method for evaluating calibration of risk prediction models without having to
group the data or use tuning parameters (e.g., loess bandwidth).  This package
implements the methodology described in Sadatsafavi and Patkau (2024)
<doi:10.1002/sim.10138>.  The core of the package is cumulcalib(), which takes
in vectors of binary responses and predicted risks.  The plot() and summary()
methods are implemented for the results returned by cumulcalib().")
    (license license:expat)))

(define-public r-cumstats
  (package
    (name "r-cumstats")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cumstats" version))
       (sha256
        (base32 "119w751z9dg6pjyk389pbl8ab8pirf9sqndi4nxi89ix2bby4xz8"))))
    (properties `((upstream-name . "cumstats")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cumstats")
    (synopsis "Cumulative Descriptive Statistics")
    (description
     "Cumulative descriptive statistics for (arithmetic, geometric, harmonic) mean,
median, mode, variance, skewness and kurtosis.")
    (license license:gpl3)))

(define-public r-cumseg
  (package
    (name "r-cumseg")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cumSeg" version))
       (sha256
        (base32 "0n1hp0abnd6zn72fkgkj9k875vivn5kr3q76sjy6q6va7x24j6sg"))))
    (properties `((upstream-name . "cumSeg")))
    (build-system r-build-system)
    (propagated-inputs (list r-lars))
    (home-page "https://cran.r-project.org/package=cumSeg")
    (synopsis "Change Point Detection in Genomic Sequences")
    (description
     "Estimation of number and location of change points in mean-shift (piecewise
constant) models.  Particularly useful (but not confined) to model genomic
sequences of continuous measurements.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-cumprinc
  (package
    (name "r-cumprinc")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cumprinc" version))
       (sha256
        (base32 "153cjl6x6mm6dix77bv9614nrd7x7qimwkw96mgxwarfpf1172nn"))))
    (properties `((upstream-name . "cumprinc")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cumprinc")
    (synopsis "Functions Centered Around Microsoft Excel Cumprinc Function")
    (description
     "This package provides similar functionality to Microsoft Excel CUMPRINC function
<https://support.microsoft.com/en-us/office/cumprinc-function-94a4516d-bd65-41a1-bc16-053a6af4c04d>.
 Returns principal remaining at a given month, principal paid in a month, and
accumulated principal paid at a given month based on original loan amount,
monthly interest rate, and term of loan.")
    (license license:gpl2+)))

(define-public r-cump
  (package
    (name "r-cump")
    (version "2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CUMP" version))
       (sha256
        (base32 "0rdscywmi4sylpjpr8r472iapddizb1mqyrd532cvw6frxins7w0"))))
    (properties `((upstream-name . "CUMP")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CUMP")
    (synopsis
     "Analyze Multivariate Phenotypes by Combining Univariate Results")
    (description
     "Combining Univariate Association Test Results of Multiple Phenotypes for
Detecting Pleiotropy.")
    (license license:gpl2+)))

(define-public r-cultevo
  (package
    (name "r-cultevo")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cultevo" version))
       (sha256
        (base32 "0rmncp4mrdpf3izhhqn9406i36j3d3d7i8cglip04lkfbypl9jvy"))))
    (properties `((upstream-name . "cultevo")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi r-pspearman r-hmisc r-combinat))
    (native-inputs (list r-knitr))
    (home-page "https://kevinstadler.github.io/cultevo/")
    (synopsis "Tools, Measures and Statistical Tests for Cultural Evolution")
    (description
     "This package provides tools for measuring the compositionality of signalling
systems (in particular the information-theoretic measure due to Spike (2016)
<http://hdl.handle.net/1842/25930> and the Mantel test for distance matrix
correlation (after Dietz 1983) <doi:10.1093/sysbio/32.1.21>), functions for
computing string and meaning distance matrices as well as an implementation of
the Page test for monotonicity of ranks (Page 1963)
<doi:10.1080/01621459.1963.10500843> with exact p-values up to k = 22.")
    (license license:expat)))

(define-public r-cuff
  (package
    (name "r-cuff")
    (version "1.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CUFF" version))
       (sha256
        (base32 "1fhxqnymcam845h8jlwp4al68rm9ajllmpnmarbh48c0vhcziaj8"))))
    (properties `((upstream-name . "CUFF")))
    (build-system r-build-system)
    (propagated-inputs (list r-xtable
                             r-openxlsx
                             r-nlme
                             r-lmertest
                             r-haven
                             r-dt
                             r-dplyr
                             r-clipr))
    (home-page "https://github.com/giguerch/CUFF")
    (synopsis "Charles's Utility Function using Formula")
    (description
     "Utility functions that provides wrapper to descriptive base functions like cor,
mean and table.  It makes use of the formula interface to pass variables to
functions.  It also provides operators to concatenate (%+%), to repeat (%n%) and
manage character vectors for nice display.")
    (license license:gpl2+)))

(define-public r-cuda-ml
  (package
    (name "r-cuda-ml")
    (version "0.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cuda.ml" version))
       (sha256
        (base32 "0vqmy8qs3234gllpymvnf2x4a5g9rcmn9ja8cvccksvx6bh10mgz"))))
    (properties `((upstream-name . "cuda.ml")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-rcpp r-parsnip r-hardhat r-ellipsis))
    (home-page "https://mlverse.github.io/cuda.ml/")
    (synopsis "R Interface for the RAPIDS cuML Suite of Libraries")
    (description
     "R interface for RAPIDS @code{cuML} (<https://github.com/rapidsai/cuml>), a suite
of GPU-accelerated machine learning libraries powered by CUDA
(<https://en.wikipedia.org/wiki/CUDA>).")
    (license license:expat)))

(define-public r-cucumber
  (package
    (name "r-cucumber")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cucumber" version))
       (sha256
        (base32 "0p2y119aqy947jkagw89hvy44pzwx3rhd1ipylpilhj57lzl4l63"))))
    (properties `((upstream-name . "cucumber")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr
                             r-tibble
                             r-testthat
                             r-stringr
                             r-rlang
                             r-purrr
                             r-glue
                             r-fs
                             r-dplyr
                             r-checkmate))
    (native-inputs (list r-quarto))
    (home-page "https://github.com/jakubsob/cucumber")
    (synopsis "Behavior-Driven Development for R")
    (description
     "Write executable specifications in a natural language that describes how your
code should behave.  Write specifications in feature files using Gherkin
language and execute them using functions implemented in R. Use them as an
extension to your testthat tests to provide a high level description of how your
code works.")
    (license license:expat)))

(define-public r-cubist
  (package
    (name "r-cubist")
    (version "0.4.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Cubist" version))
       (sha256
        (base32 "140m4if4g4v74dwhzdp4bgdgy4zzcyplxqd311gfg7dn0kqzzmai"))))
    (properties `((upstream-name . "Cubist")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2 r-lattice))
    (native-inputs (list r-knitr))
    (home-page "https://topepo.github.io/Cubist/")
    (synopsis "Rule- And Instance-Based Regression Modeling")
    (description
     "Regression modeling using rules with added instance-based corrections.")
    (license license:gpl3)))

(define-public r-cubing
  (package
    (name "r-cubing")
    (version "1.0-5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cubing" version))
       (sha256
        (base32 "1q23fplvklaaldicqic0zpnh301m08zb9k21l47zj47g9m9pj4bc"))))
    (properties `((upstream-name . "cubing")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgl))
    (home-page "https://cran.r-project.org/package=cubing")
    (synopsis "Rubik's Cube Solving")
    (description
     "This package provides functions for visualizing, animating, solving and
analyzing the Rubik's cube.  Includes data structures for solvable and
unsolvable cubes, random moves and random state scrambles and cubes, 3D displays
and animations using @code{OpenGL}', patterned cube generation, and lightweight
solvers.  See Rokicki, T. (2008) <@code{arXiv:0803.3435>} for the Kociemba
solver.")
    (license license:gpl3)))

(define-public r-cubicbsplines
  (package
    (name "r-cubicbsplines")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cubicBsplines" version))
       (sha256
        (base32 "1dzwadhhrxgral9x4hxyyy1fyn45pmbwv6wiwfxhivkxmd3s2xdr"))))
    (properties `((upstream-name . "cubicBsplines")))
    (build-system r-build-system)
    (native-inputs (list gfortran))
    (home-page "http://www.statsoc.ulg.ac.be/")
    (synopsis "Computation of a Cubic B-Spline Basis and Its Derivatives")
    (description
     "Computation of a cubic B-spline basis for arbitrary knots.  It also provides the
1st and 2nd derivatives, as well as the integral of the basis elements.  It is
used by the author to fit penalized B-spline models, see e.g. Jullion, A. and
Lambert, P. (2006) <doi:10.1016/j.csda.2006.09.027>, Lambert, P. and Eilers,
P.H.C. (2009) <doi:10.1016/j.csda.2008.11.022> and, more recently, Lambert, P.
(2021) <doi:10.1016/j.csda.2021.107250>.  It is inspired by the algorithm
developed by de Boor, C. (1977) <doi:10.1137/0714026>.")
    (license license:gpl3)))

(define-public r-cubfits
  (package
    (name "r-cubfits")
    (version "0.1-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cubfits" version))
       (sha256
        (base32 "1dg60162s77p82v8vig52yl8ar8h0pijps8kqq35v1hvp5a3ny5q"))))
    (properties `((upstream-name . "cubfits")))
    (build-system r-build-system)
    (propagated-inputs (list r-foreach r-coda))
    (home-page "https://github.com/snoweye/cubfits")
    (synopsis "Codon Usage Bias Fits")
    (description
     "Estimating mutation and selection coefficients on synonymous codon bias usage
based on models of ribosome overhead cost (ROC).  Multinomial logistic
regression and Markov Chain Monte Carlo are used to estimate and predict protein
production rates with/without the presence of expressions and measurement
errors.  Work flows with examples for simulation, estimation and prediction
processes are also provided with parallelization speedup.  The whole framework
is tested with yeast genome and gene expression data of Yassour, et al. (2009)
<doi:10.1073/pnas.0812841106>.")
    (license (license:fsdg-compatible "Mozilla Public License 2.0"))))

(define-public r-cubeview
  (package
    (name "r-cubeview")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cubeview" version))
       (sha256
        (base32 "1352hi2j9x9rx4iy3xvsca86nsh39x1vnymd17f5qc8c3plfm8db"))))
    (properties `((upstream-name . "cubeview")))
    (build-system r-build-system)
    (arguments
     (list
      #:modules '((guix build r-build-system)
                  (guix build minify-build-system)
                  (guix build utils)
                  (ice-9 match))
      #:imported-modules `(,@%r-build-system-modules (guix build
                                                      minify-build-system))
      #:phases '(modify-phases %standard-phases
                  (add-after 'unpack 'process-javascript
                    (lambda* (#:key inputs #:allow-other-keys)
                      (with-directory-excursion "inst/"
                        (for-each (match-lambda
                                    ((source . target) (minify source
                                                               #:target target)))
                                  '())))))))
    (propagated-inputs (list r-viridislite
                             r-stars
                             r-raster
                             r-lattice
                             r-htmlwidgets
                             r-htmltools
                             r-base64enc))
    (native-inputs (list esbuild))
    (home-page "https://cran.r-project.org/package=cubeview")
    (synopsis "View 3D Raster Cubes Interactively")
    (description
     "This package creates a 3D data cube view of a @code{RasterStack/Brick},
typically a collection/array of @code{RasterLayers} (along z-axis) with the same
geographical extent (x and y dimensions) and resolution, provided by package
raster'.  Slices through each dimension (x/y/z), freely adjustable in location,
are mapped to the visible sides of the cube.  The cube can be freely rotated.
Zooming and panning can be used to focus on different areas of the cube.")
    (license license:expat)))

(define-public r-cubelyr
  (package
    (name "r-cubelyr")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cubelyr" version))
       (sha256
        (base32 "154vwf5pj2jh66wqdh78nc0v722b4rh88hss24g5lc31wlghzc8q"))))
    (properties `((upstream-name . "cubelyr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tibble
                             r-rlang
                             r-purrr
                             r-pillar
                             r-glue
                             r-dplyr))
    (home-page "https://github.com/hadley/cubelyr")
    (synopsis "Data Cube 'dplyr' Backend")
    (description
     "An implementation of a data cube extracted out of dplyr for backward
compatibility.")
    (license license:expat)))

(define-public r-cubble
  (package
    (name "r-cubble")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cubble" version))
       (sha256
        (base32 "0x05mizhhmy332ivhly5g8184s2b0q394rj2klf27qfi1fyp1vg5"))))
    (properties `((upstream-name . "cubble")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-tsibble
                             r-tidyselect
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-sf
                             r-rlang
                             r-ncdf4
                             r-lubridate
                             r-glue
                             r-ggplot2
                             r-dplyr
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/huizezhang-sherry/cubble")
    (synopsis "Vector Spatio-Temporal Data Structure for Data Analysis")
    (description
     "This package provides a spatiotemperal data object in a relational data
structure to separate the recording of time variant/ invariant variables.  See
the Journal of Statistical Software reference: <doi:10.18637/jss.v110.i07>.")
    (license license:expat)))

(define-public r-cubar
  (package
    (name "r-cubar")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cubar" version))
       (sha256
        (base32 "1hggjq1p6xcffvr13pxjc4345gzrbaxppryn6ijf2b56ffzy7xgx"))))
    (properties `((upstream-name . "cubar")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-iranges r-ggplot2 r-data-table
                             r-biostrings))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mt1022/cubar")
    (synopsis "Codon Usage Bias Analysis")
    (description
     "This package provides a suite of functions for rapid and flexible analysis of
codon usage bias.  It provides in-depth analysis at the codon level, including
relative synonymous codon usage (RSCU), @code{tRNA} weight calculations, machine
learning predictions for optimal or preferred codons, and visualization of
codon-anticodon pairing.  Additionally, it can calculate various gene- specific
codon indices such as codon adaptation index (CAI), effective number of codons
(ENC), fraction of optimal codons (Fop), @code{tRNA} adaptation index
(@code{tAI}), mean codon stabilization coefficients (CSCg), and GC contents
(GC/GC3s/GC4d).  It also supports both standard and non-standard genetic code
tables found in NCBI, as well as custom genetic code tables.")
    (license license:expat)))

(define-public r-cub
  (package
    (name "r-cub")
    (version "1.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CUB" version))
       (sha256
        (base32 "0i9fpjasvmsprgfp28f46xvwmd71qqmvwqaibvc8kh47ghjnfpzv"))))
    (properties `((upstream-name . "CUB")))
    (build-system r-build-system)
    (propagated-inputs (list r-formula))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CUB")
    (synopsis "Class of Mixture Models for Ordinal Data")
    (description
     "For ordinal rating data, estimate and test models within the family of CUB
models and their extensions (where CUB stands for Combination of a discrete
Uniform and a shifted Binomial distributions); Simulation routines, plotting
facilities and fitting measures are also provided.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-cuadramelo
  (package
    (name "r-cuadramelo")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cuadramelo" version))
       (sha256
        (base32 "08n1g32lfbm8mjg1m9brxbqbjlxxbpfv8gfwzqv6mjdsiri00qiw"))))
    (properties `((upstream-name . "cuadramelo")))
    (build-system r-build-system)
    (propagated-inputs (list r-dplyr r-cvxr))
    (native-inputs (list r-knitr))
    (home-page "https://mserrano-ine.github.io/cuadramelo/")
    (synopsis "Matrix Balancing and Rounding")
    (description
     "Balancing and rounding matrices subject to restrictions.  Adjustment of matrices
so that columns and rows add up to given vectors, rounding of a matrix while
keeping the column and/or row totals, performing these by blocks...")
    (license license:gpl3+)))

(define-public r-ctypesio
  (package
    (name "r-ctypesio")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctypesio" version))
       (sha256
        (base32 "0flgxsby1nazs3dwnjwzkz1p964qygyivmifnrb2b2sy7smda41f"))))
    (properties `((upstream-name . "ctypesio")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/coolbutuseless/ctypesio")
    (synopsis
     "Read and Write Standard C Types from Files, Connections and Raw Vectors")
    (description
     "Interacting with binary files can be difficult because R's types are a subset of
what is generally supported by C'.  This package provides a suite of functions
for reading and writing binary data (with files, connections, and raw vectors)
using C type descriptions.  These functions convert data between C types and R
types while checking for values outside the type limits, NA values, etc.")
    (license license:expat)))

(define-public r-ctxr
  (package
    (name "r-ctxr")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctxR" version))
       (sha256
        (base32 "1m3hj5cwghm7nx9s5z3j6yby2i04ykich213x6j0gps4n4c8zanr"))))
    (properties `((upstream-name . "ctxR")))
    (build-system r-build-system)
    (propagated-inputs (list r-urltools
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-purrr
                             r-jsonlite
                             r-httr
                             r-data-table
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/USEPA/ctxR")
    (synopsis "Utilities for Interacting with the 'CTX' APIs")
    (description
     "Access chemical, hazard, bioactivity, and exposure data from the Computational
Toxicology and Exposure ('CTX') APIs <https://api-ccte.epa.gov/docs/>.
@code{ctxR} was developed to streamline the process of accessing the information
available through the CTX APIs without requiring prior knowledge of how to use
APIs.  Most data is also available on the @code{CompTox} Chemical Dashboard
('CCD') <https://comptox.epa.gov/dashboard/> and other resources found at the
EPA Computational Toxicology and Exposure Online Resources
<https://www.epa.gov/comptox-tools>.")
    (license license:gpl3+)))

(define-public r-ctv
  (package
    (name "r-ctv")
    (version "0.9-5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctv" version))
       (sha256
        (base32 "1mr37p7mdv2p8rswz9clwj25ipm16pc4a7flwg3a4bgyj1n5mz55"))))
    (properties `((upstream-name . "ctv")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/cran-task-views/ctv/")
    (synopsis "CRAN Task Views")
    (description
     "Infrastructure for task views to CRAN-style repositories: Querying task views
and installing the associated packages (client-side tools), generating HTML
pages and storing task view information in the repository (server-side tools).")
    (license (list license:gpl2 license:gpl3))))

(define-public r-cttshiny
  (package
    (name "r-cttshiny")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CTTShiny" version))
       (sha256
        (base32 "1c9vsiqyig6kfjpy3dfrysc466h4v9530m49aynz65i1njplswyh"))))
    (properties `((upstream-name . "CTTShiny")))
    (build-system r-build-system)
    (propagated-inputs (list r-shinyace r-shiny r-psych r-ltm r-ctt))
    (home-page "https://cran.r-project.org/package=CTTShiny")
    (synopsis "Classical Test Theory via Shiny")
    (description
     "Interactive shiny application for running classical test theory (item analysis).")
    (license license:gpl3)))

(define-public r-cttinshiny
  (package
    (name "r-cttinshiny")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CTTinShiny" version))
       (sha256
        (base32 "1dc6kaxajkvviszmrcvhh9cg2k8g1hbpf1f6fg3wlgnb80fsx9b7"))))
    (properties `((upstream-name . "CTTinShiny")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-foreign r-ctt))
    (home-page "https://cran.r-project.org/package=CTTinShiny")
    (synopsis "Shiny Interface for the CTT Package")
    (description
     "This package provides a Shiny interface developed in close coordination with the
CTT package, providing a GUI that guides the user through CTT analyses.")
    (license license:gpl2)))

(define-public r-ctt
  (package
    (name "r-ctt")
    (version "2.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CTT" version))
       (sha256
        (base32 "02z354gf7rzh9xzyflmsag4hgmqgv3sr9s9ja903rwdz1pjqrlff"))))
    (properties `((upstream-name . "CTT")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CTT")
    (synopsis "Classical Test Theory Functions")
    (description
     "This package provides a collection of common test and item analyses from a
classical test theory (CTT) framework.  Analyses can be applied to both
dichotomous and polytomous data.  Functions provide reliability analyses
(alpha), item statistics, disctractor analyses, disattenuated correlations,
scoring routines, and empirical ICCs.")
    (license license:gpl2+)))

(define-public r-ctshiny2
  (package
    (name "r-ctshiny2")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CTShiny2" version))
       (sha256
        (base32 "13klj1h0m80hlf5hbbzm2xriy37ky772pk1fm4b6k3xma7ss2a6q"))))
    (properties `((upstream-name . "CTShiny2")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny
                             r-rpart-plot
                             r-rpart
                             r-rmarkdown
                             r-rhandsontable
                             r-party
                             r-e1071
                             r-dplyr
                             r-caret))
    (home-page "https://cran.r-project.org/package=CTShiny2")
    (synopsis
     "Interactive Document for Working with Classification Tree Analysis")
    (description
     "An interactive document on the topic of classification tree analysis using
rmarkdown and shiny packages.  Runtime examples are provided in the package
function as well as at <https://kartikeyab.shinyapps.io/CTShiny/>.")
    (license license:gpl2)))

(define-public r-ctshiny
  (package
    (name "r-ctshiny")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CTShiny" version))
       (sha256
        (base32 "0lmzf02w8j4rgz1kh7jwvl0sb6y38r56gwmsf7pkc00w1dskb722"))))
    (properties `((upstream-name . "CTShiny")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny
                             r-rpart-plot
                             r-rpart
                             r-rmarkdown
                             r-rhandsontable
                             r-party
                             r-e1071
                             r-dplyr
                             r-caret))
    (home-page "https://cran.r-project.org/package=CTShiny")
    (synopsis
     "Interactive Document for Working with Classification Tree Analysis")
    (description
     "An interactive document on the topic of classification tree analysis using
rmarkdown and shiny packages.  Runtime examples are provided in the package
function as well as at <https://kartikeyab.shinyapps.io/CTShiny/>.")
    (license license:gpl2)))

(define-public r-ctsfeatures
  (package
    (name "r-ctsfeatures")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctsfeatures" version))
       (sha256
        (base32 "0nmqx56mbmanq6y3msdkii144srgxvyl0lzwhixm719xhjii39w3"))))
    (properties `((upstream-name . "ctsfeatures")))
    (build-system r-build-system)
    (propagated-inputs (list r-tsibble
                             r-rdpack
                             r-latex2exp
                             r-ggplot2
                             r-bolstad2
                             r-astsa))
    (home-page "https://cran.r-project.org/package=ctsfeatures")
    (synopsis "Analyzing Categorical Time Series")
    (description
     "An implementation of several functions for feature extraction in categorical
time series datasets.  Specifically, some features related to marginal
distributions and serial dependence patterns can be computed.  These features
can be used to feed clustering and classification algorithms for categorical
time series, among others.  The package also includes some interesting datasets
containing biological sequences.  Practitioners from a broad variety of fields
could benefit from the general framework provided by ctsfeatures'.")
    (license license:gpl2)))

(define-public r-ctsemomx
  (package
    (name "r-ctsemomx")
    (version "1.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctsemOMX" version))
       (sha256
        (base32 "1vr7zpxfhwzj8v54dzgk42hvjb4433y9r8al9069prkrvlv74gx8"))))
    (properties `((upstream-name . "ctsemOMX")))
    (build-system r-build-system)
    (propagated-inputs (list r-plyr r-openmx r-matrix r-ctsem))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/cdriveraus/ctsemOMX")
    (synopsis "Continuous Time SEM - 'OpenMx' Based Functions")
    (description
     "Original ctsem (continuous time structural equation modelling) functionality,
based on the @code{OpenMx} software, as described in Driver, Oud, Voelkle (2017)
<doi:10.18637/jss.v077.i05>, with updated details in vignette.  Combines
stochastic differential equations representing latent processes with structural
equation measurement models.  These functions were split off from the main
package of ctsem', as the main package uses the rstan package as a backend now
-- offering estimation options from max likelihood to Bayesian.  There are
nevertheless use cases for the wide format SEM style approach as offered here,
particularly when there are no individual differences in observation timing and
the number of individuals is large.  For the main ctsem package, see
<https://cran.r-project.org/package=ctsem>.")
    (license license:gpl3)))

(define-public r-ctsem
  (package
    (name "r-ctsem")
    (version "3.10.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctsem" version))
       (sha256
        (base32 "040risfqqb8zbnd9ingfv6labqg8lry43943h2kr6vlaq4h3jdwb"))))
    (properties `((upstream-name . "ctsem")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-statmod
                             r-stanheaders
                             r-rstantools
                             r-rstan
                             r-rcppparallel
                             r-rcppeigen
                             r-rcpp
                             r-plyr
                             r-mvtnorm
                             r-mize
                             r-matrix
                             r-mass
                             r-ggplot2
                             r-expm
                             r-deriv
                             r-data-table
                             r-code
                             r-bh))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/cdriveraus/ctsem")
    (synopsis "Continuous Time Structural Equation Modelling")
    (description
     "Hierarchical continuous (and discrete) time state space modelling, for linear
and nonlinear systems measured by continuous variables, with limited support for
binary data.  The subject specific dynamic system is modelled as a stochastic
differential equation (SDE) or difference equation, measurement models are
typically multivariate normal factor models.  Linear mixed effects SDE's
estimated via maximum likelihood and optimization are the default.
Nonlinearities, (state dependent parameters) and random effects on all
parameters are possible, using either max likelihood / max a posteriori
optimization (with optional importance sampling) or Stan's Hamiltonian Monte
Carlo sampling.  See
<https://github.com/cdriveraus/ctsem/raw/master/vignettes/hierarchicalmanual.pdf>
for details.  Priors may be used.  For the conceptual overview of the
hierarchical Bayesian linear SDE approach, see
<https://www.researchgate.net/publication/324093594_Hierarchical_Bayesian_Continuous_Time_Dynamic_Modeling>.
 Exogenous inputs may also be included, for an overview of such possibilities
see
<https://www.researchgate.net/publication/328221807_Understanding_the_Time_Course_of_Interventions_with_Continuous_Time_Dynamic_Models>
.  Stan based functions are not available on 32 bit Windows systems at present.
<https://cdriver.netlify.app/> contains some tutorial blog posts.")
    (license license:gpl3)))

(define-public r-ctrlgene
  (package
    (name "r-ctrlgene")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctrlGene" version))
       (sha256
        (base32 "0x7j11v7jj4k1jml6lrnjq79awhrvsm3pig1yxsd337jlfml3ra9"))))
    (properties `((upstream-name . "ctrlGene")))
    (build-system r-build-system)
    (propagated-inputs (list r-psych))
    (home-page "http://www.bioinf.com.cn/")
    (synopsis "Assess the Stability of Candidate Housekeeping Genes")
    (description
     "This package provides a simple way to assess the stability of candidate
housekeeping genes is implemented in this package.")
    (license license:gpl2+)))

(define-public r-ctring
  (package
    (name "r-ctring")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CTRing" version))
       (sha256
        (base32 "1gi8xmd7hs23war2ixxgbmmkairrmbjdfmlkrzbaqlbwl3pgz5r9"))))
    (properties `((upstream-name . "CTRing")))
    (build-system r-build-system)
    (propagated-inputs (list r-xring r-oro-dicom r-functional))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CTRing")
    (synopsis "Density Profiles of Wood from CT Scan Images")
    (description
     "Computerized tomography (CT) can be used to assess certain wood properties when
wood disks or logs are scanned.  Wood density profiles (i.e.  variations of wood
density from pith to bark) can yield important information used for studies in
forest resource assessment, wood quality and dendrochronology studies.  The
first step consists in transforming grey values from the scan images to density
values.  The packages then proposes a unique method to automatically locate the
pith by combining an adapted Hough Transform method and a one-dimensional edge
detector.  Tree ring profiles (average ring density, earlywood and latewood
density, ring width and percent latewood for each ring) are then obtained.")
    (license license:gpl3)))

(define-public r-ctqr
  (package
    (name "r-ctqr")
    (version "2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctqr" version))
       (sha256
        (base32 "050v5am4cmr6y35ygppabs32hlzpngfqy1wdpqwc76kc3m097mlr"))))
    (properties `((upstream-name . "ctqr")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-pch))
    (home-page "https://cran.r-project.org/package=ctqr")
    (synopsis "Censored and Truncated Quantile Regression")
    (description "Estimation of quantile regression models for survival data.")
    (license license:gpl2)))

(define-public r-ctpm
  (package
    (name "r-ctpm")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctpm" version))
       (sha256
        (base32 "1bycdh3mbimmfvv3yb50c8rwcmkbjj0jwnfiynsp2h56y3dmzc1r"))))
    (properties `((upstream-name . "ctpm")))
    (build-system r-build-system)
    (propagated-inputs (list r-slouch r-ctmm r-clusterr r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/NoonanM/ctpm")
    (synopsis "Continuous-Time Phylogenetic Modeling")
    (description
     "This package provides functions for identifying, fitting, and applying
continuous-time stochastic models to phylogenetic data.  The package is based on
methods introduced in Noonan et al. (2021) <doi:10.1101/2021.05.21.445056>.")
    (license license:gpl3)))

(define-public r-ctost
  (package
    (name "r-ctost")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cTOST" version))
       (sha256
        (base32 "15vynxc2zyqv0wly4paa4b2j5z0yw0qqkm2adsj9cm5x7cfv1k4p"))))
    (properties `((upstream-name . "cTOST")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmarkdown r-powertost r-owenq r-knitr r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/yboulag/cTOST")
    (synopsis
     "Finite Sample Correction of the Two One-Sided Tests in the Univariate Framework")
    (description
     "This package provides a system containing easy-to-use tools to compute the
bioequivalence assessment in the univariate framework using the methods proposed
in Boulaguiem et al. (2023) <doi:10.1101/2023.03.11.532179>.")
    (license license:agpl3)))

(define-public r-ctnote
  (package
    (name "r-ctnote")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CTNote" version))
       (sha256
        (base32 "078h48y42skjdknamyznnl2g7jl3vicdggmx7w7rd3wc1lnm7l8f"))))
    (properties `((upstream-name . "CTNote")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-stringi))
    (native-inputs (list r-knitr))
    (home-page "https://ctn-0094.github.io/CTNote/")
    (synopsis "CTN Outcomes, Treatments, and Endpoints")
    (description
     "The Clinical Trials Network (CTN) of the U.S. National Institute of Drug Abuse
sponsored the CTN-0094 research team to harmonize data sets from three
nationally-representative clinical trials for opioid use disorder (OUD).  The
CTN-0094 team herein provides a coded collection of trial outcomes and endpoints
used in various OUD clinical trials over the past 50 years.  These coded outcome
functions are used to contrast and cluster different clinical outcome functions
based on daily or weekly patient urine screenings.  Note that we abbreviate
urine drug screen as \"UDS\" and urine opioid screen as \"UOS\".  For the example
data sets (based on clinical trials data harmonized by the CTN-0094 research
team), UDS and UOS are largely interchangeable.")
    (license license:gpl3)))

(define-public r-ctmva
  (package
    (name "r-ctmva")
    (version "1.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctmva" version))
       (sha256
        (base32 "0nfn6l31bsifrb1szsrig6l4023svsr81lqnq072yi6441klyf81"))))
    (properties `((upstream-name . "ctmva")))
    (build-system r-build-system)
    (propagated-inputs (list r-polynom r-fda))
    (home-page "https://cran.r-project.org/package=ctmva")
    (synopsis "Continuous-Time Multivariate Analysis")
    (description
     "This package implements a basis function or functional data analysis framework
for several techniques of multivariate analysis in continuous-time setting.
Specifically, we introduced continuous-time analogues of several classical
techniques of multivariate analysis, such as principal component analysis,
canonical correlation analysis, Fisher linear discriminant analysis, K-means
clustering, and so on.  Details are in Biplab Paul, Philip T. Reiss and Erjia
Cui (2023) \"Continuous-time multivariate analysis\"
<doi:10.48550/@code{arXiv.2307.09404>}.")
    (license license:gpl2+)))

(define-public r-ctmm
  (package
    (name "r-ctmm")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctmm" version))
       (sha256
        (base32 "0fmihi6ihk4jgg0abyhlfhg4wx91sq06xr11dc0vbhcyaq2090r4"))))
    (properties `((upstream-name . "ctmm")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra
                             r-statmod
                             r-sp
                             r-shape
                             r-sf
                             r-raster
                             r-pracma
                             r-pbivnorm
                             r-parsedate
                             r-numderiv
                             r-mass
                             r-manipulate
                             r-gsl
                             r-gmedian
                             r-fasttime
                             r-expm
                             r-digest
                             r-data-table
                             r-bessel))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ctmm-initiative/ctmm")
    (synopsis "Continuous-Time Movement Modeling")
    (description
     "This package provides functions for identifying, fitting, and applying
continuous-space, continuous-time stochastic-process movement models to animal
tracking data.  The package is described in Calabrese et al (2016)
<doi:10.1111/2041-210X.12559>, with models and methods based on those introduced
and detailed in Fleming & Calabrese et al (2014) <doi:10.1086/675504>, Fleming
et al (2014) <doi:10.1111/2041-210X.12176>, Fleming et al (2015)
<doi:10.1103/@code{PhysRevE.91.032107>}, Fleming et al (2015)
<doi:10.1890/14-2010.1>, Fleming et al (2016) <doi:10.1890/15-1607>, PÃ©ron &
Fleming et al (2016) <doi:10.1186/s40462-016-0084-7>, Fleming & Calabrese (2017)
<doi:10.1111/2041-210X.12673>, PÃ©ron et al (2017) <doi:10.1002/ecm.1260>,
Fleming et al (2017) <doi:10.1016/j.ecoinf.2017.04.008>, Fleming et al (2018)
<doi:10.1002/eap.1704>, Winner & Noonan et al (2018)
<doi:10.1111/2041-210X.13027>, Fleming et al (2019)
<doi:10.1111/2041-210X.13270>, Noonan & Fleming et al (2019)
<doi:10.1186/s40462-019-0177-1>, Fleming et al (2020)
<doi:10.1101/2020.06.12.130195>, Noonan et al (2021)
<doi:10.1111/2041-210X.13597>, Fleming et al (2022)
<doi:10.1111/2041-210X.13815>, Silva et al (2022) <doi:10.1111/2041-210X.13786>,
Alston & Fleming et al (2023) <doi:10.1111/2041-210X.14025>.")
    (license license:gpl3)))

(define-public r-ctmle
  (package
    (name "r-ctmle")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctmle" version))
       (sha256
        (base32 "0qc1ji8fjpr88dn6mrpijfcx1ij4zkrxsbcw405hxal7rli0gyp3"))))
    (properties `((upstream-name . "ctmle")))
    (build-system r-build-system)
    (propagated-inputs (list r-tmle r-superlearner r-glmnet))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ctmle")
    (synopsis "Collaborative Targeted Maximum Likelihood Estimation")
    (description
     "This package implements the general template for collaborative targeted maximum
likelihood estimation.  It also provides several commonly used C-TMLE
instantiation, like the vanilla/scalable variable-selection C-TMLE (Ju et al.
(2017) <doi:10.1177/0962280217729845>) and the glmnet-C-TMLE algorithm (Ju et
al. (2017) <@code{arXiv:1706.10029>}).")
    (license license:gpl2)))

(define-public r-ctmcmove
  (package
    (name "r-ctmcmove")
    (version "1.2.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctmcmove" version))
       (sha256
        (base32 "1pxyxbbhfa8arqfb7qw10ya1b8hy9ylqbqqzys6d9dsixvdk98h0"))))
    (properties `((upstream-name . "ctmcmove")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp r-raster r-matrix r-gdistance r-fda))
    (home-page "https://cran.r-project.org/package=ctmcmove")
    (synopsis
     "Modeling Animal Movement with Continuous-Time Discrete-Space Markov Chains")
    (description
     "Software to facilitates taking movement data in xyt format and pairing it with
raster covariates within a continuous time Markov chain (CTMC) framework.  As
described in Hanks et al. (2015) <DOI:10.1214/14-AOAS803> , this allows flexible
modeling of movement in response to covariates (or covariate gradients) with
model fitting possible within a Poisson GLM framework.")
    (license license:gpl2)))

(define-public r-ctmcd
  (package
    (name "r-ctmcd")
    (version "1.4.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctmcd" version))
       (sha256
        (base32 "0w0dhxw9qdh7p59d4xkm3h5zhmvawgy9lsw84nh9vphrqrzbfghm"))))
    (properties `((upstream-name . "ctmcd")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-numderiv r-expm r-coda))
    (native-inputs (list r-r-rsp r-knitr))
    (home-page "https://cran.r-project.org/package=ctmcd")
    (synopsis
     "Estimating the Parameters of a Continuous-Time Markov Chain from Discrete-Time Data")
    (description
     "Estimation of Markov generator matrices from discrete-time observations.  The
implemented approaches comprise diagonal and weighted adjustment of matrix
logarithm based candidate solutions as in Israel (2001)
<doi:10.1111/1467-9965.00114> as well as a quasi-optimization approach.
Moreover, the expectation-maximization algorithm and the Gibbs sampling approach
of Bladt and Sorensen (2005) <doi:10.1111/j.1467-9868.2005.00508.x> are
included.")
    (license license:gpl3)))

(define-public r-ctm
  (package
    (name "r-ctm")
    (version "0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CTM" version))
       (sha256
        (base32 "0h1lpygjq46nwkn4km49bngvxmgrnh3csrfln3yjr9yyzs7d3lz1"))))
    (properties `((upstream-name . "CTM")))
    (build-system r-build-system)
    (propagated-inputs (list r-plyr r-jiebar))
    (home-page "https://cran.r-project.org/package=CTM")
    (synopsis "Text Mining Toolkit for Chinese Document")
    (description
     "The CTM package is designed to solve problems of text mining and is specific for
Chinese document.")
    (license license:gpl3)))

(define-public r-ctl
  (package
    (name "r-ctl")
    (version "1.0.0-10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctl" version))
       (sha256
        (base32 "0wzav2307w6vbj1ksrg8qqfk1l97fclfl4i9w3sj6a238s0am3dv"))))
    (properties `((upstream-name . "ctl")))
    (build-system r-build-system)
    (propagated-inputs (list r-qtl r-mass))
    (home-page "https://cran.r-project.org/package=ctl")
    (synopsis "Correlated Trait Locus Mapping")
    (description
     "Identification and network inference of genetic loci associated with correlation
changes in quantitative traits (called correlated trait loci, CTLs).  Arends et
al. (2016) <doi:10.21105/joss.00087>.")
    (license license:gpl3)))

(define-public r-cthresher
  (package
    (name "r-cthresher")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cthreshER" version))
       (sha256
        (base32 "18b66d08dq8pvnixmm4ir4r800b37z5yillaa88l317mdilbci9s"))))
    (properties `((upstream-name . "cthreshER")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix))
    (home-page "https://arxiv.org/abs/1611.02609")
    (synopsis "Continuous Threshold Expectile Regression")
    (description
     "Estimation and inference methods for the continuous threshold expectile
regression.  It can fit the continuous threshold expectile regression and test
the existence of change point, for the paper, \"Feipeng Zhang and Qunhua Li
(2016).  A continuous threshold expectile regression, submitted.\".")
    (license license:gpl2+)))

(define-public r-cthist
  (package
    (name "r-cthist")
    (version "2.1.11")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cthist" version))
       (sha256
        (base32 "01d5fkc15k96bp3ymvxlf27789d4wl1913w0vlshq0sdaknsq1xy"))))
    (properties `((upstream-name . "cthist")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-readr
                             r-purrr
                             r-magrittr
                             r-lubridate
                             r-jsonlite
                             r-httr
                             r-dplyr
                             r-assertthat))
    (home-page "https://github.com/bgcarlisle/cthist")
    (synopsis "Clinical Trial Registry History")
    (description
     "Retrieves historical versions of clinical trial registry entries from
<https://@code{ClinicalTrials.gov>}.  Package functionality and implementation
for v 1.0.0 is documented in Carlisle (2022) <DOI:10.1371/journal.pone.0270909>.")
    (license license:agpl3+)))

(define-public r-ctgt
  (package
    (name "r-ctgt")
    (version "2.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctgt" version))
       (sha256
        (base32 "0yiclmpnpzzqv1d76bk97dwq9x44l5v7rlk2dknrx8j3zj4svais"))))
    (properties `((upstream-name . "ctgt")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-bh))
    (home-page "https://cran.r-project.org/package=ctgt")
    (synopsis "Closed Testing with Globaltest for Pathway Analysis")
    (description
     "This package provides a shortcut procedure is proposed to implement closed
testing for large-scale multiple testings, especially with the global test.
This shortcut is asymptotically equivalent to closed testing and post hoc.
Users could detect any possible sets of features or pathways with family-wise
error rate controlled.  The global test is powerful to detect associations
between a group of features and an outcome of interest.")
    (license license:gpl2+)))

(define-public r-ctgdist
  (package
    (name "r-ctgdist")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctgdist" version))
       (sha256
        (base32 "1m3ryppfvd984n5xfphjqhi9i1sigl17v897mqaichj21dzaq62f"))))
    (properties `((upstream-name . "ctgdist")))
    (build-system r-build-system)
    (propagated-inputs (list r-mirt))
    (home-page "https://cran.r-project.org/package=ctgdist")
    (synopsis "Likert Category Distance Calculator")
    (description
     "It is assumed that psychological distances between the categories are equal for
the measurement instruments consisted of polytomously scored items.  According
to Muraki, this assumption must be tested.  In the examination process of this
assumption, the fit indexes are obtained and evaluated.  This package provides
that this assumption is removed.  By with this package, the converted scale
values of all items in a measurement instrument can be calculated by estimating
a category parameter set for each item.  Thus, the calculations can be made
without any need to usage of the common category parameter set.  Through this
package, the psychological distances of the items are scaled.  The scaling of a
category parameter set for each item cause differentiation of score of the
categories will be got from items.  Also, the total measurement instrument score
of an individual can be calculated according to the scaling of item score
categories by with this package.This package provides that the place of
individuals related to the structure to be measured with a measurement
instrument consisted of polytomously scored items can be reveal more accurately.
 In this way, it is thought that the results obtained about individuals can be
made more sensitive, and the differences between individuals can be revealed
more accurately.  On the other hand, it can be argued that more accurate
evidences can be obtained regarding the psychometric properties of the
measurement instruments.")
    (license license:gpl2)))

(define-public r-ctf
  (package
    (name "r-ctf")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctf" version))
       (sha256
        (base32 "1vwqfh1y2if79rkpy6b0ay50fyis7h5rlpvhgikahnmcr2q5l14m"))))
    (properties `((upstream-name . "ctf")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-iotools))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/julianofhernandez/ctf")
    (synopsis "Read and Write Column Text Format (CTF)")
    (description
     "Column Text Format (CTF) is a new tabular data format designed for simplicity
and performance.  CTF is the simplest column store you can imagine: plain text
files for each column in a table, and a metadata file.  The underlying plain
text means the data is human readable and familiar to programmers, unlike
specialized binary formats.  CTF is faster than row oriented formats like CSV
when loading a subset of the columns in a table.  This package provides
functions to read and write CTF data from R.")
    (license license:expat)))

(define-public r-ctd
  (package
    (name "r-ctd")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CTD" version))
       (sha256
        (base32 "0wvz1b7dyypamaxr1zp836sxj2a9xi8yp8lnbbsjp8djpzvcv7gm"))))
    (properties `((upstream-name . "CTD")))
    (build-system r-build-system)
    (propagated-inputs (list r-igraph))
    (home-page "https://cran.r-project.org/package=CTD")
    (synopsis "Method for 'Connecting The Dots' in Weighted Graphs")
    (description
     "This package provides a method for pattern discovery in weighted graphs as
outlined in Thistlethwaite et al. (2021) <doi:10.1371/journal.pcbi.1008550>.
Two use cases are achieved: 1) Given a weighted graph and a subset of its nodes,
do the nodes show significant connectedness? 2) Given a weighted graph and two
subsets of its nodes, are the subsets close neighbors or distant?")
    (license license:expat)))

(define-public r-ctbi
  (package
    (name "r-ctbi")
    (version "2.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ctbi" version))
       (sha256
        (base32 "0gsjbj6nn909i3nh9h6i0d7bdd8zmqdcnajdc29811vv00yf2rz3"))))
    (properties `((upstream-name . "ctbi")))
    (build-system r-build-system)
    (propagated-inputs (list r-data-table))
    (home-page "https://github.com/fritte2/ctbi")
    (synopsis "Procedure to Clean, Decompose and Aggregate Timeseries")
    (description
     "Clean, decompose and aggregate univariate time series following the procedure
\"Cyclic/trend decomposition using bin interpolation\" and the Logbox method for
flagging outliers, both detailed in Ritter, F.: Technical note: A procedure to
clean, decompose, and aggregate time series, Hydrol.  Earth Syst.  Sci., 27,
349â361, <doi:10.5194/hess-27-349-2023>, 2023.")
    (license license:gpl3)))

(define-public r-ctashiny
  (package
    (name "r-ctashiny")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CTAShiny" version))
       (sha256
        (base32 "18qw8nx1r4gwlxj9zxn4hllpn29fv3i4fgwyl5fh3qsv9hmbvi0x"))))
    (properties `((upstream-name . "CTAShiny")))
    (build-system r-build-system)
    (propagated-inputs (list r-shinymatrix r-shiny r-rpivottable r-epitools))
    (home-page "https://cran.r-project.org/package=CTAShiny")
    (synopsis "Interactive Application for Working with Contingency Tables")
    (description
     "An interactive application for working with contingency Tables.  The application
has a template for solving contingency table problems like chisquare test of
independence,association plot between two categorical variables.  Runtime
examples are provided in the package function as well as at
<https://jarvisatharva.shinyapps.io/@code{CategoricalDataAnalysis/>}.")
    (license license:gpl2)))

(define-public r-cta
  (package
    (name "r-cta")
    (version "1.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cta" version))
       (sha256
        (base32 "1i8psw6p6f4633ad17apm6v5ikrpv1dagm0s8pggpsjbbw8d655v"))))
    (properties `((upstream-name . "cta")))
    (build-system r-build-system)
    (propagated-inputs (list r-numderiv r-limsolve r-intervals))
    (home-page "https://cran.r-project.org/package=cta")
    (synopsis "Contingency Table Analysis Based on ML Fitting of MPH Models")
    (description
     "Contingency table analysis is performed based on maximum likelihood (ML) fitting
of multinomial-Poisson homogeneous (MPH) and homogeneous linear predictor (HLP)
models.  See Lang (2004) <doi:10.1214/aos/1079120140> and Lang (2005)
<doi:10.1198/016214504000001042> for MPH and HLP models.  Objects computed
include model goodness-of-fit statistics; likelihood- based (cell- and
link-specific) residuals; and cell probability and expected count estimates
along with standard errors.  This package can also compute test-inversion--e.g.
Wald, profile likelihood, score, power-divergence--confidence intervals for
contingency table estimands, when table probabilities are potentially subject to
equality constraints.  For test-inversion intervals, see Lang (2008)
<doi:10.1002/sim.3391> and Zhu (2020) <doi:10.17077/etd.005331>.")
    (license license:gpl2+)))

(define-public r-csvy
  (package
    (name "r-csvy")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csvy" version))
       (sha256
        (base32 "0id015szw1c63vd1h0515jsqdhyn32sxpxm89f3sb1qkgq3yynmy"))))
    (properties `((upstream-name . "csvy")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml r-jsonlite r-data-table))
    (home-page "https://github.com/leeper/csvy")
    (synopsis "Import and Export CSV Data with a YAML Metadata Header")
    (description
     "Support for import from and export to the CSVY file format.  CSVY is a file
format that combines the simplicity of CSV (comma-separated values) with the
metadata of other plain text and binary formats (JSON, XML, Stata, etc.) by
placing a YAML header on top of a regular CSV.")
    (license license:gpl2)))

(define-public r-csvwr
  (package
    (name "r-csvwr")
    (version "0.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csvwr" version))
       (sha256
        (base32 "1yh330kh1q06f2vn8jvgirz4q7wld1ylnkjpnjh17nqq0d2lsmk2"))))
    (properties `((upstream-name . "csvwr")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-rlang
                             r-readr
                             r-purrr
                             r-magrittr
                             r-jsonlite
                             r-cli))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://robsteranium.github.io/csvwr/")
    (synopsis "Read and Write CSV on the Web (CSVW) Tables and Metadata")
    (description
     "Provide functions for reading and writing CSVW - i.e.  CSV tables and JSON
metadata.  The metadata helps interpret CSV by setting the types and variable
names.")
    (license license:gpl3)))

(define-public r-csvread
  (package
    (name "r-csvread")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csvread" version))
       (sha256
        (base32 "0cbsdlrbdgq039cyr42isqbg8w65dpia1rdwbfppnv2x0f6x0fwr"))))
    (properties `((upstream-name . "csvread")))
    (build-system r-build-system)
    (home-page "https://github.com/jabiru/csvread")
    (synopsis "Fast Specialized CSV File Loader")
    (description
     "This package provides functions for loading large (10M+ lines) CSV and other
delimited files, similar to read.csv, but typically faster and using less memory
than the standard R loader.  While not entirely general, it covers many common
use cases when the types of columns in the CSV file are known in advance.  In
addition, the package provides a class int64', which represents 64-bit integers
exactly when reading from a file.  The latter is useful when working with 64-bit
integer identifiers exported from databases.  The CSV file loader supports
common column types including integer', double', string', and int64', leaving
further type transformations to the user.")
    (license license:asl2.0)))

(define-public r-csv
  (package
    (name "r-csv")
    (version "0.6.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csv" version))
       (sha256
        (base32 "1mynaia16jm28qi597xg7kf4w85vsxg5p83xbcbbr9di49vxqlr8"))))
    (properties `((upstream-name . "csv")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi r-data-table))
    (home-page "https://cran.r-project.org/package=csv")
    (synopsis "Read and Write CSV Files with Selected Conventions")
    (description
     "Reads and writes CSV with selected conventions.  Uses the same generic function
for reading and writing to promote consistent formats.")
    (license license:gpl3)))

(define-public r-csutil
  (package
    (name "r-csutil")
    (version "2023.4.25")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csutil" version))
       (sha256
        (base32 "0yh72ddymkqi46xqjvmgqkvn2a5bl3qyrrr37w0mvdx89zr95yxn"))))
    (properties `((upstream-name . "csutil")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-ggplot2 r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://www.csids.no/csutil/")
    (synopsis "Common Base-R Problems Relating to Lists")
    (description
     "Utility functions that help with common base-R problems relating to lists.
Lists in base-R are very flexible.  This package provides functions to quickly
and easily characterize types of lists.  That is, to identify if all elements in
a list are null, data.frames, lists, or fully named lists.  Other functionality
is provided for the handling of lists, such as the easy splitting of lists into
equally sized groups, and the unnesting of data.frames within fully named lists.")
    (license license:expat)))

(define-public r-csurvey
  (package
    (name "r-csurvey")
    (version "1.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csurvey" version))
       (sha256
        (base32 "0g41mh332imf03xwxpa3ghmi8dmdpva8wb1z794as3gp5hjddsh5"))))
    (properties `((upstream-name . "csurvey")))
    (build-system r-build-system)
    (propagated-inputs (list r-survey
                             r-purrr
                             r-matrix
                             r-mass
                             r-igraph
                             r-coneproj
                             r-cgam))
    (home-page "https://cran.r-project.org/package=csurvey")
    (synopsis "Constrained Regression for Survey Data")
    (description
     "Domain mean estimation with monotonicity or block monotone constraints.  See Xu
X, Meyer MC and Opsomer JD (2021)<doi:10.1016/j.jspi.2021.02.004> for more
details.")
    (license license:gpl2+)))

(define-public r-cstools
  (package
    (name "r-cstools")
    (version "5.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CSTools" version))
       (sha256
        (base32 "0yyzc76x45pf3r84jdpxj2zplibf6zb1q3gb8jv5ncpcw3s9i3c9"))))
    (properties `((upstream-name . "CSTools")))
    (build-system r-build-system)
    (propagated-inputs (list r-verification
                             r-startr
                             r-scales
                             r-s2dv
                             r-reshape2
                             r-rcolorbrewer
                             r-rainfarmr
                             r-qmap
                             r-plyr
                             r-ncdf4
                             r-multiapply
                             r-maps
                             r-lubridate
                             r-ggplot2
                             r-easyverification
                             r-easyncdf
                             r-data-table
                             r-climprojdiags
                             r-abind))
    (native-inputs (list r-knitr gfortran))
    (home-page "https://cran.r-project.org/package=CSTools")
    (synopsis
     "Assessing Skill of Climate Forecasts on Seasonal-to-Decadal Timescales")
    (description
     "Exploits dynamical seasonal forecasts in order to provide information relevant
to stakeholders at the seasonal timescale.  The package contains process-based
methods for forecast calibration, bias correction, statistical and stochastic
downscaling, optimal forecast combination and multivariate verification, as well
as basic and advanced tools to obtain tailored products.  This package was
developed in the context of the ERA4CS project MEDSCOPE and the H2020 S2S4E
project and includes contributions from @code{ArticXchange} project founded by
EU-@code{PolarNet} 2'.  PÃ©rez-ZanÃ³n et al. (2022)
<doi:10.5194/gmd-15-6115-2022>'.  Doblas-Reyes et al. (2005)
<doi:10.1111/j.1600-0870.2005.00104.x>'.  Mishra et al. (2018)
<doi:10.1007/s00382-018-4404-z>'.  Sanchez-Garcia et al. (2019)
<doi:10.5194/asr-16-165-2019>'.  Straus et al. (2007) <doi:10.1175/JCLI4070.1>'.
 Terzago et al. (2018) <doi:10.5194/nhess-18-2825-2018>'.  Torralba et al.
(2017) <doi:10.1175/JAMC-D-16-0204.1>'.  D'Onofrio et al. (2014)
<doi:10.1175/JHM-D-13-096.1>'.  Verfaillie et al. (2017)
<doi:10.5194/gmd-10-4257-2017>'.  Van Schaeybroeck et al. (2019)
<doi:10.1016/B978-0-12-812372-0.00010-8>'.  Yiou et al. (2013)
<doi:10.1007/s00382-012-1626-3>'.")
    (license license:gpl3)))

(define-public r-cstime
  (package
    (name "r-cstime")
    (version "2023.5.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cstime" version))
       (sha256
        (base32 "0x6nilc1971fjb5s7im6jp3az13r7rd5z3pc0y7kglggp33aqw6i"))))
    (properties `((upstream-name . "cstime")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://www.csids.no/cstime/")
    (synopsis "Date and Time Functions for Public Health Purposes")
    (description
     "This package provides easy and consistent time conversion for public health
purposes.  The time conversion functions provided here are between date, ISO
week, ISO yearweek, ISO year, calendar month/year, season, season week.")
    (license license:expat)))

(define-public r-cstidy
  (package
    (name "r-cstidy")
    (version "2023.5.24")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cstidy" version))
       (sha256
        (base32 "01i5b1x6xfg8fbkhaam22ap64x6bqman5b5y57f07wiy413m65j2"))))
    (properties `((upstream-name . "cstidy")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-magrittr
                             r-ggplot2
                             r-digest
                             r-data-table
                             r-cstime
                             r-csdata
                             r-crayon))
    (native-inputs (list r-knitr))
    (home-page "https://www.csids.no/cstidy/")
    (synopsis "Helpful Functions for Cleaning Surveillance Data")
    (description
     "Helpful functions for the cleaning and manipulation of surveillance data,
especially with regards to the creation and validation of panel data from
individual level surveillance data.")
    (license license:expat)))

(define-public r-cstab
  (package
    (name "r-cstab")
    (version "0.2-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cstab" version))
       (sha256
        (base32 "1lr401fvi88f4jv8jh4brx95ymncfw8clripz1r6a46inj80nj4j"))))
    (properties `((upstream-name . "cstab")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-fastcluster r-cluster))
    (home-page "https://cran.r-project.org/package=cstab")
    (synopsis
     "Selection of Number of Clusters via Normalized Clustering Instability")
    (description
     "Selection of the number of clusters in cluster analysis using stability methods.")
    (license license:gpl2+)))

(define-public r-csstools
  (package
    (name "r-csstools")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cssTools" version))
       (sha256
        (base32 "1p8c21c1hilmd9ibqyz493fy1x95hb2pidybsyicch53gkb542br"))))
    (properties `((upstream-name . "cssTools")))
    (build-system r-build-system)
    (propagated-inputs (list r-sna))
    (home-page "https://cran.r-project.org/package=cssTools")
    (synopsis "Cognitive Social Structure Tools")
    (description
     "This package provides a collection of tools for estimating a network from a
random sample of cognitive social structure (CSS) slices.  Also contains
functions for evaluating a CSS in terms of various error types observed in each
slice.")
    (license license:gpl2+)))

(define-public r-csranks
  (package
    (name "r-csranks")
    (version "1.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csranks" version))
       (sha256
        (base32 "0banz6a5w083jm072lzygrha6l7s419qp9g79ab3fr7k0xvzbm72"))))
    (properties `((upstream-name . "csranks")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales r-mass r-lifecycle r-ggplot2 r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/danielwilhelm/R-CS-ranks")
    (synopsis "Statistical Tools for Ranks")
    (description
     "Account for uncertainty when working with ranks.  Estimate standard errors
consistently in linear regression with ranked variables.  Construct confidence
sets of various kinds for positions of populations in a ranking based on values
of a certain feature and their estimation errors.  Theory based on Mogstad,
Romano, Shaikh, and Wilhelm (2023)<doi:10.1093/restud/rdad006> and Chetverikov
and Wilhelm (2023) <doi:10.48550/@code{arXiv.2310.15512>}.")
    (license license:gpl3+)))

(define-public r-csquares
  (package
    (name "r-csquares")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csquares" version))
       (sha256
        (base32 "0x748vc146ynf2hkpb701nqnya1lkzsyplfz13v7pfn0zaw7639j"))))
    (properties `((upstream-name . "csquares")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-tidyselect
                             r-tidyr
                             r-stringr
                             r-stars
                             r-sf
                             r-rlang
                             r-purrr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://pepijn-devries.github.io/csquares/")
    (synopsis "Concise Spatial Query and Representation System (c-Squares)")
    (description
     "Encode and decode c-squares, from and to simple feature (sf) or spatiotemporal
arrays (stars) objects.  Use c-squares codes to quickly join or query spatial
data.")
    (license license:gpl3+)))

(define-public r-csppdata
  (package
    (name "r-csppdata")
    (version "0.2.61")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csppData" version))
       (sha256
        (base32 "1q9a11v512dc96lrrd03w06s8x6c1a0j4z5x8qvq48f4q7k30l1r"))))
    (properties `((upstream-name . "csppData")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=csppData")
    (synopsis "Data Only: The Correlates of State Policy Project Dataset")
    (description
     "This package contains the Correlates of State Policy Project dataset (+
codebook) assembled by Marty P. Jordan and Matt Grossmann (2020)
<http://ippsr.msu.edu/public-policy/correlates-state-policy> used by the cspp
package.  The Correlates data contains over 3000 variables across more than 100
years that pertain to state politics and policy in the United States.")
    (license license:gpl3)))

(define-public r-cspp
  (package
    (name "r-cspp")
    (version "0.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cspp" version))
       (sha256
        (base32 "1x3swcgqffqcpw4w6dwafqh9cikd6c714lbbnzwirvqvfswnmmgw"))))
    (properties `((upstream-name . "cspp")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-stringr
                             r-rlang
                             r-readr
                             r-purrr
                             r-mapproj
                             r-haven
                             r-ggplot2
                             r-ggcorrplot
                             r-dplyr
                             r-csppdata))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cspp")
    (synopsis "Tool for the Correlates of State Policy Project Data")
    (description
     "This package provides a tool that imports, subsets, visualizes, and exports the
Correlates of State Policy Project dataset assembled by Marty P. Jordan and Matt
Grossmann (2020) <http://ippsr.msu.edu/public-policy/correlates-state-policy>.
The Correlates data contains over 2000 variables across more than 100 years that
pertain to state politics and policy in the United States.  Users with only a
basic understanding of R can subset this data across multiple dimensions, export
their search results, create map visualizations, export the citations associated
with their searches, and more.")
    (license license:gpl3+)))

(define-public r-cspec
  (package
    (name "r-cspec")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cspec" version))
       (sha256
        (base32 "049vynbffxyd5zwxwyz1jv05zgq7zrx1ypzv5j62ph64gl42m13p"))))
    (properties `((upstream-name . "cspec")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cspec")
    (synopsis "Complete Discrete Fourier Transform (DFT) and Periodogram")
    (description
     "Calculate the predictive discrete Fourier transform, complete discrete Fourier
transform, complete periodogram, and tapered complete periodogram.  This
algorithm is based on the preprint \"Spectral methods for small sample time
series: A complete periodogram approach\" (2020) by Sourav Das, Suhasini Subba
Rao, and Junho Yang.")
    (license license:gpl2)))

(define-public r-csodata
  (package
    (name "r-csodata")
    (version "1.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csodata" version))
       (sha256
        (base32 "11sgkf6xy3wh73yqhcjcpif9w73026rmiwm5vcgm21fg9fl4hyfk"))))
    (properties `((upstream-name . "csodata")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-sf
                             r-rjstat
                             r-reshape2
                             r-r-cache
                             r-lubridate
                             r-lifecycle
                             r-jsonlite
                             r-httr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/CSOIreland/csodata")
    (synopsis "Download Data from the CSO 'PxStat' API")
    (description
     "Imports @code{PxStat} data in JSON-stat format and (optionally) reshapes it into
wide format.  The Central Statistics Office (CSO) is the national statistical
institute of Ireland and @code{PxStat} is the CSOs online database of Official
Statistics.  This database contains current and historical data series compiled
from CSO statistical releases and is accessed at <http://data.cso.ie>.  The CSO
@code{PxStat} Application Programming Interface (API), which is accessed in this
package, provides access to @code{PxStat} data in JSON-stat format at
<http://data.cso.ie>.  This dissemination tool allows developers machine to
machine access to CSO @code{PxStat} data.")
    (license license:gpl3)))

(define-public r-csn
  (package
    (name "r-csn")
    (version "1.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csn" version))
       (sha256
        (base32 "102w1qh9hgz4j9lh5hnbw1z3b7p034si73q4pkk564a2mhzlksw4"))))
    (properties `((upstream-name . "csn")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm))
    (home-page "https://cran.r-project.org/package=csn")
    (synopsis "Closed Skew-Normal Distribution")
    (description
     "This package provides functions for computing the density and the log-likelihood
function of closed-skew normal variates, and for generating random vectors
sampled from this distribution.  See Gonzalez-Farias, G., Dominguez-Molina, J.,
and Gupta, A. (2004).  The closed skew normal distribution, Skew-elliptical
distributions and their applications: a journey beyond normality, Chapman and
Hall/CRC, Boca Raton, FL, pp.  25-42.")
    (license license:gpl2)))

(define-public r-csmpv
  (package
    (name "r-csmpv")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csmpv" version))
       (sha256
        (base32 "13b7i4ri0a3cjnhn14m72rff4gxxda556h38gjwp900mnjaqrwbj"))))
    (properties `((upstream-name . "csmpv")))
    (build-system r-build-system)
    (propagated-inputs (list r-xgboost
                             r-survminer
                             r-survival
                             r-scales
                             r-rms
                             r-matrix
                             r-hmisc
                             r-glmnet
                             r-ggpubr
                             r-ggplot2
                             r-forestmodel))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=csmpv")
    (synopsis
     "Biomarker Confirmation, Selection, Modelling, Prediction, and Validation")
    (description
     "There are diverse purposes such as biomarker confirmation, novel biomarker
discovery, constructing predictive models, model-based prediction, and
validation.  It handles binary, continuous, and time-to-event outcomes at the
sample or patient level. - Biomarker confirmation utilizes established functions
like glm() from stats', coxph() from survival', surv_fit(), and ggsurvplot()
from survminer'. - Biomarker discovery and variable selection are facilitated by
three LASSO-related functions LASSO2(), LASSO_plus(), and LASSO2plus(),
leveraging the glmnet R package with additional steps. - Eight versatile
modeling functions are offered, each designed for predictive models across
various outcomes and data types.  1) LASSO2(), LASSO_plus(), LASSO2plus(), and
LASSO2_reg() perform variable selection using LASSO methods and construct
predictive models based on selected variables.  2) XGBtraining() employs XGBoost
for model building and is the only function not involving variable selection.
3) Functions like LASSO2_XGBtraining(), LASSOplus_XGBtraining(), and
LASSO2plus_XGBtraining() combine LASSO-related variable selection with XGBoost
for model construction. - All models support prediction and validation,
requiring a testing dataset comparable to the training dataset.  Additionally,
the package introduces XGpred() for risk prediction based on survival data, with
the XGpred_predict() function available for predicting risk groups in new
datasets.  The methodology is based on our new algorithms and various
references: - Hastie et al. (1992, ISBN 0 534 16765-9), - Therneau et al. (2000,
ISBN 0-387-98784-3), - Kassambara et al. (2021)
<https://CRAN.R-project.org/package=survminer>, - Friedman et al. (2010)
<doi:10.18637/jss.v033.i01>, - Simon et al. (2011) <doi:10.18637/jss.v039.i05>,
- Harrell (2023) <https://CRAN.R-project.org/package=rms>, - Harrell (2023)
<https://CRAN.R-project.org/package=Hmisc>, - Chen and Guestrin (2016)
<@code{arXiv:1603.02754>}, - Aoki et al. (2023) <doi:10.1200/JCO.23.01115>.")
    (license license:expat)))

(define-public r-csmes
  (package
    (name "r-csmes")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CSMES" version))
       (sha256
        (base32 "1p8wsl9h1f44a7kkj660h1k1v26pp6q1h13rw9l6pikniwdks84c"))))
    (properties `((upstream-name . "CSMES")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-rpart
                             r-rocr
                             r-mco
                             r-data-table
                             r-catools))
    (home-page "https://cran.r-project.org/package=CSMES")
    (synopsis
     "Cost-Sensitive Multi-Criteria Ensemble Selection for Uncertain Cost Conditions")
    (description
     "This package provides functions for cost-sensitive multi-criteria ensemble
selection (CSMES) (as described in De bock et al. (2020)
<doi:10.1016/j.ejor.2020.01.052>) for cost-sensitive learning under unknown cost
conditions.")
    (license license:gpl2+)))

(define-public r-csmaps
  (package
    (name "r-csmaps")
    (version "2023.5.22")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csmaps" version))
       (sha256
        (base32 "02w3g6qc928fbic462nn22s6fcqxr4v9hhhrv632azcc2x83k100"))))
    (properties `((upstream-name . "csmaps")))
    (build-system r-build-system)
    (propagated-inputs (list r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://www.csids.no/csmaps/")
    (synopsis "Preformatted Maps of Norway that Don't Need Geolibraries")
    (description
     "This package provides datasets containing preformatted maps of Norway at the
county, municipality, and ward (Oslo only) level for redistricting in 2024,
2020, 2018, and 2017.  Multiple layouts are provided (normal, split, and with an
insert for Oslo), allowing the user to rapidly create choropleth maps of Norway
without any geolibraries.")
    (license license:expat)))

(define-public r-csindicators
  (package
    (name "r-csindicators")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CSIndicators" version))
       (sha256
        (base32 "062v23vm2yz0dr2s0d6p7iwccdkgywn8k9gfp4jc8kr56ff3hvvr"))))
    (properties `((upstream-name . "CSIndicators")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-spei
                             r-s2dv
                             r-multiapply
                             r-lmomco
                             r-lmom
                             r-cstools
                             r-climprojdiags))
    (native-inputs (list r-knitr))
    (home-page "https://earth.bsc.es/gitlab/es/csindicators/")
    (synopsis
     "Climate Services' Indicators Based on Sub-Seasonal to Decadal Predictions")
    (description
     "Set of generalised tools for the flexible computation of climate related
indicators defined by the user.  Each method represents a specific mathematical
approach which is combined with the possibility to select an arbitrary time
period to define the indicator.  This enables a wide range of possibilities to
tailor the most suitable indicator for each particular climate service
application (agriculture, food security, energy, water management, ...).  This
package is intended for sub-seasonal, seasonal and decadal climate predictions,
but its methods are also applicable to other time-scales, provided the
dimensional structure of the input is maintained.  Additionally, the outputs of
the functions in this package are compatible with CSTools'.  This package is
described in PÃ©rez-ZanÃ³n et al. (2023) <doi:10.1016/j.cliser.2023.100393> and
it was developed in the context of H2020 MED-GOLD (776467) and S2S4E (776787)
projects.  See LledÃ³ et al. (2019) <doi:10.1016/j.renene.2019.04.135> and Chou
et al., 2023 <doi:10.1016/j.cliser.2023.100345> for details.")
    (license license:gpl3)))

(define-public r-cshshydrology
  (package
    (name "r-cshshydrology")
    (version "1.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CSHShydRology" version))
       (sha256
        (base32 "0f90k32ngfkb7cp9s79h50qmxxxggkkm8a72diz9981wz6n3zjaa"))))
    (properties `((upstream-name . "CSHShydRology")))
    (build-system r-build-system)
    (propagated-inputs (list r-whitebox
                             r-timedate
                             r-tidyhydat
                             r-stringr
                             r-sf
                             r-raster
                             r-plotrix
                             r-magrittr
                             r-lubridate
                             r-kendall
                             r-httr
                             r-ggspatial
                             r-ggplot2
                             r-fields
                             r-dplyr
                             r-circular))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/CSHS-hydRology/CSHShydRology")
    (synopsis "Canadian Hydrological Analyses")
    (description
     "This package provides a collection of user-submitted functions to aid in the
analysis of hydrological data, particularly for users in Canada.  The functions
focus on the use of Canadian data sets, and are suited to Canadian hydrology,
such as the important cold region hydrological processes and will work with
Canadian hydrological models.  The functions are grouped into several themes,
currently including Statistical hydrology, Basic data manipulations,
Visualization, and Spatial hydrology.  Functions developed by the Floodnet
project are also included.  CSH@code{ShydRology} has been developed with the
assistance of the Canadian Society for Hydrological Sciences (CSHS) which is an
affiliated society of the Canadian Water Resources Association (CWRA).  As of
version 1.2.6, functions now fail gracefully when attempting to download data
from a url which is unavailable.")
    (license license:agpl3)))

(define-public r-cshapes
  (package
    (name "r-cshapes")
    (version "2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cshapes" version))
       (sha256
        (base32 "0c3q85whvp28zlm4k1570kwc5qvl2fmaszx9dpmfcdqv6m19f9ks"))))
    (properties `((upstream-name . "cshapes")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp r-sf r-rmapshaper))
    (home-page "https://cran.r-project.org/package=cshapes")
    (synopsis "The CShapes 2.0 Dataset and Utilities")
    (description
     "Package for CShapes 2.0, a GIS dataset of country borders (1886-today).
Includes functions for data extraction and the computation of distance matrices
and -lists.")
    (license license:gpl2+)))

(define-public r-csgo
  (package
    (name "r-csgo")
    (version "0.6.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CSGo" version))
       (sha256
        (base32 "19awbblkx0g58gvd43xs1dmcsn588k185njw3fri8xxbn26xp5jy"))))
    (properties `((upstream-name . "CSGo")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-purrr
                             r-magrittr
                             r-jsonlite
                             r-httr
                             r-ggplot2
                             r-fuzzyjoin
                             r-future
                             r-furrr
                             r-extrafont
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/adsoncostanzifilho/CSGo")
    (synopsis "Collecting Counter Strike Global Offensive Data")
    (description
     "An implementation of calls designed to collect and organize in an easy way the
data from the Steam API specifically for the Counter-Strike Global Offensive
Game (CS Go) <https://developer.valvesoftware.com/wiki/Steam_Web_API>.")
    (license license:expat)))

(define-public r-csesa
  (package
    (name "r-csesa")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CSESA" version))
       (sha256
        (base32 "0pv6iabq1w22qbhlsbckdvva4n7igpzrjnrahmq83a6wxgvjbf5j"))))
    (properties `((upstream-name . "CSESA")))
    (build-system r-build-system)
    (propagated-inputs (list r-biostrings))
    (home-page "https://cran.r-project.org/package=CSESA")
    (synopsis "CRISPR-Based Salmonella Enterica Serotype Analyzer")
    (description
     "Salmonella enterica is a major cause of bacterial food-borne disease worldwide.
Serotype identification is the most commonly used typing method to characterize
Salmonella isolates.  However, experimental serotyping needs great cost on
manpower and resources.  Recently, we found that the newly incorporated spacer
in the clustered regularly interspaced short palindromic repeat (CRISPR) could
serve as an effective marker for typing of Salmonella.  It was further revealed
by Li et.  al (2014) <doi:10.1128/JCM.00696-14> that recognized types based on
the combination of two newly incorporated spacer in both CRISPR loci showed high
accordance with serotypes.  Here, we developed an R package CSESA to predict the
serotype based on this finding.  Considering itâs time saving and of high
accuracy, we recommend to predict the serotypes of unknown Salmonella isolates
using CSESA before doing the traditional serotyping.")
    (license license:gpl2+)))

(define-public r-cseqpat
  (package
    (name "r-cseqpat")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CSeqpat" version))
       (sha256
        (base32 "1nqk873cagpn4fba4rmyzb6hni1p5lqcvsr9givrcm0gfx756w1h"))))
    (properties `((upstream-name . "CSeqpat")))
    (build-system r-build-system)
    (propagated-inputs (list r-tm r-nlp))
    (home-page "https://cran.r-project.org/package=CSeqpat")
    (synopsis "Frequent Contiguous Sequential Pattern Mining of Text")
    (description "Mines contiguous sequential patterns in text.")
    (license license:expat)))

(define-public r-csem
  (package
    (name "r-csem")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cSEM" version))
       (sha256
        (base32 "0a0pv01ynlac53rdwjhw20alx72ip23izvcxv8bdkdxa41ai3bi5"))))
    (properties `((upstream-name . "cSEM")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncatednormal
                             r-symmoments
                             r-rlang
                             r-rdpack
                             r-purrr
                             r-psych
                             r-progressr
                             r-polycor
                             r-matrixstats
                             r-matrixcalc
                             r-matrix
                             r-mass
                             r-magrittr
                             r-lifecycle
                             r-lavaan
                             r-future-apply
                             r-future
                             r-expm
                             r-crayon
                             r-cli
                             r-alabama))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/M-E-Rademaker/cSEM/")
    (synopsis "Composite-Based Structural Equation Modeling")
    (description
     "Estimate, assess, test, and study linear, nonlinear, hierarchical and multigroup
structural equation models using composite-based approaches and procedures,
including estimation techniques such as partial least squares path modeling
(PLS-PM) and its derivatives (PLSc, @code{ordPLSc}, @code{robustPLSc}),
generalized structured component analysis (GSCA), generalized structured
component analysis with uniqueness terms (GSCAm), generalized canonical
correlation analysis (GCCA), principal component analysis (PCA), factor score
regression (FSR) using sum score, regression or bartlett scores (including bias
correction using Croonâs approach), as well as several tests and typical
postestimation procedures (e.g., verify admissibility of the estimates, assess
the model fit, test the model fit etc.).")
    (license license:gpl3)))

(define-public r-csdata
  (package
    (name "r-csdata")
    (version "2024.4.26")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csdata" version))
       (sha256
        (base32 "03yi9hnsr8nl4kg9q2dpmngym4xv3kscc6kri71hv3wzk60y811r"))))
    (properties `((upstream-name . "csdata")))
    (build-system r-build-system)
    (propagated-inputs (list r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://www.csids.no/csdata/")
    (synopsis "Structural Data for Norway")
    (description
     "Datasets relating to population in municipalities, municipality/county matching,
and how different municipalities have merged/redistricted over time from 2006 to
2024.")
    (license license:expat)))

(define-public r-cscnet
  (package
    (name "r-cscnet")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CSCNet" version))
       (sha256
        (base32 "0amsrjzpfga66mh6x589whz70xpl0sg10f80x87apxz312rb4r8m"))))
    (properties `((upstream-name . "CSCNet")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyverse
                             r-tibble
                             r-survival
                             r-stringr
                             r-riskregression
                             r-recipes
                             r-purrr
                             r-prodlim
                             r-magrittr
                             r-glmnet
                             r-future
                             r-furrr
                             r-dplyr
                             r-caret))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CSCNet")
    (synopsis
     "Fitting and Tuning Regularized Cause-Specific Cox Models with Elastic-Net Penalty")
    (description
     "Flexible tools to fit, tune and obtain absolute risk predictions from
regularized cause-specific cox models with elastic-net penalty.")
    (license license:gpl3+)))

(define-public r-csclone
  (package
    (name "r-csclone")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CSclone" version))
       (sha256
        (base32 "0lqsqsgh2sf44fr1r7g179556v294yr1wy7x4320g7adxshrwyh5"))))
    (properties `((upstream-name . "CSclone")))
    (build-system r-build-system)
    (propagated-inputs (list r-moments r-mcclust r-lpsolve r-dnacopy))
    (home-page "https://cran.r-project.org/package=CSclone")
    (synopsis "Bayesian Nonparametric Modeling in R")
    (description
     "Germline and somatic locus data which contain the total read depth and B allele
read depth using Bayesian model (Dirichlet Process) to cluster.  Meanwhile, the
cluster model can deal with the SNVs mutation and the CNAs mutation.")
    (license license:gpl2+)))

(define-public r-csci
  (package
    (name "r-csci")
    (version "0.9.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csci" version))
       (sha256
        (base32 "00s1gx5h141w1vjw8j3k7bn71c4dy80m6wakd1c1z7rmx1jbfp6m"))))
    (properties `((upstream-name . "csci")))
    (build-system r-build-system)
    (propagated-inputs (list r-exactci))
    (home-page "https://cran.r-project.org/package=csci")
    (synopsis "Current Status Confidence Intervals")
    (description
     "Calculates pointwise confidence intervals for the cumulative distribution
function of the event time for current status data, data where each individual
is assessed at one time to see if they had the event or not by the assessment
time.")
    (license license:gpl3)))

(define-public r-cschange
  (package
    (name "r-cschange")
    (version "0.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CsChange" version))
       (sha256
        (base32 "1qggfi7g34iw0737azn4l9cn0chsiq4wa18v8i5znlaimzmifylr"))))
    (properties `((upstream-name . "CsChange")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rms r-hmisc r-boot))
    (home-page "https://cran.r-project.org/package=CsChange")
    (synopsis "Testing for Change in C-Statistic")
    (description
     "Calculate the confidence interval and p value for change in C-statistic.  The
adjusted C-statistic is calculated by using formula as \"Somers Dxy rank
correlation\"/2+0.5.  The confidence interval was calculated by using the
bootstrap method.  The p value was calculated by using the Z testing method.
Please refer to the article of Peter Ganz et al. (2016)
<doi:10.1001/jama.2016.5951>.")
    (license license:gpl3)))

(define-public r-csampling
  (package
    (name "r-csampling")
    (version "1.2-2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csampling" version))
       (sha256
        (base32 "0kqx7j96yafsqi9cz551fqpwkbcabxl8zpwa2jms862z41xbgsv3"))))
    (properties `((upstream-name . "csampling")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-statmod r-marg))
    (home-page "https://www.r-project.org")
    (synopsis
     "Functions for Conditional Simulation in Regression-Scale Models")
    (description
     "Monte Carlo conditional inference for the parameters of a linear nonnormal
regression model.")
    (license (list license:gpl2+
                   (license:fsdg-compatible "file LICENCE")))))

(define-public r-csalert
  (package
    (name "r-csalert")
    (version "2024.6.24")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csalert" version))
       (sha256
        (base32 "0ahafz39x8zh4yrwhjkbv2fwvz1vpckksj935k9g18ympdg4nnyz"))))
    (properties `((upstream-name . "csalert")))
    (build-system r-build-system)
    (propagated-inputs (list r-surveillance
                             r-stringr
                             r-magrittr
                             r-lubridate
                             r-glm2
                             r-ggplot2
                             r-data-table
                             r-cstime
                             r-cstidy))
    (native-inputs (list r-knitr))
    (home-page "https://www.csids.no/csalert/")
    (synopsis "Alerts from Public Health Surveillance Data")
    (description
     "Helps create alerts and determine trends by using various methods to analyze
public health surveillance data.  The primary analysis method is based upon a
published analytics strategy by Benedetti (2019) <doi:10.5588/pha.19.0002>.")
    (license license:expat)))

(define-public r-csa
  (package
    (name "r-csa")
    (version "0.7.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "csa" version))
       (sha256
        (base32 "1mjvyl1l80xxyj1nafjgl6jhclyahybi47zxcrkpb78ldiwsf1hl"))))
    (properties `((upstream-name . "csa")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales
                             r-reshape2
                             r-raster
                             r-moments
                             r-lmoments
                             r-ggpubr
                             r-ggplot2
                             r-foreach
                             r-doparallel
                             r-data-table))
    (home-page "https://github.com/imarkonis/csa")
    (synopsis
     "Cross-Scale Analysis Tool for Model-Observation Visualization and Integration")
    (description
     "Integration of Earth system data from various sources is a challenging task.
Except for their qualitative heterogeneity, different data records exist for
describing similar Earth system process at different spatio-temporal scales.
Data inter-comparison and validation are usually performed at a single spatial
or temporal scale, which could hamper the identification of potential
discrepancies in other scales.  csa package offers a simple, yet efficient,
graphical method for synthesizing and comparing observed and modelled data
across a range of spatio-temporal scales.  Instead of focusing at specific
scales, such as annual means or original grid resolution, we examine how their
statistical properties change across spatio-temporal continuum.")
    (license license:gpl2)))

(define-public r-cryst
  (package
    (name "r-cryst")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cryst" version))
       (sha256
        (base32 "04da19dy3mkngd3ma44cd8cdkb5acjy9lbhfipa9flp339j1pp57"))))
    (properties `((upstream-name . "cryst")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma r-flux))
    (home-page "https://cran.r-project.org/package=cryst")
    (synopsis "Calculate the Relative Crystallinity of Starch by XRD and FTIR")
    (description
     "This package provides functions to calculate the relative crystallinity of
starch by X-ray Diffraction (XRD) and Infrared Spectroscopy (FTIR).  Starch is
biosynthesized by plants in the form of granules semicrystalline.  For XRD, the
relative crystallinity is obtained by separating the crystalline peaks from the
amorphous scattering region.  For FTIR, the relative crystallinity is achieved
by setting of a Gaussian holocrystalline-peak in the 800-1300 cm-1 region of
FTIR spectrum of starch which is divided into amorphous region and crystalline
region.  The relative crystallinity of native starch granules varies from 14 of
45 percent.  This package was supported by FONDECYT 3150630 and CIPA
Conicyt-Regional R08C1002 is gratefully acknowledged.")
    (license license:gpl2)))

(define-public r-cryptrndtest
  (package
    (name "r-cryptrndtest")
    (version "1.2.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CryptRndTest" version))
       (sha256
        (base32 "0skk0mgnkfknlbdidfh2jca1wa8rzgd29ypwpa8kdh83l9jhdi5g"))))
    (properties `((upstream-name . "CryptRndTest")))
    (build-system r-build-system)
    (propagated-inputs (list r-tseries
                             r-sfsmisc
                             r-rmpfr
                             r-lambertw
                             r-ksamples
                             r-gmp))
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=CryptRndTest")
    (synopsis "Statistical Tests for Cryptographic Randomness")
    (description
     "This package performs cryptographic randomness tests on a sequence of random
integers or bits.  Included tests are greatest common divisor, birthday
spacings, book stack, adaptive chi-square, topological binary, and three random
walk tests (Ryabko and Monarev, 2005) <doi:10.1016/j.jspi.2004.02.010>.  Tests
except greatest common divisor and birthday spacings are not covered by standard
test suites.  In addition to the chi-square goodness-of-fit test, results of
Anderson-Darling, Kolmogorov-Smirnov, and Jarque-Bera tests are also generated
by some of the cryptographic randomness tests.")
    (license license:gpl3)))

(define-public r-cryptowatchr
  (package
    (name "r-cryptowatchr")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cryptowatchR" version))
       (sha256
        (base32 "0lf94l5klkx1j1fgaq2qjqr2y8ckm5raa3a508x72ph45v10pfyq"))))
    (properties `((upstream-name . "cryptowatchR")))
    (build-system r-build-system)
    (propagated-inputs (list r-lubridate r-jsonlite r-httr))
    (home-page "https://github.com/lorenzbr/cryptowatchR")
    (synopsis "An API Wrapper for 'Cryptowatch'")
    (description
     "An API wrapper for Cryptowatch to get prices and other information (e.g.,
volume, trades, order books, bid and ask prices, live quotes, and more) about
cryptocurrencies and crypto exchanges.  See <https://docs.cryptowat.ch/rest-api>
for a detailed documentation.")
    (license license:gpl3+)))

(define-public r-cryptoverse
  (package
    (name "r-cryptoverse")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cryptoverse" version))
       (sha256
        (base32 "169afkvinngwhrxi50a4r07lhgb6x9dxjbi3bj0gc7iyxa8cl9c5"))))
    (properties `((upstream-name . "cryptoverse")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cryptoverse")
    (synopsis "Visualization and Analytics for the Cryptoverse")
    (description
     "Providing data to quickly visualize and analyze data from several
cryptocurrencies.")
    (license license:expat)))

(define-public r-cryptotrackr
  (package
    (name "r-cryptotrackr")
    (version "1.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cryptotrackr" version))
       (sha256
        (base32 "0lgz0z0qrbqrvf4hg3dk9rm6i9fxi7pvijsf3ic1f5i6fyf9c0xz"))))
    (properties `((upstream-name . "cryptotrackr")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi r-openssl r-jsonlite r-httr r-digest))
    (home-page "https://cran.r-project.org/package=cryptotrackr")
    (synopsis "An Interface to Crypto Data Sources")
    (description
     "Allows you to connect to data sources across the crypto ecosystem.  This data
can enable a range of activity such as portfolio tracking, programmatic trading,
or industry analysis.  The package is described in French (2024)
<https://github.com/@code{TrevorFrench/cryptotrackr/wiki>}.")
    (license license:expat)))

(define-public r-cryptorng
  (package
    (name "r-cryptorng")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cryptorng" version))
       (sha256
        (base32 "0c6lxms7kcgzw1dssx0l0ld0kb8jdclq8rv8j327nf45wjsll6p3"))))
    (properties `((upstream-name . "cryptorng")))
    (build-system r-build-system)
    (home-page "https://github.com/coolbutuseless/cryptorng")
    (synopsis "Access System Cryptographic Pseudorandom Number Generators")
    (description
     "Generate random numbers from the Cryptographically Secure Pseudorandom Number
Generator (CSPRNG) provided by the underlying operating system.  System CSPRNGs
are seeded internally by the OS with entropy it gathers from the system
hardware.  The following system functions are used: arc4random_buf() on
@code{macOS} and BSD; B@code{CryptgenRandom}() on Windows; Sys_getrandom() on
Linux.")
    (license license:expat)))

(define-public r-cryptoquotes
  (package
    (name "r-cryptoquotes")
    (version "1.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cryptoQuotes" version))
       (sha256
        (base32 "0fyhnba1h3vf802rab96hch6gdkggz040yvfry9ya2i74xl972pi"))))
    (properties `((upstream-name . "cryptoQuotes")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-xts
                             r-ttr
                             r-plotly
                             r-lifecycle
                             r-jsonlite
                             r-curl
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://serkor1.github.io/cryptoQuotes/")
    (synopsis
     "Streamlined Access to Cryptocurrency OHLC-V Market Data and Sentiment Indicators")
    (description
     "This high-level API client offers a streamlined access to public cryptocurrency
market data and sentiment indicators.  It features OHLC-V (Open, High, Low,
Close, Volume) that comes with granularity ranging from seconds to months and
essential sentiment indicators to develop and backtest trading strategies, or
conduct detailed market analysis.  By interacting directly with the major
cryptocurrency exchanges this package ensures a reliable, and stable, flow of
market information, eliminating the need for complex, low-level API interactions
or webcrawlers.")
    (license license:gpl2+)))

(define-public r-cryptography
  (package
    (name "r-cryptography")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cryptography" version))
       (sha256
        (base32 "0dwnm37p95i1rmrc9qq7ryz1rk96n01ik3xif1f94vz5dlm4kxd7"))))
    (properties `((upstream-name . "cryptography")))
    (build-system r-build-system)
    (propagated-inputs (list r-desctools))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/PiarasFahey/cryptography")
    (synopsis "Encrypts and Decrypts Text Ciphers")
    (description
     "Playfair, Four-Square, Scytale, Columnar Transposition and Autokey methods.
Further explanation on methods of classical cryptography can be found at
Wikipedia; (<https://en.wikipedia.org/wiki/Classical_cipher>).")
    (license license:expat)))

(define-public r-crypto2
  (package
    (name "r-crypto2")
    (version "2.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crypto2" version))
       (sha256
        (base32 "1pszqigymlj4sdyi5hhfpdag9zarjgrf3z51q27x9fvzcn9ccgm6"))))
    (properties `((upstream-name . "crypto2")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-purrr
                             r-progress
                             r-plyr
                             r-lubridate
                             r-jsonlite
                             r-janitor
                             r-dplyr
                             r-cli
                             r-base64enc))
    (home-page "https://github.com/sstoeckl/crypto2")
    (synopsis
     "Download Crypto Currency Data from 'CoinMarketCap' without 'API'")
    (description
     "Retrieves crypto currency information and historical prices as well as
information on the exchanges they are listed on.  Historical data contains daily
open, high, low and close values for all crypto currencies.  All data is scraped
from <https://coinmarketcap.com> via their web-api'.")
    (license license:expat)))

(define-public r-cry
  (package
    (name "r-cry")
    (version "0.5.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cry" version))
       (sha256
        (base32 "0n1yyjkqj0kqs53g27chl7lhk07f7aj81jwyvaxfmfkp03xzjj0d"))))
    (properties `((upstream-name . "cry")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://jfoadi.github.io/cry/")
    (synopsis "Statistics for Structural Crystallography")
    (description
     "Reading and writing of files in the most commonly used formats of structural
crystallography.  It includes functions to work with a variety of statistics
used in this field and functions to perform basic crystallographic computing.
References: D. G. Waterman, J. Foadi, G. Evans (2011)
<doi:10.1107/S0108767311084303>.")
    (license license:gpl2)))

(define-public r-crwrm
  (package
    (name "r-crwrm")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CRWRM" version))
       (sha256
        (base32 "0w6lg5q2c0w5p9vg5qr32pycyl8d1zp0s55jlvf2xhmqx34677hd"))))
    (properties `((upstream-name . "CRWRM")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CRWRM")
    (synopsis "Changing the Reference Group without Re-Running the Model")
    (description
     "To re-calculate the coefficients and the standard deviation when changing the
reference group.")
    (license license:gpl3)))

(define-public r-crwbmetareg
  (package
    (name "r-crwbmetareg")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crwbmetareg" version))
       (sha256
        (base32 "0faksz2hp1ya4j9hlpc091b1mgwz6396fc15f4f20fixcidv1jg8"))))
    (properties `((upstream-name . "crwbmetareg")))
    (build-system r-build-system)
    (propagated-inputs (list r-sandwich r-rfast2 r-lmtest))
    (home-page "https://cran.r-project.org/package=crwbmetareg")
    (synopsis "Cluster Robust Wild Bootstrap Meta Regression")
    (description
     "In meta regression sometimes the studies have multiple effects that are
correlated.  For this reason cluster robust standard errors must be computed.
However, since the clusters are unbalanced the wild bootstrap is suggested.  See
Oczkowski E. and Doucouliagos H. (2015). \"Wine prices and quality ratings: a
meta-regression analysis\".  American Journal of Agricultural Economics, 97(1):
103--121. <doi:10.1093/ajae/aau057> and Cameron A. C., Gelbach J. B. and Miller
D. L. (2008). \"Bootstrap-based improvements for inference with clustered
errors\".  The Review of Economics and Statistics, 90(3): 414--427.
<doi:10.1162/rest.90.3.414>.")
    (license license:gpl2+)))

(define-public r-cruzplot
  (package
    (name "r-cruzplot")
    (version "1.4.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CruzPlot" version))
       (sha256
        (base32 "1x9cm4773xps2q1z8vpgb8fkdrrfcrvrz6qk2m734zz9c1v39733"))))
    (properties `((upstream-name . "CruzPlot")))
    (build-system r-build-system)
    (propagated-inputs (list r-swfscdas
                             r-stringr
                             r-shinyjs
                             r-shinydashboard
                             r-shiny
                             r-marmap
                             r-maps
                             r-mapdata
                             r-geosphere
                             r-dt
                             r-dplyr))
    (home-page "https://github.com/swfsc/CruzPlot/")
    (synopsis "Plot Shipboard DAS Data")
    (description
     "This package provides a utility program oriented to create maps, plot data, and
do basic data summaries of DAS data files.  These files are typically, but do
not have to be DAS
<https://swfsc-publications.fisheries.noaa.gov/publications/TM/SWFSC/NOAA-TM-NMFS-SWFSC-305.PDF>
data produced by the Southwest Fisheries Science Center (SWFSC) program
@code{WinCruz}'.")
    (license (license:fsdg-compatible "Apache License (== 2)"))))

(define-public r-cruts
  (package
    (name "r-cruts")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cruts" version))
       (sha256
        (base32 "1ih6h9qk4yflzars00d61smjqj7s4bfvc2ikp6vlki9f6k012xcx"))))
    (properties `((upstream-name . "cruts")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-sp r-raster r-ncdf4 r-lubridate))
    (home-page "https://cran.r-project.org/package=cruts")
    (synopsis
     "Interface to Climatic Research Unit Time-Series Version 3.21 Data")
    (description
     "This package provides functions for reading in and manipulating CRU TS3.21:
Climatic Research Unit (CRU) Time-Series (TS) Version 3.21 data.")
    (license license:gpl3)))

(define-public r-crunchy
  (package
    (name "r-crunchy")
    (version "0.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crunchy" version))
       (sha256
        (base32 "15w72kmizsxkj1wx3nqny6329m2041mxyzi4nxh8l3hfmaisb4qm"))))
    (properties `((upstream-name . "crunchy")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-rstudioapi r-miniui r-httpcache
                             r-crunch))
    (native-inputs (list r-knitr))
    (home-page "https://crunch.io/r/crunchy/")
    (synopsis "Shiny Apps on Crunch")
    (description
     "To facilitate building custom dashboards on the Crunch data platform
<https://crunch.io/>, the crunchy package provides tools for working with
shiny'.  These tools include utilities to manage authentication and
authorization automatically and custom stylesheets to help match the look and
feel of the Crunch web application.  The package also includes several gadgets
for use in RStudio'.")
    (license license:lgpl3+)))

(define-public r-crunch
  (package
    (name "r-crunch")
    (version "1.30.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crunch" version))
       (sha256
        (base32 "0wbj4w50mh0l2wmvl1wzii41n0jp6pkqawwj36k0g66wjgxq07yq"))))
    (properties `((upstream-name . "crunch")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite
                             r-httr
                             r-httpcache
                             r-curl
                             r-crayon
                             r-abind))
    (native-inputs (list r-knitr))
    (home-page "https://crunch.io/r/crunch/")
    (synopsis "Crunch.io Data Tools")
    (description
     "The Crunch.io service <https://crunch.io/> provides a cloud-based data store and
analytic engine, as well as an intuitive web interface.  Using this package,
analysts can interact with and manipulate Crunch datasets from within R.
Importantly, this allows technical researchers to collaborate naturally with
team members, managers, and clients who prefer a point-and-click interface.")
    (license license:lgpl3+)))

(define-public r-crumble
  (package
    (name "r-crumble")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crumble" version))
       (sha256
        (base32 "1yiq4fjx605802h570bk90m1160lyj8ffsvcp8js5cnp86xw4k7s"))))
    (properties `((upstream-name . "crumble")))
    (build-system r-build-system)
    (propagated-inputs (list r-torch
                             r-s7
                             r-rsymphony
                             r-purrr
                             r-progressr
                             r-origami
                             r-mlr3superlearner
                             r-matrix
                             r-lmtp
                             r-generics
                             r-data-table
                             r-coro
                             r-cli
                             r-checkmate))
    (home-page "https://cran.r-project.org/package=crumble")
    (synopsis
     "Flexible and General Mediation Analysis Using Riesz Representers")
    (description
     "This package implements a modern, unified estimation strategy for common
mediation estimands (natural effects, organic effects, interventional effects,
and recanting twins) in combination with modified treatment policies as
described in Liu, Williams, Rudolph, and DÃ­az (2024)
<doi:10.48550/@code{arXiv.2408.14620>}.  Estimation makes use of recent
advancements in Riesz-learning to estimate a set of required nuisance parameters
with deep learning.  The result is the capability to estimate mediation effects
with binary, categorical, continuous, or multivariate exposures with
high-dimensional mediators and mediator-outcome confounders using machine
learning.")
    (license license:gpl3+)))

(define-public r-crtspat
  (package
    (name "r-crtspat")
    (version "1.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CRTspat" version))
       (sha256
        (base32 "0n60i8fx28mfgmzb33jz7nngrdhx8sj5lv3jl49h0xd80x7d9csb"))))
    (properties `((upstream-name . "CRTspat")))
    (build-system r-build-system)
    (propagated-inputs (list r-tsp
                             r-tidyr
                             r-spatstat-random
                             r-spatstat-geom
                             r-sf
                             r-oor
                             r-matrix
                             r-mass
                             r-magrittr
                             r-lme4
                             r-jagsui
                             r-ggplot2
                             r-geepack
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CRTspat")
    (synopsis "Workflow for Cluster Randomised Trials with Spillover")
    (description
     "Design, workflow and statistical analysis of Cluster Randomised Trials of
(health) interventions where there may be spillover between the arms (see
<https://thomasasmith.github.io/index.html>).")
    (license license:expat)))

(define-public r-crtsize
  (package
    (name "r-crtsize")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CRTSize" version))
       (sha256
        (base32 "00shm1d32gwssf230rxjnn41rvxpli6jnx0axp69bjvfm8zqynqj"))))
    (properties `((upstream-name . "CRTSize")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CRTSize")
    (synopsis "Sample Size Estimation Functions for Cluster Randomized Trials")
    (description
     "Sample size estimation in cluster (group) randomized trials.  Contains
traditional power-based methods, empirical smoothing (Rotondi and Donner, 2009),
and updated meta-analysis techniques (Rotondi and Donner, 2012).")
    (license license:gpl2+)))

(define-public r-crtgeedr
  (package
    (name "r-crtgeedr")
    (version "2.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CRTgeeDR" version))
       (sha256
        (base32 "0sqsgs8qbc6gvzr3l2r8y83nbhz12q3jf2cjlb2xgif15r7sbnxx"))))
    (properties `((upstream-name . "CRTgeeDR")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-mass r-ggplot2))
    (home-page "https://cran.r-project.org/package=CRTgeeDR")
    (synopsis
     "Doubly Robust Inverse Probability Weighted Augmented GEE Estimator")
    (description
     "This package implements a semi-parametric GEE estimator accounting for missing
data with Inverse-probability weighting (IPW) and for imbalance in covariates
with augmentation (AUG).  The estimator IPW-AUG-GEE is Doubly robust (DR).")
    (license license:gpl2+)))

(define-public r-crtconjoint
  (package
    (name "r-crtconjoint")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CRTConjoint" version))
       (sha256
        (base32 "1lp3rxjd8pilin6kvl49vm11bjd6dzhalmwf99j3jsiiavxc6baq"))))
    (properties `((upstream-name . "CRTConjoint")))
    (build-system r-build-system)
    (propagated-inputs (list r-snow r-rcpp r-foreach r-dosnow))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/daewoongham97/CRTConjoint")
    (synopsis
     "Conditional Randomization Testing (CRT) Approach for Conjoint Analysis")
    (description
     "Computes p-value according to the CRT using the @code{HierNet} test statistic.
For more details, see Ham, Imai, Janson (2022) \"Using Machine Learning to Test
Causal Hypotheses in Conjoint Analysis\" <@code{arXiv:2201.08343>}.")
    (license license:gpl3+)))

(define-public r-crt2power
  (package
    (name "r-crt2power")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crt2power" version))
       (sha256
        (base32 "115davxwq7lxwl4qqxq28bb9q7ybhwrrmmyb6kwrl0vb848q5n7b"))))
    (properties `((upstream-name . "crt2power")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyverse
                             r-tidyr
                             r-tibble
                             r-tableone
                             r-rootsolve
                             r-mvtnorm
                             r-knitr
                             r-foreach
                             r-dplyr
                             r-devtools))
    (home-page "https://github.com/melodyaowen/crt2power")
    (synopsis
     "Designing Cluster-Randomized Trials with Two Co-Primary Outcomes")
    (description
     "This package provides methods for powering cluster-randomized trials with two
co-primary outcomes using five key design techniques.  Includes functions for
calculating required sample size and statistical power.  For more details on
methodology, see Li et al. (2020) <doi:10.1111/biom.13212>, Pocock et al. (1987)
<doi:10.2307/2531989>, Vickerstaff et al. (2019)
<doi:10.1186/s12874-019-0754-4>, and Yang et al. (2022)
<doi:10.1111/biom.13692>.")
    (license license:gpl3)))

(define-public r-crsuggest
  (package
    (name "r-crsuggest")
    (version "0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crsuggest" version))
       (sha256
        (base32 "044llamxlrva5va39yzpvsmdjqn56ij7jjll73mmjg7ka0rqc5dj"))))
    (properties `((upstream-name . "crsuggest")))
    (build-system r-build-system)
    (propagated-inputs (list r-units r-sf r-purrr r-mapview r-dplyr))
    (home-page "https://cran.r-project.org/package=crsuggest")
    (synopsis
     "Obtain Suggested Coordinate Reference System Information for Spatial Data")
    (description
     "Uses data from the EPSG Registry to look up suitable coordinate reference system
transformations for spatial datasets in R. Returns a data frame with CRS codes
that can be used for CRS transformation and mapping projects.  Please see the
EPSG Dataset Terms of Use at <https://epsg.org/terms-of-use.html> for more
information.")
    (license license:expat)))

(define-public r-crsra
  (package
    (name "r-crsra")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crsra" version))
       (sha256
        (base32 "1rkqm88zmvp9gw442cby6qpvfw4pfw65wz0gyl2h37w87c3wwvrw"))))
    (properties `((upstream-name . "crsra")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidytext
                             r-tibble
                             r-readr
                             r-rcorpora
                             r-purrr
                             r-knitr
                             r-dplyr
                             r-digest))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=crsra")
    (synopsis "Tidying and Analyzing 'Coursera' Research Export Data")
    (description
     "Tidies and performs preliminary analysis of Coursera research export data.
These export data can be downloaded by anyone who has classes on Coursera and
wants to analyze the data.  Coursera is one of the leading providers of MOOCs
and was launched in January 2012.  With over 25 million learners, Coursera is
the most popular provider in the world being followed by @code{EdX}, the MOOC
provider that was a result of a collaboration between Harvard University and
MIT, with over 10 million users.  Coursera has over 150 university partners from
29 countries and offers a total of 2000+ courses from computer science to
philosophy.  Besides, Coursera offers 180+ specialization, Coursera's credential
system, and four fully online Masters degrees.  For more information about
Coursera check Coursera's About page on <https://blog.coursera.org/about/>.")
    (license license:gpl2)))

(define-public r-crso
  (package
    (name "r-crso")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crso" version))
       (sha256
        (base32 "1r10vz8z5y52a5v5phw22fhqwv9p7g66xfsx0906bcx74dn3f2b3"))))
    (properties `((upstream-name . "crso")))
    (build-system r-build-system)
    (propagated-inputs (list r-foreach))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=crso")
    (synopsis "Cancer Rule Set Optimization ('crso')")
    (description
     "An algorithm for identifying candidate driver combinations in cancer.  CRSO is
based on a theoretical model of cancer in which a cancer rule is defined to be a
collection of two or more events (i.e., alterations) that are minimally
sufficient to cause cancer.  A cancer rule set is a set of cancer rules that
collectively are assumed to account for all of ways to cause cancer in the
population.  In CRSO every event is designated explicitly as a passenger or
driver within each patient.  Each event is associated with a patient-specific,
event-specific passenger penalty, reflecting how unlikely the event would have
happened by chance, i.e., as a passenger.  CRSO evaluates each rule set by
assigning all samples to a rule in the rule set, or to the null rule, and then
calculating the total statistical penalty from all unassigned event.  CRSO uses
a three phase procedure find the best rule set of fixed size K for a range of
Ks.  A core rule set is then identified from among the best rule sets of size K
as the rule set that best balances rule set size and statistical penalty.  Users
should consult the crso vignette for an example walk through of a full CRSO run.
 The full description, of the CRSO algorithm is presented in: Klein MI,
Cannataro V, Townsend J, Stern DF and Zhao H. \"Identifying combinations of
cancer driver in individual patients.\" @code{BioRxiv} 674234 [Preprint].  June
19, 2019. <doi:10.1101/674234>.  Please cite this article if you use crso'.")
    (license license:gpl2)))

(define-public r-crsnls
  (package
    (name "r-crsnls")
    (version "0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crsnls" version))
       (sha256
        (base32 "0rv0xrdl9ix6bhaf554gma8zf923w47f8j1dkbs8g6xjqjr1c40a"))))
    (properties `((upstream-name . "crsnls")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=crsnls")
    (synopsis
     "Nonlinear Regression Parameters Estimation by 'CRS4HC' and 'CRS4HCe'")
    (description
     "This package provides functions for nonlinear regression parameters estimation
by algorithms based on Controlled Random Search algorithm.  Both functions
(crs4hc(), crs4hce()) adapt current search strategy by four heuristics
competition.  In addition, crs4hce() improves adaptability by adaptive stopping
condition.")
    (license license:gpl2)))

(define-public r-crsmeta
  (package
    (name "r-crsmeta")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crsmeta" version))
       (sha256
        (base32 "19v0bq80cma74jjl0k42pmlpd5jfv6b0hr7j2iq0d47h50pvrd02"))))
    (properties `((upstream-name . "crsmeta")))
    (build-system r-build-system)
    (home-page "https://github.com/hypertidy/crsmeta")
    (synopsis "Extract Coordinate System Metadata")
    (description
     "Obtain coordinate system metadata from various data formats.  There are
functions to extract a CRS (coordinate reference system,
<https://en.wikipedia.org/wiki/Spatial_reference_system>) in EPSG (European
Petroleum Survey Group, <http://www.epsg.org/>), PROJ4 <https://proj.org/>, or
WKT2 (Well-Known Text 2,
<http://docs.opengeospatial.org/is/12-063r5/12-063r5.html>) forms.  This is
purely for getting simple metadata from in-memory formats, please use other
tools for out of memory data sources.")
    (license license:gpl3)))

(define-public r-crseeventstudy
  (package
    (name "r-crseeventstudy")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crseEventStudy" version))
       (sha256
        (base32 "0zqqd1d1k200kah03qvpfiyshs18s5h4j8y9mwr0fbhkfj7xags7"))))
    (properties `((upstream-name . "crseEventStudy")))
    (build-system r-build-system)
    (propagated-inputs (list r-sandwich))
    (home-page "https://github.com/skoestlmeier/crseEventStudy")
    (synopsis
     "Robust and Powerful Test of Abnormal Stock Returns in Long-Horizon Event Studies")
    (description
     "Based on Dutta et al. (2018) <doi:10.1016/j.jempfin.2018.02.004>, this package
provides their standardized test for abnormal returns in long-horizon event
studies.  The methods used improve the major weaknesses of size, power, and
robustness of long-run statistical tests described in Kothari/Warner (2007)
<doi:10.1016/B978-0-444-53265-7.50015-9>.  Abnormal returns are weighted by
their statistical precision (i.e., standard deviation), resulting in abnormal
standardized returns.  This procedure efficiently captures the
heteroskedasticity problem.  Clustering techniques following Cameron et al.
(2011) <doi:10.1198/jbes.2010.07136> are adopted for computing cross-sectional
correlation robust standard errors.  The statistical tests in this package
therefore accounts for potential biases arising from returns cross-sectional
correlation, autocorrelation, and volatility clustering without power loss.")
    (license license:bsd-3)))

(define-public r-crs
  (package
    (name "r-crs")
    (version "0.15-38")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crs" version))
       (sha256
        (base32 "1wcjqpz17rcpxqixjz5a505yzp6wjnxy4mlmbxwyrfzaganpid4x"))))
    (properties `((upstream-name . "crs")))
    (build-system r-build-system)
    (propagated-inputs (list r-quantreg r-np r-boot))
    (home-page "https://github.com/JeffreyRacine/R-Package-crs")
    (synopsis "Categorical Regression Splines")
    (description
     "Regression splines that handle a mix of continuous and categorical (discrete)
data often encountered in applied settings.  I would like to gratefully
acknowledge support from the Natural Sciences and Engineering Research Council
of Canada (NSERC, <https://www.nserc-crsng.gc.ca>), the Social Sciences and
Humanities Research Council of Canada (SSHRC, <https://www.sshrc-crsh.gc.ca>),
and the Shared Hierarchical Academic Research Computing Network (SHARCNET,
<https://www.sharcnet.ca>).  We would also like to acknowledge the contributions
of the GNU GSL authors.  In particular, we adapt the GNU GSL B-spline routine
gsl_bspline.c adding automated support for quantile knots (in addition to
uniform knots), providing missing functionality for derivatives, and for
extending the splines beyond their endpoints.")
    (license license:gpl3+)))

(define-public r-crrstep
  (package
    (name "r-crrstep")
    (version "2023.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crrstep" version))
       (sha256
        (base32 "0x4fvsvcxb529c7vp5fh6vp7l0sj1wszpqzbrk1da7kmf5454ki6"))))
    (properties `((upstream-name . "crrstep")))
    (build-system r-build-system)
    (propagated-inputs (list r-cmprsk))
    (home-page "https://cran.r-project.org/package=crrstep")
    (synopsis
     "Stepwise Covariate Selection for the Fine & Gray Competing Risks Regression Model")
    (description
     "This package performs forward and backwards stepwise regression for the
Proportional subdistribution hazards model in competing risks (Fine & Gray
1999).  Procedure uses AIC, BIC and BICcr as selection criteria.  BICcr has a
penalty of k = log(n*), where n* is the number of primary events.")
    (license license:gpl2+)))

(define-public r-crrsc
  (package
    (name "r-crrsc")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crrSC" version))
       (sha256
        (base32 "0n63k1v35wvbf565msr3fczi9hjd20bqh8b4iyvzp310d8z8b3g8"))))
    (properties `((upstream-name . "crrSC")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival))
    (home-page "https://cran.r-project.org/package=crrSC")
    (synopsis "Competing Risks Regression for Stratified and Clustered Data")
    (description
     "Extension of cmprsk to Stratified and Clustered data.  A goodness of fit test
for Fine-Gray model is also provided.  Methods are detailed in the following
articles: Zhou et al. (2011) <doi:10.1111/j.1541-0420.2010.01493.x>, Zhou et al.
(2012) <doi:10.1093/biostatistics/kxr032>, Zhou et al. (2013) <doi:
10.1002/sim.5815>.")
    (license license:gpl2)))

(define-public r-crrcbcv
  (package
    (name "r-crrcbcv")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crrcbcv" version))
       (sha256
        (base32 "1rbmhnr7n99i0277d47i62ww6896z1g20v6vr558zmx3gvrs0b6k"))))
    (properties `((upstream-name . "crrcbcv")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-pracma r-crrsc r-abind))
    (home-page "https://cran.r-project.org/package=crrcbcv")
    (synopsis
     "Bias-Corrected Variance for Competing Risks Regression with Clustered Data")
    (description
     "This package provides a user friendly function crrcbcv to compute bias-corrected
variances for competing risks regression models using proportional
subdistribution hazards with small-sample clustered data.  Four types of bias
correction are included: the MD-type bias correction by Mancl and @code{DeRouen}
(2001) <doi:10.1111/j.0006-341X.2001.00126.x>, the KC-type bias correction by
Kauermann and Carroll (2001) <doi:10.1198/016214501753382309>, the FG-type bias
correction by Fay and Graubard (2001) <doi:10.1111/j.0006-341X.2001.01198.x>,
and the MBN-type bias correction by Morel, Bokossa, and Neerchal (2003)
<doi:10.1002/bimj.200390021>.")
    (license license:expat)))

(define-public r-crqa
  (package
    (name "r-crqa")
    (version "2.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crqa" version))
       (sha256
        (base32 "117sxxil4yzqss7b8d5r7y2grpc6nzcli9mrjaarsk10k95c4bwp"))))
    (properties `((upstream-name . "crqa")))
    (build-system r-build-system)
    (propagated-inputs (list r-tserieschaos
                             r-rdist
                             r-pracma
                             r-matrix
                             r-gplots
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr gfortran))
    (home-page "https://cran.r-project.org/package=crqa")
    (synopsis
     "Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis")
    (description
     "Auto, Cross and Multi-dimensional recurrence quantification analysis.  Different
methods for computing recurrence, cross vs. multidimensional or profile iti.e.,
only looking at the diagonal recurrent points, as well as functions for
optimization and plotting are proposed.  in-depth measures of the whole
cross-recurrence plot, Please refer to Coco and others (2021)
<doi:10.32614/RJ-2021-062>, Coco and Dale (2014) <doi:10.3389/fpsyg.2014.00510>
and Wallot (2018) <doi: 10.1080/00273171.2018.1512846> for further details about
the method.")
    (license license:gpl3+)))

(define-public r-crplyr
  (package
    (name "r-crplyr")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crplyr" version))
       (sha256
        (base32 "0l0vp2h4j2i5jb9wgdaqaixi9xvhb5n35zn8mdc7hyw13hjr8wa5"))))
    (properties `((upstream-name . "crplyr")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridislite
                             r-tidyselect
                             r-tibble
                             r-stringr
                             r-scales
                             r-rlang
                             r-purrr
                             r-lifecycle
                             r-lazyeval
                             r-httptest
                             r-ggplot2
                             r-dplyr
                             r-crunch))
    (native-inputs (list r-knitr))
    (home-page "https://crunch.io/r/crplyr/")
    (synopsis "'dplyr' Interface for Crunch")
    (description
     "In order to facilitate analysis of datasets hosted on the Crunch data platform
<https://crunch.io/>, the crplyr package implements dplyr methods on top of the
Crunch backend.  The usual methods select', filter', group_by', summarize', and
collect are implemented in such a way as to perform as much computation on the
server and pull as little data locally as possible.")
    (license license:lgpl3+)))

(define-public r-crov
  (package
    (name "r-crov")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crov" version))
       (sha256
        (base32 "1vnhnw6rw8qyhahy6d67cq5m9sxr6yic21qi16vic1q5115fwx01"))))
    (properties `((upstream-name . "crov")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam r-gtools))
    (home-page "https://cran.r-project.org/package=crov")
    (synopsis
     "Constrained Regression Model for an Ordinal Response and Ordinal Predictors")
    (description
     "Fits a constrained regression model for an ordinal response with ordinal
predictors and possibly others, Espinosa and Hennig (2019)
<DOI:10.1007/s11222-018-9842-2>.  The parameter estimates associated with an
ordinal predictor are constrained to be monotonic.  If a monotonicity direction
(isotonic or antitonic) is not specified for an ordinal predictor by the user,
then one of the available methods will either establish it or drop the
monotonicity assumption.  Two monotonicity tests are also available to test the
null hypothesis of monotonicity over a set of parameters associated with an
ordinal predictor.")
    (license license:gpl2)))

(define-public r-crossword-r
  (package
    (name "r-crossword-r")
    (version "0.3.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crossword.r" version))
       (sha256
        (base32 "1s31613s4qxxspka9bhgq3rq8xraf48mwfv6phvz6v06gijh64lr"))))
    (properties `((upstream-name . "crossword.r")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-r6extended
                             r-r6
                             r-magrittr
                             r-jsonlite
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=crossword.r")
    (synopsis "Generating Crosswords from Word Lists")
    (description "Generate crosswords from a list of words.")
    (license license:expat)))

(define-public r-crosswalkr
  (package
    (name "r-crosswalkr")
    (version "0.2.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crosswalkr" version))
       (sha256
        (base32 "1rxd6vy7vdrawmg7zkydl1f2wwklnzgh9dsnxbg966xrr3l9x1n9"))))
    (properties `((upstream-name . "crosswalkr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-readxl r-readr r-labelled r-haven))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/btskinner/crosswalkr")
    (synopsis "Rename and Encode Data Frames Using External Crosswalk Files")
    (description
     "This package provides a pair of functions for renaming and encoding data frames
using external crosswalk files.  It is especially useful when constructing
master data sets from multiple smaller data sets that do not name or encode
variables consistently across files.  Based on similar commands in Stata'.")
    (license license:expat)))

(define-public r-crossvalidationcp
  (package
    (name "r-crossvalidationcp")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crossvalidationCP" version))
       (sha256
        (base32 "0cmny8sjz4ampvi1jc2h4dh3x930vnwv8png6xygs2vb6p19f2ph"))))
    (properties `((upstream-name . "crossvalidationCP")))
    (build-system r-build-system)
    (propagated-inputs (list r-wbs r-fpopw r-changepoint))
    (home-page "https://cran.r-project.org/package=crossvalidationCP")
    (synopsis "Cross-Validation for Change-Point Regression")
    (description
     "This package implements the cross-validation methodology from Pein and Shah
(2021) <@code{arXiv:2112.03220>}.  Can be customised by providing different
cross-validation criteria, estimators for the change-point locations and local
parameters, and freely chosen folds.  Pre-implemented estimators and criteria
are available.  It also includes our own implementation of the COPPS procedure
<doi:10.1214/19-AOS1814>.")
    (license license:gpl3)))

(define-public r-crossvalidate
  (package
    (name "r-crossvalidate")
    (version "2.3.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CrossValidate" version))
       (sha256
        (base32 "1q5wnw2llvlw3hbjg0zccipk3ns31m2339x1aj6m526zhvgl2wvx"))))
    (properties `((upstream-name . "CrossValidate")))
    (build-system r-build-system)
    (propagated-inputs (list r-oompabase r-modeler))
    (home-page "http://oompa.r-forge.r-project.org")
    (synopsis
     "Classes and Methods for Cross Validation of \"Class Prediction\" Algorithms")
    (description
     "Defines classes and methods to cross-validate various binary classification
algorithms used for \"class prediction\" problems.")
    (license license:asl2.0)))

(define-public r-crossval
  (package
    (name "r-crossval")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crossval" version))
       (sha256
        (base32 "0rvfglnd75aa2ib8v6ibv8ywyh8v4m98ybhgc9h7a2qhk825a2w9"))))
    (properties `((upstream-name . "crossval")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=crossval")
    (synopsis "Generic Functions for Cross Validation")
    (description
     "This package contains generic functions for performing cross validation and for
computing diagnostic errors.")
    (license license:gpl3+)))

(define-public r-crossva
  (package
    (name "r-crossva")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CrossVA" version))
       (sha256
        (base32 "16ahw8h27acvqqixmwmsyl6rbjzxbn4pfyh2ls9rq852mc7mdg9b"))))
    (properties `((upstream-name . "CrossVA")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CrossVA")
    (synopsis
     "Verbal Autopsy Data Transformation for InSilicoVA and InterVA5 Algorithms")
    (description
     "Enables transformation of Verbal Autopsy data collected with the WHO 2016
questionnaire (versions 1.4.1 & 1.5.1) or the WHO 2014 questionnaire for
automated coding of Cause of Death using the @code{InSilicoVA} (data.type =
\"WHO2016\") and @code{InterVA5} algorithms.  Previous versions of this package
supported user-supplied mappings (via the map_records function), but this
functionality has been removed.  This package is made available by WHO and the
Bloomberg Data for Health Initiative.")
    (license license:gpl3)))

(define-public r-crossurr
  (package
    (name "r-crossurr")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crossurr" version))
       (sha256
        (base32 "1g4nr9x93ykq6qy5236vydkcbjyfzdz81kwgjv7mph3m0b862rdw"))))
    (properties `((upstream-name . "crossurr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-superlearner
                             r-sis
                             r-rlang
                             r-rcal
                             r-ranger
                             r-purrr
                             r-pbapply
                             r-glue
                             r-glmnet
                             r-gbm
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=crossurr")
    (synopsis
     "Cross-Fitting for Doubly Robust Evaluation of High-Dimensional Surrogate Markers")
    (description
     "Doubly robust methods for evaluating surrogate markers as outlined in: Agniel D,
Hejblum BP, Thiebaut R & Parast L (2022). \"Doubly robust evaluation of
high-dimensional surrogate markers\", Biostatistics
<doi:10.1093/biostatistics/kxac020>.  You can use these methods to determine how
much of the overall treatment effect is explained by a (possibly
high-dimensional) set of surrogate markers.")
    (license license:expat)))

(define-public r-crosstalkr
  (package
    (name "r-crosstalkr")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crosstalkr" version))
       (sha256
        (base32 "1p4grkh6kripkpirs2hrqwv4bz61bcr6pqzj88j75311kjiphnl0"))))
    (properties `((upstream-name . "crosstalkr")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-stringdb
                             r-rlang
                             r-readr
                             r-rcpp
                             r-matrix
                             r-magrittr
                             r-iterators
                             r-igraph
                             r-ggplot2
                             r-foreach
                             r-ensembldb
                             r-dplyr
                             r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=crosstalkr")
    (synopsis
     "Analysis of Graph-Structured Data with a Focus on Protein-Protein Interaction Networks")
    (description
     "This package provides a general toolkit for drug target identification.  We
include functionality to reduce large graphs to subgraphs and prioritize nodes.
In addition to being optimized for use with generic graphs, we also provides
support to analyze protein-protein interactions networks from online
repositories.  For more details on core method, refer to Weaver et al. (2021)
<https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008755>.")
    (license license:gpl3+)))

(define-public r-crosstabs-loglinear
  (package
    (name "r-crosstabs-loglinear")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Crosstabs.Loglinear" version))
       (sha256
        (base32 "0238652k1mv396wjxm058xvhp7rss0nkmn48bvkhq6pcryna2lzb"))))
    (properties `((upstream-name . "Crosstabs.Loglinear")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=Crosstabs.Loglinear")
    (synopsis "Cross Tabulation and Loglinear Analyses of Categorical Data")
    (description
     "This package provides SPSS'- and SAS'-like output for cross tabulations of two
categorical variables (CROSSTABS) and for hierarchical loglinear analyses of two
or more categorical variables (LOGLINEAR).  The methods are described in Agresti
(2013, ISBN:978-0-470-46363-5), Ajzen & Walker (2021, ISBN:9780429330308), Field
(2018, ISBN:9781526440273), Norusis (2012, ISBN:978-0-321-74843-0), Nussbaum
(2015, ISBN:978-1-84872-603-1), Stevens (2009, ISBN:978-0-8058-5903-4),
Tabachnik & Fidell (2019, ISBN:9780134790541), and von Eye & Mun (2013,
ISBN:978-1-118-14640-8).")
    (license license:gpl2+)))

(define-public r-crosstable
  (package
    (name "r-crosstable")
    (version "0.8.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crosstable" version))
       (sha256
        (base32 "134aadk2smdy6nwk2883840h4fjwb58hdr92pbf9djj237g2sq3v"))))
    (properties `((upstream-name . "crosstable")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-purrr
                             r-officer
                             r-lifecycle
                             r-glue
                             r-forcats
                             r-flextable
                             r-dplyr
                             r-cli
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://danchaltiel.github.io/crosstable/")
    (synopsis "Crosstables for Descriptive Analyses")
    (description
     "Create descriptive tables for continuous and categorical variables.  Apply
summary statistics and counting function, with or without a grouping variable,
and create beautiful reports using rmarkdown or officer'.  You can also compute
effect sizes and statistical tests if needed.")
    (license license:gpl3)))

(define-public r-crossrun
  (package
    (name "r-crossrun")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crossrun" version))
       (sha256
        (base32 "1v2khjb77g63ls6s15z9hy81z4hyf89g58jxjl94jrkznq1c4fa4"))))
    (properties `((upstream-name . "crossrun")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmpfr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ToreWentzel-Larsen/crossrun")
    (synopsis "Joint Distribution of Number of Crossings and Longest Run")
    (description
     "Joint distribution of number of crossings and the longest run in a series of
independent Bernoulli trials.  The computations uses an iterative procedure
where computations are based on results from shorter series.  The procedure
conditions on the start value and partitions by further conditioning on the
position of the first crossing (or none).")
    (license license:gpl3)))

(define-public r-crossover
  (package
    (name "r-crossover")
    (version "0.1-22")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Crossover" version))
       (sha256
        (base32 "05fsl22h2q6l0g9hscs4f0w4d3skd9anr570ddmnqicxzdfpap5r"))))
    (properties `((upstream-name . "Crossover")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (propagated-inputs (list r-xtable
                             r-rjava
                             r-rcpparmadillo
                             r-rcpp
                             r-multcomp
                             r-matrix
                             r-mass
                             r-javagd
                             r-ggplot2
                             r-digest
                             r-crossdes
                             r-commonjavajars))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/kornl/Crossover/wiki")
    (synopsis "Analysis and Search of Crossover Designs")
    (description
     "Generate and analyse crossover designs from combinatorial or search algorithms
as well as from literature and a GUI to access them.")
    (license license:gpl2)))

(define-public r-crossnma
  (package
    (name "r-crossnma")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crossnma" version))
       (sha256
        (base32 "0ma07lvf56z1ya587lb4zv8rbhzi8crnsgvh3xsz80livx9cdvp5"))))
    (properties `((upstream-name . "crossnma")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rlang
                             r-rjags
                             r-plyr
                             r-netmeta
                             r-meta
                             r-magrittr
                             r-ggplot2
                             r-dplyr
                             r-coda))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/htx-r/crossnma")
    (synopsis
     "Cross-Design & Cross-Format Network Meta-Analysis and Regression")
    (description
     "Network meta-analysis and meta-regression (allows including up to three
covariates) for individual participant data, aggregate data, and mixtures of
both formats using the three-level hierarchical model.  Each format can come
from randomized controlled trials or non-randomized studies or mixtures of both.
 Estimates are generated in a Bayesian framework using JAGS. The implemented
models are described by Hamza et al.  2023 <DOI:10.1002/jrsm.1619>.")
    (license license:gpl2+)))

(define-public r-crossmatch
  (package
    (name "r-crossmatch")
    (version "1.4-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crossmatch" version))
       (sha256
        (base32 "104qbc8p9ip446035xilgswhqfdvrqxqh5sirp6sc2rvy6lr1xng"))))
    (properties `((upstream-name . "crossmatch")))
    (build-system r-build-system)
    (propagated-inputs (list r-nbpmatching))
    (home-page "https://cran.r-project.org/package=crossmatch")
    (synopsis "The Cross-Match Test")
    (description
     "This package performs the cross-match test that is an exact, distribution free
test of equality of 2 high dimensional multivariate distributions.  The input is
a distance matrix and the labels of the two groups to be compared, the output is
the number of cross-matches and a p-value.  See Rosenbaum (2005)
<doi:10.1111/j.1467-9868.2005.00513.x>.")
    (license license:gpl2)))

(define-public r-crossmap
  (package
    (name "r-crossmap")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crossmap" version))
       (sha256
        (base32 "079ibxhm6877nfdqf88fhg9fjdn3vbs44jprrbhxmmbbd30nma4v"))))
    (properties `((upstream-name . "crossmap")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-rlang
                             r-purrr
                             r-lifecycle
                             r-generics
                             r-dplyr
                             r-cli
                             r-backports))
    (home-page "https://crossmap.rossellhayes.com")
    (synopsis "Apply Functions to All Combinations of List Elements")
    (description
     "This package provides an extension to the purrr family of mapping functions to
apply a function to each combination of elements in a list of inputs.  Also
includes functions for automatically detecting output type in mapping functions,
finding every combination of elements of lists or rows of data frames, and
applying multiple models to multiple subsets of a dataset.")
    (license license:expat)))

(define-public r-crosslag
  (package
    (name "r-crosslag")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crosslag" version))
       (sha256
        (base32 "0kvmpl7cqgp8jlvpz42caw1mqcfkvzvpy7rkgh70isx88k4n9f6g"))))
    (properties `((upstream-name . "crosslag")))
    (build-system r-build-system)
    (propagated-inputs (list r-rms
                             r-mgcv
                             r-lavaan
                             r-ggpubr
                             r-ggplot2
                             r-gamm4))
    (home-page "https://cran.r-project.org/package=crosslag")
    (synopsis "Perform Linear or Nonlinear Cross Lag Analysis")
    (description
     "Linear or nonlinear cross-lagged panel model can be built from input data.
Users can choose the appropriate method from three methods for constructing
nonlinear cross lagged models.  These three methods include polynomial
regression, generalized additive model and generalized linear mixed model.In
addition, a function for determining linear relationships is provided.  Relevant
knowledge of cross lagged models can be learned through the paper by Fredrik
FalkenstrÃ¶m (2024) <doi:10.1016/j.cpr.2024.102435> and the paper by A
Gasparrini (2010) <doi:10.1002/sim.3940>.")
    (license license:expat)))

(define-public r-crosshap
  (package
    (name "r-crosshap")
    (version "1.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crosshap" version))
       (sha256
        (base32 "1pr9kjad54427y8wljaghqbgin353llyfdwq278c8agqdzziwia0"))))
    (properties `((upstream-name . "crosshap")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-scales
                             r-rlang
                             r-patchwork
                             r-magrittr
                             r-gtable
                             r-gridextra
                             r-ggpp
                             r-ggplot2
                             r-ggdist
                             r-dplyr
                             r-dbscan
                             r-data-table
                             r-clustree
                             r-cli))
    (home-page "https://jacobimarsh.github.io/crosshap/")
    (synopsis "Local Haplotype Clustering and Visualization")
    (description
     "This package provides a local haplotyping visualization toolbox to capture major
patterns of co-inheritance between clusters of linked variants, whilst
connecting findings to phenotypic and demographic traits across individuals.
crosshap enables users to explore and understand genomic variation across a
trait-associated region.  For an example of successful local haplotype analysis,
see Marsh et al. (2022) <doi:10.1007/s00122-022-04045-8>.")
    (license license:expat)))

(define-public r-crossdes
  (package
    (name "r-crossdes")
    (version "1.1-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crossdes" version))
       (sha256
        (base32 "0nc9jd83mm03qpd3r3hfmrf615yvvmib9kk9dh1hgz12pxhffray"))))
    (properties `((upstream-name . "crossdes")))
    (build-system r-build-system)
    (propagated-inputs (list r-gtools r-algdesign))
    (home-page "https://cran.r-project.org/package=crossdes")
    (synopsis "Construction of Crossover Designs")
    (description
     "This package contains functions for the construction of carryover balanced
crossover designs.  In addition contains functions to check given designs for
balance.")
    (license license:gpl2)))

(define-public r-crossclustering
  (package
    (name "r-crossclustering")
    (version "4.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CrossClustering" version))
       (sha256
        (base32 "0by2kwykbm5il3smfi52vzzy18niqjgjflbza66dm5rlbny9dgpb"))))
    (properties `((upstream-name . "CrossClustering")))
    (build-system r-build-system)
    (propagated-inputs (list r-purrr
                             r-mclust
                             r-flip
                             r-dplyr
                             r-crayon
                             r-cluster
                             r-cli
                             r-checkmate))
    (home-page "https://CRAN.R-project.org/package=CrossClustering")
    (synopsis "Partial Clustering Algorithm")
    (description
     "Provide the @code{CrossClustering} algorithm (Tellaroli et al. (2016)
<doi:10.1371/journal.pone.0152333>), which is a partial clustering algorithm
that combines the Ward's minimum variance and Complete Linkage algorithms,
providing automatic estimation of a suitable number of clusters and
identification of outlier elements.")
    (license license:gpl3)))

(define-public r-crosscarry
  (package
    (name "r-crosscarry")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CrossCarry" version))
       (sha256
        (base32 "1nls5knpjfdbzwg8mapkinmmpafs4lpk6x0fayh16f6g5yvk2dr8"))))
    (properties `((upstream-name . "CrossCarry")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-ggplot2 r-gee r-dplyr))
    (home-page "https://cran.r-project.org/package=CrossCarry")
    (synopsis "Analysis of Data from a Crossover Design with GEE")
    (description
     "Analyze data from a crossover design using generalized estimation equations
(GEE), including carryover effects and various correlation structures based on
the Kronecker product.  It contains functions for semiparametric estimates of
carry-over effects in repeated measures and allows estimation of complex
carry-over effects.  Related work includes: a) Cruz N.A., Melo O.O., Martinez
C.A. (2023). \"@code{CrossCarry}: An R package for the analysis of data from a
crossover design with GEE\". <doi:10.48550/@code{arXiv.2304.02440>}.  b) Cruz
N.A., Melo O.O., Martinez C.A. (2023). \"A correlation structure for the analysis
of Gaussian and non-Gaussian responses in crossover experimental designs with
repeated measures\". <doi:10.1007/s00362-022-01391-z> and c) Cruz N.A., Melo
O.O., Martinez C.A. (2023). \"Semiparametric generalized estimating equations for
repeated measurements in cross-over designs\". <doi:10.1177/09622802231158736>.")
    (license license:gpl3+)))

(define-public r-cropzoning
  (package
    (name "r-cropzoning")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cropZoning" version))
       (sha256
        (base32 "0i9pglcfcrhw8i1731hhrc2v130dq7kr8w57yg9fmwdr46arnk24"))))
    (properties `((upstream-name . "cropZoning")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-terra r-sf r-ncdf4 r-ggplot2))
    (home-page "https://cran.r-project.org/package=cropZoning")
    (synopsis "Climate Crop Zoning Based in Air Temperature for Brazil")
    (description
     "Climate crop zoning based in minimum and maximum air temperature.  The data used
in the package are from @code{TerraClimate} dataset
(<https://www.climatologylab.org/terraclimate.html>), but, it have been
calibrated with automatic weather stations of National Meteorological Institute
of Brazil.  The climate crop zoning of this package can be run for all the
Brazilian territory.")
    (license (license:fsdg-compatible "CC BY 4.0"))))

(define-public r-cropwaterbalance
  (package
    (name "r-cropwaterbalance")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CropWaterBalance" version))
       (sha256
        (base32 "0hfy1y26v2cy1pi014zxrmp91ypnlb4jk1sa4zb0mhlmlxjmdijh"))))
    (properties `((upstream-name . "CropWaterBalance")))
    (build-system r-build-system)
    (propagated-inputs (list r-powersdi r-lubridate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/gabrielblain/CropWaterBalance")
    (synopsis "Climate Water Balance for Irrigation Purposes")
    (description
     "Calculates daily climate water balance for irrigation purposes and also
calculates the reference evapotranspiration (ET) using three methods, Penman and
Monteith (Allen et al.  1998, ISBN:92-5-104219-5); Priestley and Taylor (1972)
<doi:10/cr3qwn>; or Hargreaves and Samani (1985) <doi:10.13031/2013.26773>.
Users may specify a management allowed depletion (MAD), which is used to suggest
when to irrigate.  The functionality allows for the use of crop and water stress
coefficients as well.")
    (license license:expat)))

(define-public r-cropscaper
  (package
    (name "r-cropscaper")
    (version "1.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CropScapeR" version))
       (sha256
        (base32 "0dhziq4fybb987jv10g0wd4n765c4d87h86g96qg8wg6cx11vi6m"))))
    (properties `((upstream-name . "CropScapeR")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf
                             r-rjsonio
                             r-raster
                             r-magrittr
                             r-httr
                             r-dplyr
                             r-data-table))
    (home-page "https://cran.r-project.org/package=CropScapeR")
    (synopsis
     "Access Cropland Data Layer Data via the 'CropScape' Web Service")
    (description
     "Interface to easily access Cropland Data Layer (CDL) data for any area of
interest via the @code{CropScape}
<https://nassgeodata.gmu.edu/@code{CropScape/>} web service.")
    (license license:gpl2+)))

(define-public r-crops
  (package
    (name "r-crops")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crops" version))
       (sha256
        (base32 "0c1xvfnr4dh720x0i3f6nvmzgv8zbs7cvp8vfa341yb92pz4d6s0"))))
    (properties `((upstream-name . "crops")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyverse
                             r-tibble
                             r-sets
                             r-reshape
                             r-rdpack
                             r-memoise
                             r-magrittr
                             r-ggplot2
                             r-cowplot))
    (home-page "https://cran.r-project.org/package=crops")
    (synopsis "Changepoints for a Range of Penalties (CROPS)")
    (description
     "This package implements the Changepoints for a Range of Penalties (CROPS)
algorithm of Haynes et al. (2017) <doi:10.1080/10618600.2015.1116445> for
finding all of the optimal segmentations for multiple penalty values over a
continuous range.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-cropgrowdays
  (package
    (name "r-cropgrowdays")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cropgrowdays" version))
       (sha256
        (base32 "08k525882lm1x2igz1pk8g3kjiikcw68yqpic240l3lzq0x2wi3y"))))
    (properties `((upstream-name . "cropgrowdays")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-purrrlyr
                             r-purrr
                             r-lubridate
                             r-httr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://gitlab.com/petebaker/cropgrowdays/")
    (synopsis "Crop Growing Degree Days and Agrometeorological Calculations")
    (description
     "Calculate agrometeorological variables for crops including growing degree days
(@code{McMaster}, GS & Wilhelm, WW (1997) <doi:10.1016/S0168-1923(97)00027-0>),
cumulative rainfall, number of stress days and cumulative or mean radiation and
evaporation.  Convert dates to day of year and vice versa.  Also, download
curated and interpolated Australian weather data from the Queensland Government
DES longpaddock website <https://www.longpaddock.qld.gov.au/>.  This data is
freely available under the Creative Commons 4.0 licence.")
    (license license:expat)))

(define-public r-cropdemand
  (package
    (name "r-cropdemand")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cropDemand" version))
       (sha256
        (base32 "14frz3pdb3z8w513r64k0w8p6fs0gv04dazpwvjw6ky384wcd3w6"))))
    (properties `((upstream-name . "cropDemand")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-terra
                             r-sf
                             r-ncdf4
                             r-ggplot2
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=cropDemand")
    (synopsis "Spatial Crop Water Demand for Brazil")
    (description
     "Estimation of crop water demand can be processed via this package.  As example,
the data from @code{TerraClimate} dataset
(<https://www.climatologylab.org/terraclimate.html>) calibrated with automatic
weather stations of National Meteorological Institute of Brazil is available in
a coarse spatial resolution to do the crop water demand.  However, the user have
also the option to download the variables directly from @code{TerraClimate}
repository with the download.terraclimate function and access the original
@code{TerraClimate} products.  If the user believes that is necessary calibrate
the variables, there is another function to do it.  Lastly, the estimation of
the crop water demand present in this package can be run for all the Brazilian
territory with @code{TerraClimate} dataset.")
    (license (license:fsdg-compatible "CC BY 4.0"))))

(define-public r-cropdatape
  (package
    (name "r-cropdatape")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cropdatape" version))
       (sha256
        (base32 "19bn0apx4p8hnz388zg7sq59qv89vv8k5php317kcv7ai2k2gh34"))))
    (properties `((upstream-name . "cropdatape")))
    (build-system r-build-system)
    (home-page "https://github.com/omarbenites/cropdatape")
    (synopsis "Open Data of Agricultural Production of Crops of Peru")
    (description
     "This package provides peruvian agricultural production data from the Agriculture
Minestry of Peru (MINAGRI).  The first version includes 6 crops: rice, quinoa,
potato, sweet potato, tomato and wheat; all of them across 24 departments.
Initially, in excel files which has been transformed and assembled using tidy
data principles, i.e.  each variable is in a column, each observation is a row
and each value is in a cell.  The variables variables are sowing and harvest
area per crop, yield, production and price per plot, every one year, from 2004
to 2014.")
    (license license:expat)))

(define-public r-cropcircles
  (package
    (name "r-cropcircles")
    (version "0.2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cropcircles" version))
       (sha256
        (base32 "16by5gqdzgkd2qycslnxfhphpcil9w31mf9p4am9pzcc1gi06a71"))))
    (properties `((upstream-name . "cropcircles")))
    (build-system r-build-system)
    (propagated-inputs (list r-purrr r-magick r-glue))
    (home-page "https://github.com/doehm/cropcircles")
    (synopsis "Crops an Image to a Circle")
    (description
     "Images are cropped to a circle with a transparent background.  The function
takes a vector of images, either local or from a link, and circle crops the
image.  Paths to the cropped image are returned for plotting with ggplot2'.
Also includes cropping to a hexagon, heart, parallelogram, and square.")
    (license license:expat)))

(define-public r-crop
  (package
    (name "r-crop")
    (version "0.0-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crop" version))
       (sha256
        (base32 "12nngv12p3x8nm26c23xm3xamp8gsm9p1cd2cn5lrfjb9igvc0yy"))))
    (properties `((upstream-name . "crop")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=crop")
    (synopsis "Graphics Cropping Tool")
    (description
     "This package provides a device closing function which is able to crop graphics
(e.g., PDF, PNG files) on Unix-like operating systems with the required
underlying command-line tools installed.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-cronr
  (package
    (name "r-cronr")
    (version "0.6.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cronR" version))
       (sha256
        (base32 "000kd3pa1di8qhnjxlfp3dknckxdzrwmyzkwpmkrhnbpl9bf64yp"))))
    (properties `((upstream-name . "cronR")))
    (build-system r-build-system)
    (inputs (list))
    (propagated-inputs (list r-digest))
    (home-page "https://github.com/bnosac/cronR")
    (synopsis "Schedule R Scripts and Processes with the 'cron' Job Scheduler")
    (description
     "Create, edit, and remove cron jobs on your unix-alike system.  The package
provides a set of easy-to-use wrappers to crontab'.  It also provides an RStudio
add-in to easily launch and schedule your scripts.")
    (license license:expat)))

(define-public r-cronologia
  (package
    (name "r-cronologia")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cronologia" version))
       (sha256
        (base32 "143wc9i9d99cybnjzg4dj7jn7sv3cc4bq3hh6mp50j9hwxnr1xhh"))))
    (properties `((upstream-name . "cronologia")))
    (build-system r-build-system)
    (propagated-inputs (list r-htmltools r-glue))
    (home-page "https://github.com/feddelegrand7/cronologia")
    (synopsis
     "Create an HTML Vertical Timeline from a Data Frame in 'rmarkdown' and 'shiny'")
    (description
     "This package creates an HTML vertical timeline from a data frame as an input for
rmarkdown documents and shiny applications.")
    (license license:agpl3+)))

(define-public r-crone
  (package
    (name "r-crone")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crone" version))
       (sha256
        (base32 "03qznxml940rl3kfxy4jkg9nsx9ss0gf2ck0ry000xglw6rm2s42"))))
    (properties `((upstream-name . "crone")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=crone")
    (synopsis "Structural Crystallography in 1d")
    (description
     "This package provides functions to carry out the most important crystallographic
calculations for crystal structures made of 1d Gaussian-shaped atoms, especially
useful for methods development.  Main reference: E. Smith, G. Evans, J. Foadi
(2017) <doi:10.1088/1361-6404/aa8188>.")
    (license license:gpl2)))

(define-public r-cronbach
  (package
    (name "r-cronbach")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Cronbach" version))
       (sha256
        (base32 "1gkapi7pgf1mwidhgdf3y5cm4bz5igzb7mdflz560aa67asp1qyf"))))
    (properties `((upstream-name . "Cronbach")))
    (build-system r-build-system)
    (propagated-inputs (list r-boot))
    (home-page "https://cran.r-project.org/package=Cronbach")
    (synopsis "Cronbach's Alpha")
    (description
     "Cronbach's alpha and various formulas for confidence intervals.  The relevant
paper is Tsagris M., Frangos C.C. and Frangos C.C. (2013). \"Confidence intervals
for Cronbach's reliability coefficient\".  Recent Techniques in Educational
Science, 14-16 May, Athens, Greece.")
    (license license:gpl2+)))

(define-public r-cromwelldashboard
  (package
    (name "r-cromwelldashboard")
    (version "0.5.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cromwellDashboard" version))
       (sha256
        (base32 "0d57c1wdd1ds9fr7p256la63qbv8mirljgrvl1k8fp5gcnkps5wb"))))
    (properties `((upstream-name . "cromwellDashboard")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-shinydashboard
                             r-shiny
                             r-httr
                             r-dt
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=cromwellDashboard")
    (synopsis "Dashboard to Visualize Scientific Workflows in 'Cromwell'")
    (description
     "This package provides a dashboard supports the usage of cromwell'.  Cromwell is
a scientific workflow engine for command line users.  This package utilizes
cromwell REST APIs and provides these convenient functions: timing diagrams for
running workflows, cromwell engine status, a tabular workflow list.  For more
information about cromwell', visit <http://cromwell.readthedocs.io>.")
    (license license:gpl3)))

(define-public r-crmreg
  (package
    (name "r-crmreg")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crmReg" version))
       (sha256
        (base32 "0y6xb0sxhsqcmcwbkwvk70snwqhxgzl513ld9dp53cm88qdwaj1r"))))
    (properties `((upstream-name . "crmReg")))
    (build-system r-build-system)
    (propagated-inputs (list r-rrcov
                             r-robustbase
                             r-plyr
                             r-pcapp
                             r-gplots
                             r-ggplot2
                             r-fnn))
    (home-page "https://cran.r-project.org/package=crmReg")
    (synopsis "Cellwise Robust M-Regression and SPADIMO")
    (description
     "Method for fitting a cellwise robust linear M-regression model (CRM, Filzmoser
et al. (2020) <DOI:10.1016/j.csda.2020.106944>) that yields both a map of
cellwise outliers consistent with the linear model, and a vector of regression
coefficients that is robust against vertical outliers and leverage points.  As a
by-product, the method yields an imputed data set that contains estimates of
what the values in cellwise outliers would need to amount to if they had fit the
model.  The package also provides diagnostic tools for analyzing casewise and
cellwise outliers using sparse directions of maximal outlyingness (SPADIMO,
Debruyne et al. (2019) <DOI:10.1007/s11222-018-9831-5>).")
    (license license:gpl2+)))

(define-public r-crmpack
  (package
    (name "r-crmpack")
    (version "1.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crmPack" version))
       (sha256
        (base32 "1wdar6i0h184ynddvl2w6ipbdappncl0grsw7g4hnfiz1hw9x9p4"))))
    (properties `((upstream-name . "crmPack")))
    (build-system r-build-system)
    (propagated-inputs (list r-rjags
                             r-mvtnorm
                             r-mass
                             r-gridextra
                             r-ggplot2
                             r-gensa))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/openpharma/crmPack")
    (synopsis "Object-Oriented Implementation of CRM Designs")
    (description
     "This package implements a wide range of model-based dose escalation designs,
ranging from classical and modern continual reassessment methods (CRMs) based on
dose-limiting toxicity endpoints to dual-endpoint designs taking into account a
biomarker/efficacy outcome.  The focus is on Bayesian inference, making it very
easy to setup a new design with its own JAGS code.  However, it is also possible
to implement 3+3 designs for comparison or models with non-Bayesian estimation.
The whole package is written in a modular form in the S4 class system, making it
very flexible for adaptation to new models, escalation or stopping rules.")
    (license license:gpl2+)))

(define-public r-crmn
  (package
    (name "r-crmn")
    (version "0.0.21")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crmn" version))
       (sha256
        (base32 "0wp99fsw7y859gp1x22f77r9rv1m0xspbzhzgshzf7hi86xb57k5"))))
    (properties `((upstream-name . "crmn")))
    (build-system r-build-system)
    (propagated-inputs (list r-pcamethods r-biobase))
    (home-page "https://github.com/hredestig/crmn")
    (synopsis "CCMN and Other Normalization Methods for Metabolomics Data")
    (description
     "This package implements the Cross-contribution Compensating Multiple standard
Normalization (CCMN) method described in Redestig et al. (2009) Analytical
Chemistry <doi:10.1021/ac901143w> and other normalization algorithms.")
    (license license:gpl3+)))

(define-public r-crmetrics
  (package
    (name "r-crmetrics")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CRMetrics" version))
       (sha256
        (base32 "1abrbkhhn5s3h4dam2pgmvqpqw0bpqzhj0521p7v48gsyfg224bw"))))
    (properties `((upstream-name . "CRMetrics")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-sparsematrixstats
                             r-sccore
                             r-scales
                             r-r6
                             r-matrix
                             r-magrittr
                             r-ggrepel
                             r-ggpubr
                             r-ggpmisc
                             r-ggplot2
                             r-ggbeeswarm
                             r-dplyr
                             r-cowplot))
    (home-page "https://github.com/khodosevichlab/CRMetrics")
    (synopsis "Cell Ranger Output Filtering and Metrics Visualization")
    (description
     "Sample and cell filtering as well as visualisation of output metrics from Cell
Ranger by Grace X.Y. Zheng et al. (2017) <doi:10.1038/ncomms14049>.  CRMetrics
allows for easy plotting of output metrics across multiple samples as well as
comparative plots including statistical assessments of these.  CRMetrics allows
for easy removal of ambient RNA using @code{SoupX} by Matthew D Young and Sam
Behjati (2020) <doi:10.1093/gigascience/giaa151> or @code{CellBender} by Stephen
J Fleming et al. (2022) <doi:10.1101/791699>.  Furthermore, it is possible to
preprocess data using Pagoda2 by Nikolas Barkas et al. (2021)
<https://github.com/kharchenkolab/pagoda2> or Seurat by Yuhan Hao et al. (2021)
<doi:10.1016/j.cell.2021.04.048> followed by embedding of cells using Conos by
Nikolas Barkas et al. (2019) <doi:10.1038/s41592-019-0466-z>.  Finally, doublets
can be detected using scrublet by Samuel L. Wolock et al. (2019)
<doi:10.1016/j.cels.2018.11.005> or @code{DoubletDetection} by Gayoso et al.
(2020) <doi:10.5281/zenodo.2678041>.  In the end, cells are filtered based on
user input for use in downstream applications.")
    (license license:gpl3)))

(define-public r-crm12comb
  (package
    (name "r-crm12comb")
    (version "0.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crm12Comb" version))
       (sha256
        (base32 "08jbalbz43qjwjk9lmibp7fyhic41zvfc1frmkdar7p6fnzb8xc4"))))
    (properties `((upstream-name . "crm12Comb")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2 r-ggforce r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=crm12Comb")
    (synopsis "Phase I/II CRM Based Drug Combination Design")
    (description
     "This package implements the adaptive designs for integrated phase I/II trials of
drug combinations via continual reassessment method (CRM) to evaluate toxicity
and efficacy simultaneously for each enrolled patient cohort based on Bayesian
inference.  It supports patients assignment guidance in a single trial using
current enrolled data, as well as conducting extensive simulation studies to
evaluate operating characteristics before the trial starts.  It includes various
link functions such as empiric, one-parameter logistic, two-parameter logistic,
and hyperbolic tangent, as well as considering multiple prior distributions of
the parameters like normal distribution, gamma distribution and exponential
distribution to accommodate diverse clinical scenarios.  Method using Bayesian
framework with empiric link function is described in: Wages and Conaway (2014)
<doi:10.1002/sim.6097>.")
    (license license:gpl3+)))

(define-public r-crm
  (package
    (name "r-crm")
    (version "1.2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CRM" version))
       (sha256
        (base32 "0jv2z1y3zyj1m86p4pmqww58hj8pvid1ss6ym67y46n9srzxsmj5"))))
    (properties `((upstream-name . "CRM")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CRM")
    (synopsis
     "Continual Reassessment Method (CRM) for Phase I Clinical Trials")
    (description
     "This package provides functions for phase I clinical trials using the continual
reassessment method.")
    (license license:gpl2+)))

(define-public r-critpath
  (package
    (name "r-critpath")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "critpath" version))
       (sha256
        (base32 "0y9vbsdppi8xir1rvk8j7zvj69gjmc2whpqfcklws898rcnwck1f"))))
    (properties `((upstream-name . "critpath")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-reshape2 r-ggplot2 r-dplyr
                             r-diagrammer))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=critpath")
    (synopsis "Setting the Critical Path in Project Management")
    (description
     "Solving the problem of project management using CPM (Critical Path Method), PERT
(Program Evaluation and Review Technique) and LESS (Least Cost Estimating and
Scheduling) methods.  The package sets the critical path, schedule and Gantt
chart.  In addition, it allows to draw a graph even with marked critical
activities.  For more information about project management see: Taha H. A.
\"Operations Research.  An Introduction\" (2017, ISBN:978-1-292-16554-7), Rama
Murthy P. \"Operations Research\" (2007, ISBN:978-81-224-2944-2), Yuval Cohen &
Arik Sadeh (2006) \"A New Approach for Constructing and Generating AOA Networks\",
Journal of Engineering, Computing and Architecture 1.  1-13, Konarzewska I.,
Jewczak M., Kucharski A. (2020, ISBN:978-83-8220-112-3), MiszczyÅska D.,
MiszczyÅski M. \"Wybrane metody badaÅ operacyjnych\" (2000, ISBN:83-907712-0-9).")
    (license license:gpl2)))

(define-public r-criticalpath
  (package
    (name "r-criticalpath")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "criticalpath" version))
       (sha256
        (base32 "1b8iwvdlq5czd7p7yy6il3irrcarc23cy26vprycnyjll38lcfjz"))))
    (properties `((upstream-name . "criticalpath")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-r6
                             r-magrittr
                             r-igraph
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://rubensjoserosa.com/criticalpath")
    (synopsis "An Implementation of the Critical Path Method")
    (description
     "An R implementation of the Critical Path Method (CPM).  CPM is a method used to
estimate the minimum project duration and determine the amount of scheduling
flexibility on the logical network paths within the schedule model.  The
flexibility is in terms of early start, early finish, late start, late finish,
total float and free float.  Beside, it permits to quantify the complexity of
network diagram through the analysis of topological indicators.  Finally, it
permits to change the activities duration to perform what-if scenario analysis.
The package was built based on following references: To make topological sorting
and other graph operation, we use Csardi, G. & Nepusz, T. (2005)
<https://www.researchgate.net/publication/221995787_The_Igraph_Software_Package_for_Complex_Network_Research>;
For schedule concept, the reference was Project Management Institute (2017)
<https://www.pmi.org/pmbok-guide-standards/foundational/pmbok>; For standards
terms, we use Project Management Institute (2017)
<https://www.pmi.org/pmbok-guide-standards/lexicon>; For algorithms on Critical
Path Method development, we use Vanhoucke, M. (2013)
<doi:10.1007/978-3-642-40438-2> and Vanhoucke, M. (2014)
<doi:10.1007/978-3-319-04331-9>; And, finally, for topological definitions, we
use Vanhoucke, M. (2009) <doi:10.1007/978-1-4419-1014-1>.")
    (license license:expat)))

(define-public r-criticality
  (package
    (name "r-criticality")
    (version "0.9.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "criticality" version))
       (sha256
        (base32 "0cy08v2lqld9y9cc140hxk734r9pb66cx2c04303c9rl81gy1cmk"))))
    (properties `((upstream-name . "criticality")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales
                             r-reticulate
                             r-magrittr
                             r-keras
                             r-ggplot2
                             r-fitdistrplus
                             r-evd
                             r-dplyr
                             r-caret
                             r-bnlearn))
    (home-page "https://cran.r-project.org/package=criticality")
    (synopsis "Modeling Fissile Material Operations in Nuclear Facilities")
    (description
     "This package provides a collection of functions for modeling fissile material
operations in nuclear facilities, based on Zywiec et al (2021)
<doi:10.1016/j.ress.2020.107322>.")
    (license license:expat)))

(define-public r-crisprdesignr
  (package
    (name "r-crisprdesignr")
    (version "1.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crispRdesignR" version))
       (sha256
        (base32 "0z0sc0plq6x68b70pprzr7p7wpv8zsvg9ygi0gv1djh5j4wiaiz1"))))
    (properties `((upstream-name . "crispRdesignR")))
    (build-system r-build-system)
    (propagated-inputs (list r-vtreat
                             r-stringr
                             r-shiny
                             r-s4vectors
                             r-rtracklayer
                             r-iranges
                             r-genomicranges
                             r-genomeinfodb
                             r-gbm
                             r-dt
                             r-biostrings
                             r-biocgenerics))
    (home-page "<https://github.com/dylanbeeber/crispRdesignR>")
    (synopsis "Guide Sequence Design for CRISPR/Cas9")
    (description
     "Designs guide sequences for CRISPR/Cas9 genome editing and provides information
on sequence features pertinent to guide efficiency.  Sequence features include
annotated off-target predictions in a user-selected genome and a predicted
efficiency score based on the model described in Doench et al. (2016)
<doi:10.1038/nbt.3437>.  Users are able to import additional genomes and genome
annotation files to use when searching and annotating off-target hits.  All
guide sequences and off-target data can be generated through the R console with
@code{sgRNA_Design}() or through @code{crispRdesignR's} user interface with
@code{crispRdesignRUI}().  CRISPR (Clustered Regularly Interspaced Short
Palindromic Repeats) and the associated protein Cas9 refer to a technique used
in genome editing.")
    (license license:gpl3)))

(define-public r-crisp
  (package
    (name "r-crisp")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crisp" version))
       (sha256
        (base32 "1gs8jnd9y9pd55w6kwv9mvmg3wd8hjiw3lwx7k242pxccsxklfxq"))))
    (properties `((upstream-name . "crisp")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-mass))
    (home-page "https://cran.r-project.org/package=crisp")
    (synopsis
     "Fits a Model that Partitions the Covariate Space into Blocks in a Data- Adaptive Way")
    (description
     "This package implements convex regression with interpretable sharp partitions
(CRISP), which considers the problem of predicting an outcome variable on the
basis of two covariates, using an interpretable yet non-additive model.  CRISP
partitions the covariate space into blocks in a data-adaptive way, and fits a
mean model within each block.  Unlike other partitioning methods, CRISP is fit
using a non-greedy approach by solving a convex optimization problem, resulting
in low-variance fits.  More details are provided in Petersen, A., Simon, N., and
Witten, D. (2016).  Convex Regression with Interpretable Sharp Partitions.
Journal of Machine Learning Research, 17(94): 1-31
<http://jmlr.org/papers/volume17/15-344/15-344.pdf>.")
    (license license:gpl2+)))

(define-public r-crimeutils
  (package
    (name "r-crimeutils")
    (version "0.5.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crimeutils" version))
       (sha256
        (base32 "0jsh2b1kv8r9x8sx1s2x6dpc8jyfnjsinycqb5wck5jcsswswgd6"))))
    (properties `((upstream-name . "crimeutils")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-scales
                             r-rlang
                             r-readr
                             r-magrittr
                             r-gt
                             r-gridextra
                             r-ggplot2
                             r-dplyr))
    (home-page "https://github.com/jacobkap/crimeutils/")
    (synopsis
     "Comprehensive Set of Functions to Clean, Analyze, and Present Crime Data")
    (description
     "This package provides a collection of functions that make it easier to
understand crime (or other) data, and assist others in understanding it.  The
package helps you read data from various sources, clean it, fix column names,
and graph the data.")
    (license license:expat)))

(define-public r-crimedata
  (package
    (name "r-crimedata")
    (version "0.3.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crimedata" version))
       (sha256
        (base32 "16b413drkxccxcq269spl6rwfmy61pwl7xq237g018nih439ym7d"))))
    (properties `((upstream-name . "crimedata")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-sf
                             r-rlang
                             r-purrr
                             r-osfr
                             r-dplyr
                             r-digest))
    (native-inputs (list r-knitr))
    (home-page "http://pkgs.lesscrime.info/crimedata/")
    (synopsis "Access Crime Data from the Open Crime Database")
    (description
     "Gives convenient access to publicly available police-recorded open crime data
from large cities in the United States that are included in the Crime Open
Database <https://osf.io/zyaqn/>.")
    (license license:expat)))

(define-public r-crimcv
  (package
    (name "r-crimcv")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crimCV" version))
       (sha256
        (base32 "0jj1m0f65pp7w6ml4dwj73y2n9q02nizp5jqi9ph7klk8x069hzk"))))
    (properties `((upstream-name . "crimCV")))
    (build-system r-build-system)
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=crimCV")
    (synopsis "Group-Based Modelling of Longitudinal Data")
    (description
     "This package provides a finite mixture of Zero-Inflated Poisson (ZIP) models for
analyzing criminal trajectories.")
    (license license:gpl2+)))

(define-public r-cricketr
  (package
    (name "r-cricketr")
    (version "0.0.26")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cricketr" version))
       (sha256
        (base32 "1y1zf9f59v95knggq5nna5rp7fqpv1swwvkajwqbpicc12g2azq4"))))
    (properties `((upstream-name . "cricketr")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml
                             r-scatterplot3d
                             r-plotrix
                             r-lubridate
                             r-httr
                             r-ggplot2
                             r-forecast
                             r-dplyr))
    (home-page "https://github.com/tvganesh/cricketr")
    (synopsis
     "Analyze Cricketers and Cricket Teams Based on ESPN Cricinfo Statsguru")
    (description
     "This package provides tools for analyzing performances of cricketers based on
stats in ESPN Cricinfo Statsguru.  The toolset can be used for analysis of
Tests,ODIs and Twenty20 matches of both batsmen and bowlers.  The package can
also be used to analyze team performances.")
    (license license:expat)))

(define-public r-cricketdata
  (package
    (name "r-cricketdata")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cricketdata" version))
       (sha256
        (base32 "07sj53c2ryvcichsa9b0ywmrslisbr4hkrnrf1crw7x1ym55hsan"))))
    (properties `((upstream-name . "cricketdata")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rvest
                             r-readr
                             r-lubridate
                             r-janitor
                             r-dplyr
                             r-cli))
    (native-inputs (list r-r-rsp r-knitr))
    (home-page "https://pkg.robjhyndman.com/cricketdata/")
    (synopsis "International Cricket Data")
    (description
     "Data on international and other major cricket matches from ESPNCricinfo
<https://www.espncricinfo.com> and Cricsheet <https://cricsheet.org>.  This
package provides some functions to download the data into tibbles ready for
analysis.")
    (license license:gpl3)))

(define-public r-crfsuite
  (package
    (name "r-crfsuite")
    (version "0.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crfsuite" version))
       (sha256
        (base32 "15ldbx8g9xa6sql6is2gcqryzqb9dad1hiarvrgmizdp5fd3gxnm"))))
    (properties `((upstream-name . "crfsuite")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/bnosac/crfsuite")
    (synopsis
     "Conditional Random Fields for Labelling Sequential Data in Natural Language Processing")
    (description
     "Wraps the CRFsuite library <https://github.com/chokkan/crfsuite> allowing users
to fit a Conditional Random Field model and to apply it on existing data.  The
focus of the implementation is in the area of Natural Language Processing where
this R package allows you to easily build and apply models for named entity
recognition, text chunking, part of speech tagging, intent recognition or
classification of any category you have in mind.  Next to training, a small web
application is included in the package to allow you to easily construct training
data.")
    (license license:bsd-3)))

(define-public r-crf
  (package
    (name "r-crf")
    (version "0.4-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CRF" version))
       (sha256
        (base32 "0jlcc1ffd2z7sz1szbi4vrp5rihmcp18bsw27x02ivi6l21nyivf"))))
    (properties `((upstream-name . "CRF")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/wulingyun/CRF")
    (synopsis "Conditional Random Fields")
    (description
     "This package implements modeling and computational tools for conditional random
fields (CRF) model as well as other probabilistic undirected graphical models of
discrete data with pairwise and unary potentials.")
    (license license:gpl2+)))

(define-public r-crew-cluster
  (package
    (name "r-crew-cluster")
    (version "0.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crew.cluster" version))
       (sha256
        (base32 "1n40rl1z64ig7jp637xrydnvzmpjad76xsd2avhb8nkbcima89f8"))))
    (properties `((upstream-name . "crew.cluster")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-xml2
                             r-vctrs
                             r-rlang
                             r-r6
                             r-ps
                             r-lifecycle
                             r-crew))
    (home-page "https://wlandau.github.io/crew.cluster/")
    (synopsis
     "Crew Launcher Plugins for Traditional High-Performance Computing Clusters")
    (description
     "In computationally demanding analysis projects, statisticians and data
scientists asynchronously deploy long-running tasks to distributed systems,
ranging from traditional clusters to cloud services.  The crew.cluster package
extends the mirai'-powered crew package with worker launcher plugins for
traditional high-performance computing systems.  Inspiration also comes from
packages mirai by Gao (2023) <https://github.com/shikokuchuo/mirai>, future by
Bengtsson (2021) <doi:10.32614/RJ-2021-048>, rrq by @code{FitzJohn} and Ashton
(2023) <https://github.com/mrc-ide/rrq>, clustermq by Schubert (2019)
<doi:10.1093/bioinformatics/btz284>), and batchtools by Lang, Bischl, and
Surmann (2017). <doi:10.21105/joss.00135>.")
    (license license:expat)))

(define-public r-crew-aws-batch
  (package
    (name "r-crew-aws-batch")
    (version "0.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crew.aws.batch" version))
       (sha256
        (base32 "06q06jc53w0yh91vs45r8g9q13avcfi6s30h2bwqbdsqsx6rk54r"))))
    (properties `((upstream-name . "crew.aws.batch")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-rlang
                             r-r6
                             r-paws-management
                             r-paws-compute
                             r-paws-common
                             r-crew
                             r-cli))
    (home-page "https://wlandau.github.io/crew.aws.batch/")
    (synopsis "Crew Launcher Plugin for AWS Batch")
    (description
     "In computationally demanding analysis projects, statisticians and data
scientists asynchronously deploy long-running tasks to distributed systems,
ranging from traditional clusters to cloud services.  The crew.aws.batch package
extends the mirai'-powered crew package with a worker launcher plugin for AWS
Batch.  Inspiration also comes from packages mirai by Gao (2023)
<https://github.com/shikokuchuo/mirai>, future by Bengtsson (2021)
<doi:10.32614/RJ-2021-048>, rrq by @code{FitzJohn} and Ashton (2023)
<https://github.com/mrc-ide/rrq>, clustermq by Schubert (2019)
<doi:10.1093/bioinformatics/btz284>), and batchtools by Lang, Bischl, and
Surmann (2017). <doi:10.21105/joss.00135>.")
    (license license:expat)))

(define-public r-crew
  (package
    (name "r-crew")
    (version "0.10.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crew" version))
       (sha256
        (base32 "0xrl4wpwl8jpdlxvvsh4nqb3wg08r3wz8qia4lpbp4ranngzz7sc"))))
    (properties `((upstream-name . "crew")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tibble
                             r-rlang
                             r-r6
                             r-ps
                             r-promises
                             r-processx
                             r-nanonext
                             r-mirai
                             r-later
                             r-getip
                             r-data-table
                             r-cli
                             r-autometric))
    (native-inputs (list r-knitr))
    (home-page "https://wlandau.github.io/crew/")
    (synopsis "Distributed Worker Launcher Framework")
    (description
     "In computationally demanding analysis projects, statisticians and data
scientists asynchronously deploy long-running tasks to distributed systems,
ranging from traditional clusters to cloud services.  The NNG'-powered mirai R
package by Gao (2023) <doi:10.5281/zenodo.7912722> is a sleek and sophisticated
scheduler that efficiently processes these intense workloads.  The crew package
extends mirai with a unifying interface for third-party worker launchers.
Inspiration also comes from packages.  future by Bengtsson (2021)
<doi:10.32614/RJ-2021-048>, rrq by @code{FitzJohn} and Ashton (2023)
<https://github.com/mrc-ide/rrq>, clustermq by Schubert (2019)
<doi:10.1093/bioinformatics/btz284>), and batchtools by Lang, Bischel, and
Surmann (2017) <doi:10.21105/joss.00135>.")
    (license license:expat)))

(define-public r-credule
  (package
    (name "r-credule")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "credule" version))
       (sha256
        (base32 "0kwjjkavch21grx845kdcansaj0g407v7z3wmhy4whra9ic12y76"))))
    (properties `((upstream-name . "credule")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/blenezet/credule")
    (synopsis "Credit Default Swap Functions")
    (description
     "It provides functions to bootstrap Credit Curves from market quotes (Credit
Default Swap - CDS - spreads) and price Credit Default Swaps - CDS.")
    (license license:expat)))

(define-public r-credsubs
  (package
    (name "r-credsubs")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "credsubs" version))
       (sha256
        (base32 "19l3vsjxd9lvaf67l61x9l0j4y124p93dfqzw7rl1ya5sxbdzs7a"))))
    (properties `((upstream-name . "credsubs")))
    (build-system r-build-system)
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=credsubs")
    (synopsis "Credible Subsets")
    (description
     "This package provides functions for constructing simultaneous credible bands and
identifying subsets via the \"credible subsets\" (also called \"credible
subgroups\") method.  Package documentation includes the vignette included in
this package, and the paper by Schnell, Fiecas, and Carlin (2020,
<doi:10.18637/jss.v094.i07>).")
    (license license:gpl3)))

(define-public r-creds
  (package
    (name "r-creds")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CREDS" version))
       (sha256
        (base32 "1llgxsmpk13gq75y2r3qiwwjcl87bknkryaw5dq0ndf17rj31mw8"))))
    (properties `((upstream-name . "CREDS")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=CREDS")
    (synopsis "Calibrated Ratio Estimator under Double Sampling Design")
    (description
     "Population ratio estimator (calibrated) under two-phase random sampling design
has gained enormous popularity in the recent time.  This package provides
functions for estimation population ratio (calibrated) under two phase sampling
design, including the approximate variance of the ratio estimator.  The improved
ratio estimator can be applicable for both the case, when auxiliary data is
available at unit level or aggregate level (eg., mean or total) for first phase
sampled.  Calibration weight of each unit of the second phase sample was
calculated.  Single and combined inclusion probabilities were also estimated for
both phases under two phase random [simple random sampling without replacement
(SRSWOR)] sampling.  The improved ratio estimator's percentage coefficient of
variation was also determined as a measure of accuracy.  This package has been
developed based on the theoretical development of Islam et al. (2021) and Ozgul
(2020) <doi:10.1080/00949655.2020.1844702>.")
    (license license:gpl3)))

(define-public r-creditrisk
  (package
    (name "r-creditrisk")
    (version "0.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CreditRisk" version))
       (sha256
        (base32 "1jw8r0fzh5kmwygf5mrhg91ahv42gdvd1f91h5bwff6y08q3h345"))))
    (properties `((upstream-name . "CreditRisk")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CreditRisk")
    (synopsis
     "Evaluation of Credit Risk with Structural and Reduced Form Models")
    (description
     "Evaluation of default probability of sovereign and corporate entities based on
structural or intensity based models and calibration on market Credit Default
Swap quotes.  References: Damiano Brigo, Massimo Morini, Andrea Pallavicini
(2013) <doi:10.1002/9781118818589>.  Print ISBN: 9780470748466, Online ISBN:
9781118818589.  Â© 2013 John Wiley & Sons Ltd.")
    (license license:expat)))

(define-public r-creditmodel
  (package
    (name "r-creditmodel")
    (version "1.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "creditmodel" version))
       (sha256
        (base32 "1nmp5h1cji7g2wh099zlgcqjxi30kcb0lv7b84w3dx9aplsja57l"))))
    (properties `((upstream-name . "creditmodel")))
    (build-system r-build-system)
    (propagated-inputs (list r-xgboost
                             r-rpart
                             r-glmnet
                             r-ggplot2
                             r-foreach
                             r-dplyr
                             r-doparallel
                             r-data-table
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=creditmodel")
    (synopsis "Toolkit for Credit Modeling, Analysis and Visualization")
    (description
     "This package provides a highly efficient R tool suite for Credit Modeling,
Analysis and Visualization.Contains infrastructure functionalities such as data
exploration and preparation, missing values treatment, outliers treatment,
variable derivation, variable selection, dimensionality reduction, grid search
for hyper parameters, data mining and visualization, model evaluation, strategy
analysis etc.  This package is designed to make the development of binary
classification models (machine learning based models as well as credit
scorecard) simpler and faster.  The references including: 1 Refaat, M. (2011,
ISBN: 9781447511199).  Credit Risk Scorecard: Development and Implementation
Using SAS; 2 Bezdek, James C.FCM: The fuzzy c-means clustering algorithm.
Computers & Geosciences (0098-3004),<DOI:10.1016/0098-3004(84)90020-7>.")
    (license license:agpl3)))

(define-public r-creditas
  (package
    (name "r-creditas")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CRediTas" version))
       (sha256
        (base32 "163m37bz99g6qvfbnbvvdv02x6984x5prsbj1d7mq08bnlmj9zr0"))))
    (properties `((upstream-name . "CRediTas")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ropensci/CRediTas/")
    (synopsis "Generate CRediT Author Statements")
    (description
     "This package provides a tiny package to generate C@code{RediT} author statements
(<https://credit.niso.org/>).  It provides three functions: create a template,
read it back and generate the C@code{RediT} author statement in a text file.")
    (license license:expat)))

(define-public r-createlogicalpcm
  (package
    (name "r-createlogicalpcm")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "createLogicalPCM" version))
       (sha256
        (base32 "1vm4pwyzpddzsfnji0qfvv9pmz6rvmss9g58q4laqi4q3r643v14"))))
    (properties `((upstream-name . "createLogicalPCM")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=createLogicalPCM")
    (synopsis
     "Create Logical Pairwise Comparison Matrix for the Analytic Hierarchy Process")
    (description
     "Create Pairwise Comparison Matrices for use in the Analytic Hierarchy Process.
The Pairwise Comparison Matrix created will be a logical matrix, which unlike a
random comparison matrix, is similar to what a rational decision maker would
create on the basis of a preference vector for the alternatives considered.")
    (license license:gpl3)))

(define-public r-cream
  (package
    (name "r-cream")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CREAM" version))
       (sha256
        (base32 "1lccpwn6c5pmykgf689gvvpqdcilkys4vclpxjhllhanjrfhcs3q"))))
    (properties `((upstream-name . "CREAM")))
    (build-system r-build-system)
    (home-page "https://github.com/bhklab/CREAM")
    (synopsis "Clustering of Genomic Regions Analysis Method")
    (description
     "This package provides a new method for identification of clusters of genomic
regions within chromosomes.  Primarily, it is used for calling clusters of
cis-regulatory elements (COREs).  CREAM uses genome-wide maps of genomic regions
in the tissue or cell type of interest, such as those generated from
chromatin-based assays including D@code{NaseI}, ATAC or @code{ChIP-Seq}.  CREAM
considers proximity of the elements within chromosomes of a given sample to
identify COREs in the following steps: 1) It identifies window size or the
maximum allowed distance between the elements within each CORE, 2) It identifies
number of elements which should be clustered as a CORE, 3) It calls COREs, 4) It
filters the COREs with lowest order which does not pass the threshold considered
in the approach.")
    (license license:gpl3+)))

(define-public r-cre
  (package
    (name "r-cre")
    (version "0.2.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CRE" version))
       (sha256
        (base32 "0pbdbzxwgc3k03ki1kdzr3n57p0g0dd2c819bzwcg3i18h4ssc04"))))
    (properties `((upstream-name . "CRE")))
    (build-system r-build-system)
    (propagated-inputs (list r-xtable
                             r-xgboost
                             r-superlearner
                             r-stringr
                             r-stabs
                             r-rrf
                             r-randomforest
                             r-mass
                             r-magrittr
                             r-logger
                             r-glmnet
                             r-ggplot2
                             r-gbm
                             r-data-table
                             r-bartcause
                             r-arules))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/NSAPH-Software/CRE")
    (synopsis
     "Interpretable Discovery and Inference of Heterogeneous Treatment Effects")
    (description
     "This package provides a new method for interpretable heterogeneous treatment
effects characterization in terms of decision rules via an extensive exploration
of heterogeneity patterns by an ensemble-of-trees approach, enforcing high
stability in the discovery.  It relies on a two-stage pseudo-outcome regression,
and it is supported by theoretical convergence guarantees.  Bargagli-Stoffi, F.
J., Cadei, R., Lee, K., & Dominici, F. (2023) Causal rule ensemble:
Interpretable Discovery and Inference of Heterogeneous Treatment Effects.
@code{arXiv} preprint <doi:10.48550/@code{arXiv.2009.09036>}.")
    (license license:gpl3)))

(define-public r-crctstepdown
  (package
    (name "r-crctstepdown")
    (version "0.5.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crctStepdown" version))
       (sha256
        (base32 "0jjskjr3nwxsg6fz317nyb0r6vj1m82adlc06pyhazyhb7hh1gzl"))))
    (properties `((upstream-name . "crctStepdown")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-reshape2
                             r-rcppparallel
                             r-rcppeigen
                             r-rcpp
                             r-lme4
                             r-ggpubr
                             r-ggplot2
                             r-fastglm))
    (home-page "https://cran.r-project.org/package=crctStepdown")
    (synopsis "Univariate Analysis of Cluster Trials with Multiple Outcomes")
    (description
     "Frequentist statistical inference for cluster randomised trials with multiple
outcomes that controls the family-wise error rate and provides nominal coverage
of confidence sets.  A full description of the methods can be found in Watson et
al. (2023) <doi:10.1002/sim.9831>.")
    (license license:cc-by-sa4.0)))

(define-public r-crch
  (package
    (name "r-crch")
    (version "1.2-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crch" version))
       (sha256
        (base32 "181yczk269nw7d1pprs5662lj1423lni0id0k3pg37ifqhjjdqzn"))))
    (properties `((upstream-name . "crch")))
    (build-system r-build-system)
    (propagated-inputs (list r-scoringrules r-sandwich r-ordinal r-formula))
    (native-inputs (list r-quarto))
    (home-page "https://topmodels.R-Forge.R-project.org/crch/")
    (synopsis "Censored Regression with Conditional Heteroscedasticity")
    (description
     "Different approaches to censored or truncated regression with conditional
heteroscedasticity are provided.  First, continuous distributions can be used
for the (right and/or left censored or truncated) response with separate linear
predictors for the mean and variance.  Second, cumulative link models for
ordinal data (obtained by interval-censoring continuous data) can be employed
for heteroscedastic extended logistic regression (HXLR).  In the latter type of
models, the intercepts depend on the thresholds that define the intervals.
Infrastructure for working with censored or truncated normal, logistic, and
Student-t distributions, i.e., d/p/q/r functions and distributions3 objects.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-crc32c
  (package
    (name "r-crc32c")
    (version "0.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crc32c" version))
       (sha256
        (base32 "149bwwpgw69j4msqplrv7yym2fjs7c9v7sq8418lzz9szyj87dzg"))))
    (properties `((upstream-name . "crc32c")))
    (build-system r-build-system)
    (inputs (list cmake))
    (propagated-inputs (list r-tidycpp))
    (home-page "https://github.com/google/crc32c")
    (synopsis "Cyclic Redundancy Check with CPU-Specific Acceleration")
    (description
     "Hardware-based support for CRC32C cyclic redundancy checksum function is made
available for x86_64 systems with SSE2 support as well as for arm64', and
detected at build-time via cmake with a software-based fallback.  This
functionality is exported at the C'-language level for use by other packages.
CRC32C is described in RFC 3270 at
<https://datatracker.ietf.org/doc/html/rfc3720> and is based on Castagnoli et al
<doi:10.1109/26.231911>.")
    (license license:gpl2+)))

(define-public r-crayons
  (package
    (name "r-crayons")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crayons" version))
       (sha256
        (base32 "0pfgkcs5mrdxq63zqkkdi5fb54swp0w342n6pzgn8lzw1wf4svba"))))
    (properties `((upstream-name . "crayons")))
    (build-system r-build-system)
    (propagated-inputs (list r-palette r-ggplot2))
    (home-page "https://github.com/christopherkenny/crayons")
    (synopsis "Color Palettes from Crayon Boxes")
    (description
     "This package provides color palettes based on crayon colors since the early
1900s.  Colors are based on various crayon colors, sets, and promotional
palettes, most of which can be found at
<https://en.wikipedia.org/wiki/List_of_Crayola_crayon_colors>.  All palettes are
discrete palettes and are not necessarily color-blind friendly.  Provides scales
for ggplot2 for discrete coloring.")
    (license license:expat)))

(define-public r-crawl
  (package
    (name "r-crawl")
    (version "2.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crawl" version))
       (sha256
        (base32 "0qn64n54lsj56r5xj7xk8irns95724zmdv0nscsm3jd06fqybgj4"))))
    (properties `((upstream-name . "crawl")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-sp
                             r-sf
                             r-rlang
                             r-rcpparmadillo
                             r-rcpp
                             r-purrr
                             r-mvtnorm
                             r-magrittr
                             r-lubridate
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=crawl")
    (synopsis
     "Fit Continuous-Time Correlated Random Walk Models to Animal Movement Data")
    (description
     "Fit continuous-time correlated random walk models with time indexed covariates
to animal telemetry data.  The model is fit using the Kalman-filter on a state
space version of the continuous-time stochastic movement process.")
    (license license:cc0)))

(define-public r-crassmat
  (package
    (name "r-crassmat")
    (version "0.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crassmat" version))
       (sha256
        (base32 "1c4ii34vh8y5b3z2maby4cafb3n2m9bnxv3762cy0z12mbg7zk1s"))))
    (properties `((upstream-name . "crassmat")))
    (build-system r-build-system)
    (propagated-inputs (list r-svmisc))
    (home-page "https://cran.r-project.org/package=crassmat")
    (synopsis "Conditional Random Sampling Sparse Matrices")
    (description
     "Conducts conditional random sampling on observed values in sparse matrices.
Useful for training and test set splitting sparse matrices prior to model
fitting in cross-validation procedures and estimating the predictive accuracy of
data imputation methods, such as matrix factorization or singular value
decomposition (SVD).  Although designed for applications with sparse matrices,
CRASSMAT can also be applied to complete matrices, as well as to those
containing missing values.")
    (license license:gpl3)))

(define-public r-cransearcher
  (package
    (name "r-cransearcher")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CRANsearcher" version))
       (sha256
        (base32 "09gw1s28gb0l2cn4w3asl6zlr7wfacxwafbdrayajwckyfkjl5dl"))))
    (properties `((upstream-name . "CRANsearcher")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-shinyjs
                             r-shiny
                             r-miniui
                             r-lubridate
                             r-dt
                             r-dplyr
                             r-curl))
    (home-page "https://github.com/RhoInc/CRANsearcher")
    (synopsis
     "RStudio Addin for Searching Packages in CRAN Database Based on Keywords")
    (description
     "One of the strengths of R is its vast package ecosystem.  Indeed, R packages
extend from visualization to Bayesian inference and from spatial analyses to
pharmacokinetics (<https://cran.r-project.org/web/views/>).  There is probably
not an area of quantitative research that isn't represented by at least one R
package.  At the time of this writing, there are more than 10,000 active CRAN
packages.  Because of this massive ecosystem, it is important to have tools to
search and learn about packages related to your personal R needs.  For this
reason, we developed an RStudio addin capable of searching available CRAN
packages directly within RStudio.")
    (license license:expat)))

(define-public r-cranly
  (package
    (name "r-cranly")
    (version "0.6.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cranly" version))
       (sha256
        (base32 "1i8bk6wvar21y3bsr6by7dway8khsxwbyyw554pjwdpmxs3nz030"))))
    (properties `((upstream-name . "cranly")))
    (build-system r-build-system)
    (propagated-inputs (list r-wordcloud
                             r-visnetwork
                             r-tm
                             r-stringr
                             r-igraph
                             r-ggplot2
                             r-countrycode
                             r-colorspace))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ikosmidis/cranly")
    (synopsis "Package Directives and Collaboration Networks in CRAN")
    (description
     "Core visualizations and summaries for the CRAN package database.  The package
provides comprehensive methods for cleaning up and organizing the information in
the CRAN package database, for building package directives networks (depends,
imports, suggests, enhances, linking to) and collaboration networks, producing
package dependence trees, and for computing useful summaries and producing
interactive visualizations from the resulting networks and summaries.  The
resulting networks can be coerced to igraph
<https://CRAN.R-project.org/package=igraph> objects for further analyses and
modelling.")
    (license license:gpl3)))

(define-public r-cranlogs
  (package
    (name "r-cranlogs")
    (version "2.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cranlogs" version))
       (sha256
        (base32 "02d9qrqyjj33naq3g7ykaw9dzzl1dq8qf13id6h7kfx1fvx9b7zd"))))
    (properties `((upstream-name . "cranlogs")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr))
    (home-page "https://github.com/r-hub/cranlogs")
    (synopsis "Download Logs from the 'RStudio' 'CRAN' Mirror")
    (description
     "API to the database of CRAN package downloads from the RStudio CRAN mirror'.
The database itself is at <http://cranlogs.r-pkg.org>, see
<https://github.com/r-hub/cranlogs.app> for the raw API'.")
    (license license:expat)))

(define-public r-cranlike
  (package
    (name "r-cranlike")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cranlike" version))
       (sha256
        (base32 "022kya5p0f92szpw751czjka7bzq297af4i2l33892yfxkapfqfg"))))
    (properties `((upstream-name . "cranlike")))
    (build-system r-build-system)
    (propagated-inputs (list r-rsqlite r-desc r-debugme r-dbi))
    (home-page "https://github.com/r-hub/cranlike")
    (synopsis "Tools for 'CRAN'-Like Repositories")
    (description
     "This package provides a set of functions to manage CRAN'-like repositories
efficiently.")
    (license license:gpl2+)))

(define-public r-crank
  (package
    (name "r-crank")
    (version "1.1-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crank" version))
       (sha256
        (base32 "0wwbdh5sfi2bg13nrlkxxij4k053kjx9afm4gjpgs6iir6pml711"))))
    (properties `((upstream-name . "crank")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=crank")
    (synopsis "Completing Ranks")
    (description
     "This package provides functions for completing and recalculating rankings and
sorting.")
    (license license:gpl2+)))

(define-public r-crandep
  (package
    (name "r-crandep")
    (version "0.3.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "crandep" version))
       (sha256
        (base32 "07y5gkxdr12v715zy9skgjhw3sjsjlscpfril4hcdz0qwhr5cy5d"))))
    (properties `((upstream-name . "crandep")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-rcpparmadillo
                             r-rcpp
                             r-pracma
                             r-igraph
                             r-gsl
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/clement-lee/crandep")
    (synopsis "Network Analysis of Dependencies of CRAN Packages")
    (description
     "The dependencies of CRAN packages can be analysed in a network fashion.  For
each package we can obtain the packages that it depends, imports, suggests, etc.
 By iterating this procedure over a number of packages, we can build, visualise,
and analyse the dependency network, enabling us to have a bird's-eye view of the
CRAN ecosystem.  One aspect of interest is the number of reverse dependencies of
the packages, or equivalently the in-degree distribution of the dependency
network.  This can be fitted by the power law and/or an extreme value mixture
distribution <doi:10.1111/stan.12355>, of which functions are provided.")
    (license license:gpl2+)))

(define-public r-cramer
  (package
    (name "r-cramer")
    (version "0.9-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cramer" version))
       (sha256
        (base32 "0i5qg912rp8m1br00kd3iidy1v1yrmzj21xmy2wbjyyqrzakykc3"))))
    (properties `((upstream-name . "cramer")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-boot))
    (home-page "https://cran.r-project.org/package=cramer")
    (synopsis
     "Multivariate Nonparametric Cramer-Test for the Two-Sample-Problem")
    (description
     "This package provides R routine for the so called two-sample Cramer-Test.  This
nonparametric two-sample-test on equality of the underlying distributions can be
applied to multivariate data as well as univariate data.  It offers two
possibilities to approximate the critical value both of which are included in
this package.")
    (license license:gpl2+)))

(define-public r-cragg
  (package
    (name "r-cragg")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cragg" version))
       (sha256
        (base32 "1iznv72g47r2yd26p1i06a72p8n0albgb4j4l3lndi39wrkrpbwd"))))
    (properties `((upstream-name . "cragg")))
    (build-system r-build-system)
    (propagated-inputs (list r-expm))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cragg")
    (synopsis "Tests for Weak Instruments in R")
    (description
     "This package implements Cragg-Donald (1993) <doi:10.1017/S0266466600007519> and
Stock and Yogo (2005) <doi:10.1017/CBO9780511614491.006> tests for weak
instruments in R.")
    (license license:gpl3+)))

(define-public r-crabs
  (package
    (name "r-crabs")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CRABS" version))
       (sha256
        (base32 "062nxmidji9qcp1v5hdh1806r99hkxqq5d9cay7xwby0h5qzl75x"))))
    (properties `((upstream-name . "CRABS")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-pracma
                             r-patchwork
                             r-magrittr
                             r-latex2exp
                             r-ggplot2
                             r-dplyr
                             r-desolve
                             r-colorspace
                             r-ape))
    (home-page "https://github.com/afmagee/CRABS")
    (synopsis "Congruent Rate Analyses in Birth-Death Scenarios")
    (description
     "Features tools for exploring congruent phylogenetic birth-death models.  It can
construct the pulled speciation- and net-diversification rates from a reference
model.  Given alternative speciation- or extinction rates, it can construct new
models that are congruent with the reference model.  Functionality is included
to sample new rate functions, and to visualize the distribution of one
congruence class.  See also Louca & Pennell (2020)
<doi:10.1038/s41586-020-2176-1>.")
    (license license:gpl3)))

(define-public r-cr2
  (package
    (name "r-cr2")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CR2" version))
       (sha256
        (base32 "1j9wkpfr6bk07sj1swcjih12qz0cin811k69ihizsi4190m5f49k"))))
    (properties `((upstream-name . "CR2")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-performance
                             r-nlme
                             r-matrix
                             r-magrittr
                             r-lme4
                             r-generics
                             r-dplyr
                             r-broom))
    (home-page "https://github.com/flh3/CR2")
    (synopsis
     "Compute Cluster Robust Standard Errors with Degrees of Freedom Adjustments")
    (description
     "Estimate different types of cluster robust standard errors (CR0, CR1, CR2) with
degrees of freedom adjustments.  Standard errors are computed based on Liang and
Zeger (1986) <doi:10.1093/biomet/73.1.13> and Bell and @code{McCaffrey}
<https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2002002/article/9058-eng.pdf?st=@code{NxMjN1YZ>}.
 Functions used in Huang and Li <doi:10.3758/s13428-021-01627-0>, Huang,
Wiedermann', and Zhang <doi:10.1080/00273171.2022.2077290>, and Huang, Zhang',
and Li (forthcoming: Journal of Research on Educational Effectiveness).")
    (license license:expat)))

(define-public r-cquad
  (package
    (name "r-cquad")
    (version "2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cquad" version))
       (sha256
        (base32 "0m8hakw0k58v3gb24vvcs7q7l98m2nmyqv712wdn9g16krq49hnr"))))
    (properties `((upstream-name . "cquad")))
    (build-system r-build-system)
    (propagated-inputs (list r-plm r-mass r-formula))
    (home-page "https://cran.r-project.org/package=cquad")
    (synopsis
     "Conditional Maximum Likelihood for Quadratic Exponential Models for Binary Panel Data")
    (description
     "Estimation, based on conditional maximum likelihood, of the quadratic
exponential model proposed by Bartolucci, F. & Nigro, V. (2010, Econometrica)
<DOI:10.3982/ECTA7531> and of a simplified and a modified version of this model.
 The quadratic exponential model is suitable for the analysis of binary
longitudinal data when state dependence (further to the effect of the covariates
and a time-fixed individual intercept) has to be taken into account.  Therefore,
this is an alternative to the dynamic logit model having the advantage of easily
allowing conditional inference in order to eliminate the individual intercepts
and then getting consistent estimates of the parameters of main interest (for
the covariates and the lagged response).  The simplified version of this model
does not distinguish, as the original model does, between the last time occasion
and the previous occasions.  The modified version formulates in a different way
the interaction terms and it may be used to test in a easy way state dependence
as shown in Bartolucci, F., Nigro, V. & Pigini, C. (2018, Econometric Reviews)
<DOI:10.1080/07474938.2015.1060039>.  The package also includes estimation of
the dynamic logit model by a pseudo conditional estimator based on the quadratic
exponential model, as proposed by Bartolucci, F. & Nigro, V. (2012, Journal of
Econometrics) <DOI:10.1016/j.jeconom.2012.03.004>.  For large time dimensions of
the panel, the computation of the proposed models involves a recursive function
from Krailo M. D., & Pike M. C. (1984, Journal of the Royal Statistical Society.
 Series C (Applied Statistics)) and Bartolucci F., Valentini, F. & Pigini C.
(2021, Computational Economics <DOI:10.1007/s10614-021-10218-2>.")
    (license license:gpl2+)))

(define-public r-cptnonpar
  (package
    (name "r-cptnonpar")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CptNonPar" version))
       (sha256
        (base32 "1mpjxy5wivadbska51g30594rqgdx3g0m4jr90lnnri2yb8a78kw"))))
    (properties `((upstream-name . "CptNonPar")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfast
                             r-rcpp
                             r-parallelly
                             r-iterators
                             r-foreach
                             r-doparallel))
    (home-page "https://github.com/EuanMcGonigle/CptNonPar")
    (synopsis
     "Nonparametric Change Point Detection for Multivariate Time Series")
    (description
     "This package implements the nonparametric moving sum procedure for detecting
changes in the joint characteristic function (NP-MOJO) for multiple change point
detection in multivariate time series.  See @code{McGonigle}, E. T., Cho, H.
(2023) <doi:10.48550/@code{arXiv.2305.07581>} for description of the NP-MOJO
methodology.")
    (license license:gpl3+)))

(define-public r-cptcity
  (package
    (name "r-cptcity")
    (version "1.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cptcity" version))
       (sha256
        (base32 "03g10pjpz7gb6daalinki7smfjhbadrsmnxf6qgygqdaxm3ah400"))))
    (properties `((upstream-name . "cptcity")))
    (build-system r-build-system)
    (home-page "https://github.com/ibarraespinosa/cptcity")
    (synopsis "'cpt-city' Colour Gradients")
    (description
     "Incorporates colour gradients from the cpt-city web archive available at
<http://soliton.vm.bytemark.co.uk/pub/cpt-city/>.")
    (license license:gpl3)))

(define-public r-cpt
  (package
    (name "r-cpt")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cpt" version))
       (sha256
        (base32 "0j9ns8qhcvwxnzl9rc59vmh5jdahnni5dxpmi38gxvvj5k9hd8p7"))))
    (properties `((upstream-name . "cpt")))
    (build-system r-build-system)
    (propagated-inputs (list r-randomforest r-nnet r-mass r-glmnet))
    (home-page "http://dept.stat.lsa.umich.edu/~johanngb")
    (synopsis "Classification Permutation Test")
    (description
     "Non-parametric test for equality of multivariate distributions.  Trains a
classifier to classify (multivariate) observations as coming from one of several
distributions.  If the classifier is able to classify the observations better
than would be expected by chance (using permutation inference), then the null
hypothesis that the distributions are equal is rejected.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-cpsvote
  (package
    (name "r-cpsvote")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cpsvote" version))
       (sha256
        (base32 "0nmg79isqwvxyg7zkfbshndfjb2fnc2ffg32hxvjvsy714lpljf6"))))
    (properties `((upstream-name . "cpsvote")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-rlang
                             r-readr
                             r-magrittr
                             r-forcats
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Reed-EVIC/cpsvote")
    (synopsis
     "Toolbox for Using the CPSâs Voting and Registration Supplement")
    (description
     "This package provides automated methods for downloading, recoding, and merging
selected years of the Current Population Survey's Voting and Registration
Supplement, a large N national survey about registration, voting, and non-voting
in United States federal elections.  Provides documentation for appropriate use
of sample weights to generate statistical estimates, drawing from Hur & Achen
(2013) <doi:10.1093/poq/nft042> and @code{McDonald} (2018)
<http://www.electproject.org/home/voter-turnout/voter-turnout-data>.")
    (license license:expat)))

(define-public r-cpsurvsim
  (package
    (name "r-cpsurvsim")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cpsurvsim" version))
       (sha256
        (base32 "1didw3zglzinb22r1r7shg9796mwb3cwfb53i86q7sl0ljbja11i"))))
    (properties `((upstream-name . "cpsurvsim")))
    (build-system r-build-system)
    (propagated-inputs (list r-plyr r-knitr r-hmisc))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/camillejo/cpsurvsim")
    (synopsis
     "Simulating Survival Data from Change-Point Hazard Distributions")
    (description
     "Simulates time-to-event data with type I right censoring using two methods: the
inverse CDF method and our proposed memoryless method.  The latter method takes
advantage of the memoryless property of survival and simulates a separate
distribution between change-points.  We include two parametric distributions:
exponential and Weibull.  Inverse CDF method draws on the work of Rainer Walke
(2010), <https://www.demogr.mpg.de/papers/technicalreports/tr-2010-003.pdf>.")
    (license license:gpl3+)))

(define-public r-cpsurv
  (package
    (name "r-cpsurv")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CPsurv" version))
       (sha256
        (base32 "1r68pp3jbcbwgfac132h30qx6ah780aychr49rlncn17xbdalxsh"))))
    (properties `((upstream-name . "CPsurv")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-muhaz))
    (home-page "https://cran.r-project.org/package=CPsurv")
    (synopsis "Nonparametric Change Point Estimation for Survival Data")
    (description
     "Nonparametric change point estimation for survival data based on p-values of
exact binomial tests.")
    (license license:gpl2)))

(define-public r-cpss
  (package
    (name "r-cpss")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cpss" version))
       (sha256
        (base32 "1j8hyhfkjwyq6nmfynlzl8q7n5irlzrqdqh83v7pfpizzjdhhfxq"))))
    (properties `((upstream-name . "cpss")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-rlang
                             r-rfast
                             r-rcpparmadillo
                             r-rcpp
                             r-mvtnorm
                             r-magrittr
                             r-gridextra
                             r-ggplot2
                             r-dplyr))
    (home-page "https://github.com/ghwang-nk/cpss")
    (synopsis "Change-Point Detection by Sample-Splitting Methods")
    (description
     "This package implements multiple change searching algorithms for a variety of
frequently considered parametric change-point models.  In particular, it
integrates a criterion proposed by Zou, Wang and Li (2020)
<doi:10.1214/19-AOS1814> to select the number of change-points in a data-driven
fashion.  Moreover, it also provides interfaces for user-customized change-point
models with one's own cost function and parameter estimation routine.  It is
easy to get started with the cpss.* set of functions by accessing their
documentation pages (e.g., ?cpss).")
    (license license:gpl3+)))

(define-public r-cpsr
  (package
    (name "r-cpsr")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cpsR" version))
       (sha256
        (base32 "06sdsqc17cnkn9zgy62dv56am7f1jvxiw205l7hbqlab4gbdp92a"))))
    (properties `((upstream-name . "cpsR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-jsonlite r-httr))
    (home-page "https://github.com/matt-saenz/cpsR")
    (synopsis "Load CPS Microdata into R Using the 'Census Bureau Data' API")
    (description
     "Load Current Population Survey (CPS) microdata into R using the Census Bureau
Data API (<https://www.census.gov/data/developers/data-sets.html>), including
basic monthly CPS and CPS ASEC microdata.")
    (license license:expat)))

(define-public r-cpseudomarg
  (package
    (name "r-cpseudomarg")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cPseudoMaRg" version))
       (sha256
        (base32 "1mf78pilhx4mqv8n0xrdzn9wkvhnb3bs7rill7n588f18bnjp9mh"))))
    (properties `((upstream-name . "cPseudoMaRg")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cPseudoMaRg")
    (synopsis "Constructs a Correlated Pseudo-Marginal Sampler")
    (description
     "The primary function @code{makeCPMSampler}() generates a sampler function which
performs the correlated pseudo-marginal method of Deligiannidis, Doucet and Pitt
(2017) <@code{arXiv:1511.04992>}.  If the rho= argument of
@code{makeCPMSampler}() is set to 0, then the generated sampler function
performs the original pseudo-marginal method of Andrieu and Roberts (2009)
<DOI:10.1214/07-AOS574>.  The sampler function is constructed with the user's
choice of prior, parameter proposal distribution, and the likelihood
approximation scheme.  Note that this algorithm is not automatically tuned--each
one of these arguments must be carefully chosen.")
    (license license:expat)))

(define-public r-cprr
  (package
    (name "r-cprr")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cprr" version))
       (sha256
        (base32 "049xnma0rdnya7zp05iraq15nwjgmdmli9g7xxprab822047vld7"))))
    (properties `((upstream-name . "cprr")))
    (build-system r-build-system)
    (home-page "http://github.com/anhoej/cprr")
    (synopsis "Functions for Working with Danish CPR Numbers")
    (description
     "Calculate date of birth, age, and gender, and generate anonymous sequence
numbers from CPR numbers.
<https://en.wikipedia.org/wiki/Personal_identification_number_(Denmark)>.")
    (license license:gpl3)))

(define-public r-cprobit
  (package
    (name "r-cprobit")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cprobit" version))
       (sha256
        (base32 "16fnndpkd226paahmadsddakj4yhybw7lp3csr73fwv78zfl2fj9"))))
    (properties `((upstream-name . "cprobit")))
    (build-system r-build-system)
    (propagated-inputs (list r-nortest r-gridextra r-ggplot2 r-car))
    (home-page "https://cran.r-project.org/package=cprobit")
    (synopsis "Conditional Probit Model for Analysing Continuous Outcomes")
    (description
     "This package implements the three-step workflow for robust analysis of change in
two repeated measurements of continuous outcomes, described in Ning et al. (in
press), \"Robust estimation of the effect of an exposure on the change in a
continuous outcome\", BMC Medical Research Methodology.")
    (license license:lgpl3)))

(define-public r-cpr
  (package
    (name "r-cpr")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cpr" version))
       (sha256
        (base32 "1vv7cmjf08accdpp5qjw9rad8yb9izc6bw440366ckh4q87306q4"))))
    (properties `((upstream-name . "cpr")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales
                             r-rgl
                             r-rcpparmadillo
                             r-rcpp
                             r-plot3d
                             r-lme4
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/dewittpe/cpr/")
    (synopsis "Control Polygon Reduction")
    (description
     "Implementation of the Control Polygon Reduction and Control Net Reduction
methods for finding parsimonious B-spline regression models.")
    (license license:gpl2+)))

(define-public r-cpprouting
  (package
    (name "r-cpprouting")
    (version "3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cppRouting" version))
       (sha256
        (base32 "1mhp6k2kwlhyrswlxi9f0f6ndvm5968ljp3k97c2m2sfbxaablxy"))))
    (properties `((upstream-name . "cppRouting")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppprogress r-rcppparallel r-rcpp r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/vlarmet/cppRouting")
    (synopsis
     "Algorithms for Routing and Solving the Traffic Assignment Problem")
    (description
     "Calculation of distances, shortest paths and isochrones on weighted graphs using
several variants of Dijkstra algorithm.  Proposed algorithms are unidirectional
Dijkstra (Dijkstra, E. W. (1959) <doi:10.1007/BF01386390>), bidirectional
Dijkstra (Goldberg, Andrew & Fonseca F. Werneck, Renato (2005)
<https://archive.siam.org/meetings/alenex05/papers/03agoldberg.pdf>), A* search
(P. E. Hart, N. J. Nilsson et B. Raphael (1968) <doi:10.1109/TSSC.1968.300136>),
new bidirectional A* (Pijls & Post (2009)
<https://repub.eur.nl/pub/16100/ei2009-10.pdf>), Contraction hierarchies (R.
Geisberger, P. Sanders, D. Schultes and D. Delling (2008)
<doi:10.1007/978-3-540-68552-4_24>), PHAST (D. Delling, A.Goldberg, A. Nowatzyk,
R. Werneck (2011) <doi:10.1016/j.jpdc.2012.02.007>).  Algorithms for solving the
traffic assignment problem are All-or-Nothing assignment, Method of Successive
Averages, Frank-Wolfe algorithm (M. Fukushima (1984)
<doi:10.1016/0191-2615(84)90029-8>), Conjugate and Bi-Conjugate Frank-Wolfe
algorithms (M. Mitradjieva, P. O. Lindberg (2012) <doi:10.1287/trsc.1120.0409>),
Algorithm-B (R. B. Dial (2006) <doi:10.1016/j.trb.2006.02.008>).")
    (license license:gpl2+)))

(define-public r-cppdoubles
  (package
    (name "r-cppdoubles")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cppdoubles" version))
       (sha256
        (base32 "1m5d4lwji6yrbzb68m61zkrkchj9mv7m0sdqg2vnxzr5799whckh"))))
    (properties `((upstream-name . "cppdoubles")))
    (build-system r-build-system)
    (propagated-inputs (list r-cpp11))
    (home-page "https://cran.r-project.org/package=cppdoubles")
    (synopsis "Fast Relative Comparisons of Floating Point Numbers in 'C++'")
    (description
     "Compare double-precision floating point vectors using relative differences.  All
equality operations are calculated using cpp11'.")
    (license license:expat)))

(define-public r-cppcheckr
  (package
    (name "r-cppcheckr")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cppcheckR" version))
       (sha256
        (base32 "1f3b8gadpiyxwxp34pd3i7s715dkm23427fp86vvnqvy9schg3ga"))))
    (properties `((upstream-name . "cppcheckR")))
    (build-system r-build-system)
    (arguments
     (list
      #:modules '((guix build r-build-system)
                  (guix build minify-build-system)
                  (guix build utils)
                  (ice-9 match))
      #:imported-modules `(,@%r-build-system-modules (guix build
                                                      minify-build-system))
      #:phases '(modify-phases %standard-phases
                  (add-after 'unpack 'process-javascript
                    (lambda* (#:key inputs #:allow-other-keys)
                      (with-directory-excursion "inst/"
                        (for-each (match-lambda
                                    ((source . target) (minify source
                                                               #:target target)))
                                  '())))))))
    (inputs (list cppcheck))
    (propagated-inputs (list r-xml2
                             r-v8
                             r-shiny
                             r-rstudioapi
                             r-rmarkdown
                             r-htmlwidgets))
    (native-inputs (list esbuild))
    (home-page "https://github.com/stla/cppcheckR")
    (synopsis "Check 'C' and 'C++' Files using 'Cppcheck'")
    (description
     "Allow to run Cppcheck (<https://cppcheck.sourceforge.io/>) on C and C++ files
with a R command or a RStudio addin.  The report appears in the RStudio viewer
pane as a formatted HTML file.  It is also possible to get this report with a
shiny application.  Cppcheck can spot many error types and it can also give some
recommendations on the code.")
    (license license:gpl3)))

(define-public r-cpp11eigen
  (package
    (name "r-cpp11eigen")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cpp11eigen" version))
       (sha256
        (base32 "1bnr08a0pspgbzpjgbvkgng9i4z094ljlw9zxf8gl83mygdh93xy"))))
    (properties `((upstream-name . "cpp11eigen")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://pacha.dev/cpp11eigen/")
    (synopsis "An 'Eigen' Interface")
    (description
     "This package provides function declarations and inline function definitions that
facilitate communication between R and the Eigen C++ library for linear algebra
and scientific computing.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-cpp11armadillo
  (package
    (name "r-cpp11armadillo")
    (version "0.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cpp11armadillo" version))
       (sha256
        (base32 "1kd66cfmxgbh45358iy031hxxqcx4y4yrbc04sqlpjyqif31ja25"))))
    (properties `((upstream-name . "cpp11armadillo")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://pacha.dev/cpp11armadillo/")
    (synopsis "An 'Armadillo' Interface")
    (description
     "This package provides function declarations and inline function definitions that
facilitate communication between R and the Armadillo C++ library for linear
algebra and scientific computing.  This implementation is detailed in Vargas
Sepulveda and Schneider Malamud (2024) <doi:10.48550/@code{arXiv.2408.11074>}.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-cpp
  (package
    (name "r-cpp")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CPP" version))
       (sha256
        (base32 "1kdf43pnavjbmxkvrj78fiwl0ykln9x9ck8pcivhj9q5rsfbhbh4"))))
    (properties `((upstream-name . "CPP")))
    (build-system r-build-system)
    (propagated-inputs (list r-mc2d r-kappalab r-ineq))
    (home-page "https://cran.r-project.org/package=CPP")
    (synopsis "Composition of Probabilistic Preferences (CPP)")
    (description
     "CPP is a multiple criteria decision method to evaluate alternatives on complex
decision making problems, by a probabilistic approach.  The CPP was created and
expanded by Sant'Anna, Annibal P. (2015) <doi:10.1007/978-3-319-11277-0>.")
    (license license:gpl2+)))

(define-public r-cpoptim
  (package
    (name "r-cpoptim")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CPoptim" version))
       (sha256
        (base32 "1i0rlv7k6mhh71hya5nc2xbk7061jghgcnlgdwiqb3zag709pf8c"))))
    (properties `((upstream-name . "CPoptim")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CPoptim")
    (synopsis "Convex Partition Optimisation")
    (description
     "Convex Partition is a black-box optimisation algorithm for single objective
real-parameters functions.  The basic principle is to progressively estimate and
exploit a regression tree similar to a CART (Classification and Regression Tree)
of the objective function.  For more details see de Paz (2024)
<doi:10.1007/978-3-031-62836-8_3> and Loh (2011) <doi:10.1002/widm.8> .")
    (license license:gpl2)))

(define-public r-cpop
  (package
    (name "r-cpop")
    (version "1.0.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cpop" version))
       (sha256
        (base32 "082ny87ph3wz5kbp2i4yzf9g6r3bihbgfynv060fy6sv0xb9hxc1"))))
    (properties `((upstream-name . "cpop")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack
                             r-rcpp
                             r-pracma
                             r-pacman
                             r-mathjaxr
                             r-ggplot2
                             r-crops))
    (home-page "https://cran.r-project.org/package=cpop")
    (synopsis
     "Detection of Multiple Changes in Slope in Univariate Time-Series")
    (description
     "Detects multiple changes in slope using the CPOP dynamic programming approach of
Fearnhead, Maidstone, and Letchford (2019) <doi:10.1080/10618600.2018.1512868>.
This method finds the best continuous piecewise linear fit to data under a
criterion that measures fit to data using the residual sum of squares, but
penalizes complexity based on an L0 penalty on changes in slope.  Further
information regarding the use of this package with detailed examples can be
found in Fearnhead and Grose (2024) <doi:10.18637/jss.v109.i07>.")
    (license license:gpl2+)))

(define-public r-cpncoverageanalysis
  (package
    (name "r-cpncoverageanalysis")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CPNCoverageAnalysis" version))
       (sha256
        (base32 "0w4yw6d41sgl1ypcmp3bxgz4p3cpnbqx73id17zklid4avr3y9yi"))))
    (properties `((upstream-name . "CPNCoverageAnalysis")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CPNCoverageAnalysis")
    (synopsis "Conceptual Properties Norming Studies as Parameter Estimation")
    (description
     "Implementation of conceptual properties norming studies, including estimates of
CPNs parameters with their corresponding variances and estimates for the
sampling process, and a sampling property function based on a modified empirical
distribution from the original data.")
    (license license:gpl3+)))

(define-public r-cpmr
  (package
    (name "r-cpmr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cpmr" version))
       (sha256
        (base32 "0scjp3v6li9hr7pbvmlci2qmdbmd1yzlcpr748bdm9cp548cjpqg"))))
    (properties `((upstream-name . "cpmr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-rfast r-generics))
    (home-page "https://github.com/psychelzh/cpmr")
    (synopsis "Connectome Predictive Modelling in R")
    (description
     "Connectome Predictive Modelling (CPM) (Shen et al. (2017)
<doi:10.1038/nprot.2016.178>) is a method to predict individual differences in
behaviour from brain functional connectivity.  cpmr provides a simple yet
efficient implementation of this method.")
    (license license:expat)))

(define-public r-cpmerccutoff
  (package
    (name "r-cpmerccutoff")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CpmERCCutoff" version))
       (sha256
        (base32 "1vmfhdi4mmfbw5zz5yhsqrqz7w5jpg0ls6d22mm8bplgssrc2kk9"))))
    (properties `((upstream-name . "CpmERCCutoff")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CpmERCCutoff")
    (synopsis
     "Calculation of Log2 Counts per Million Cutoff from ERCC Controls")
    (description
     "Implementation of the empirical method to derive log2 counts per million (CPM)
cutoff to filter out lowly expressed genes using ERCC spike-ins as described in
Goll and Bosinger et.al (2022)<doi:10.1101/2022.06.23.497396>.  This package
utilizes the synthetic @code{mRNA} control pairs developed by the External RNA
Controls Consortium (ERCC) (ERCC 1 / ERCC 2) that are spiked into sample pairs
at known ratios at various absolute abundances.  The relationship between the
observed and expected fold changes is then used to empirically determine an
optimal log2 CPM cutoff for filtering out lowly expressed genes.")
    (license license:gpl3+)))

(define-public r-cpmcglm
  (package
    (name "r-cpmcglm")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CPMCGLM" version))
       (sha256
        (base32 "07hx2ik5zg05w1h6i94398mp54q958phws9ydgp6syjqlp9dpf1p"))))
    (properties `((upstream-name . "CPMCGLM")))
    (build-system r-build-system)
    (propagated-inputs (list r-plyr r-mvtnorm r-abind))
    (home-page "https://cran.r-project.org/")
    (synopsis
     "Correction of the P-Value after Multiple Coding in Generalized Linear Models")
    (description
     "We propose to determine the correction of the significance level after multiple
coding of an explanatory variable in Generalized Linear Model.  The different
methods of correction of the p-value are the Single step Bonferroni procedure,
and resampling based methods developed by P.H.Westfall in 1993.  Resampling
methods are based on the permutation and the parametric bootstrap procedure.  If
some continuous, and dichotomous transformations are performed this package
offers an exact correction of the p-value developed by B.Liquet & D.Commenges in
2005.  The naive method with no correction is also available.")
    (license license:gpl3+)))

(define-public r-cpmbigdata
  (package
    (name "r-cpmbigdata")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cpmBigData" version))
       (sha256
        (base32 "0fdch6hj6l620gj0pk8ffrl9j2rmd9jlin7yx7myfy46qij1cxpi"))))
    (properties `((upstream-name . "cpmBigData")))
    (build-system r-build-system)
    (propagated-inputs (list r-sparsem
                             r-rms
                             r-iterators
                             r-hmisc
                             r-foreach
                             r-doparallel
                             r-benchmarkme))
    (home-page "https://cran.r-project.org/package=cpmBigData")
    (synopsis
     "Fitting Semiparametric Cumulative Probability Models for Big Data")
    (description
     "This package provides a big data version for fitting cumulative probability
models using the orm() function from the rms package.  See Liu et al. (2017)
<DOI:10.1002/sim.7433> for details.")
    (license license:gpl2+)))

(define-public r-cpm
  (package
    (name "r-cpm")
    (version "2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cpm" version))
       (sha256
        (base32 "07zbvc5jkwv76lkzby6r073fxjsqgnrdl2w9lcph577knnip89jx"))))
    (properties `((upstream-name . "cpm")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cpm")
    (synopsis
     "Sequential and Batch Change Detection Using Parametric and Nonparametric Methods")
    (description
     "Sequential and batch change detection for univariate data streams, using the
change point model framework.  Functions are provided to allow nonparametric
distribution-free change detection in the mean, variance, or general
distribution of a given sequence of observations.  Parametric change detection
methods are also provided for Gaussian, Bernoulli and Exponential sequences.
Both the batch (Phase I) and sequential (Phase II) settings are supported, and
the sequences may contain either a single or multiple change points.  A full
description of this package is available in Ross, G.J (2015) - \"Parametric and
nonparametric sequential change detection in R\" available at
<https://www.jstatsoft.org/article/view/v066i03>.")
    (license license:gpl3)))

(define-public r-cplots
  (package
    (name "r-cplots")
    (version "0.5-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cplots" version))
       (sha256
        (base32 "12nac8hywhsfh2fcv30w36la46hvvp5mwc2rrq34smraig0dq8f3"))))
    (properties `((upstream-name . "cplots")))
    (build-system r-build-system)
    (propagated-inputs (list r-circular))
    (home-page "https://cran.r-project.org/package=cplots")
    (synopsis "Plots for Circular Data")
    (description
     "This package provides functions to produce some circular plots for circular
data, in a height- or area-proportional manner.  They include bar plots, smooth
density plots, stacked dot plots, histograms, multi-class stacked smooth density
plots, and multi-class stacked histograms.")
    (license license:gpl2+)))

(define-public r-cpi
  (package
    (name "r-cpi")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cpi" version))
       (sha256
        (base32 "1gz92jcl8wg2vp8qhnkn37l2xs8wjdbjvnga22v9n943k9zsk2kh"))))
    (properties `((upstream-name . "cpi")))
    (build-system r-build-system)
    (propagated-inputs (list r-mlr3 r-lgr r-knockoff r-foreach))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/bips-hb/cpi")
    (synopsis "Conditional Predictive Impact")
    (description
     "This package provides a general test for conditional independence in supervised
learning algorithms as proposed by Watson & Wright (2021)
<doi:10.1007/s10994-021-06030-6>.  Implements a conditional variable importance
measure which can be applied to any supervised learning algorithm and loss
function.  Provides statistical inference procedures without parametric
assumptions and applies equally well to continuous and categorical predictors
and outcomes.")
    (license license:gpl3+)))

(define-public r-cpglib
  (package
    (name "r-cpglib")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CPGLIB" version))
       (sha256
        (base32 "10pv9f36cg4ahgcbl3agc6zvgh3bmv78rc2vl6xhm1jpijhxqk93"))))
    (properties `((upstream-name . "CPGLIB")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "https://cran.r-project.org/package=CPGLIB")
    (synopsis "Competing Proximal Gradients Library")
    (description
     "This package provides functions to generate ensembles of generalized linear
models using competing proximal gradients.  The optimal sparsity and diversity
tuning parameters are selected via an alternating grid search.")
    (license license:gpl2+)))

(define-public r-cpgfilter
  (package
    (name "r-cpgfilter")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CpGFilter" version))
       (sha256
        (base32 "0ccvk7lawmay0wqdyhs6ww7396dcfzazn72sq6zwyw7dl45k2j0i"))))
    (properties `((upstream-name . "CpGFilter")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrixstats))
    (home-page "https://cran.r-project.org/package=CpGFilter")
    (synopsis
     "CpG Filtering Method Based on Intra-Class Correlation Coefficients")
    (description
     "Filter @code{CpGs} based on Intra-class Correlation Coefficients (ICCs) when
replicates are available.  ICCs are calculated by fitting linear mixed effects
models to all samples including the un-replicated samples.  Including the large
number of un-replicated samples improves ICC estimates dramatically.  The method
accommodates any replicate design.")
    (license license:gpl3)))

(define-public r-cpgassoc
  (package
    (name "r-cpgassoc")
    (version "2.70")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CpGassoc" version))
       (sha256
        (base32 "0y3jwy4kpqw6r4w93bm1c7yjxpv5jyhpmgbbkagb7qjvbsg935qx"))))
    (properties `((upstream-name . "CpGassoc")))
    (build-system r-build-system)
    (propagated-inputs (list r-nlme))
    (home-page "https://cran.r-project.org/package=CpGassoc")
    (synopsis "Association Between Methylation and a Phenotype of Interest")
    (description
     "Is designed to test for association between methylation at @code{CpG} sites
across the genome and a phenotype of interest, adjusting for any relevant
covariates.  The package can perform standard analyses of large datasets very
quickly with no need to impute the data.  It can also handle mixed effects
models with chip or batch entering the model as a random intercept.  Also
includes tools to apply quality control filters, perform permutation tests, and
create QQ plots, manhattan plots, and scatterplots for individual @code{CpG}
sites.")
    (license license:gpl2+)))

(define-public r-cpfa
  (package
    (name "r-cpfa")
    (version "1.1-5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cpfa" version))
       (sha256
        (base32 "0bga39lipzcam6pr9sm1rij31b5la59arjjhsydh826gdfmnlqg9"))))
    (properties `((upstream-name . "cpfa")))
    (build-system r-build-system)
    (propagated-inputs (list r-xgboost
                             r-rda
                             r-randomforest
                             r-nnet
                             r-multiway
                             r-glmnet
                             r-foreach
                             r-e1071
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=cpfa")
    (synopsis "Classification with Parallel Factor Analysis")
    (description
     "Classification using Richard A. Harshman's Parallel Factor Analysis-1 (Parafac)
model or Parallel Factor Analysis-2 (Parafac2) model fit to a three-way or
four-way data array.  See Harshman and Lundy (1994):
<doi:10.1016/0167-9473(94)90132-5>.  Uses component weights from one mode of a
Parafac or Parafac2 model as features to tune parameters for one or more
classification methods via a k-fold cross-validation procedure.  Allows for
constraints on different tensor modes.  Supports penalized logistic regression,
support vector machine, random forest, feed-forward neural network, regularized
discriminant analysis, and gradient boosting machine.  Supports binary and
multiclass classification.  Predicts class labels or class probabilities and
calculates multiple classification performance measures.  Implements parallel
computing via the parallel and @code{doParallel} packages.")
    (license license:gpl2+)))

(define-public r-cpe
  (package
    (name "r-cpe")
    (version "1.6.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CPE" version))
       (sha256
        (base32 "1m62g6psfhzk6ravqiydg4ix422j1sgcx92qpg9fpz6xm6aa17vc"))))
    (properties `((upstream-name . "CPE")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rms))
    (home-page "https://cran.r-project.org/package=CPE")
    (synopsis "Concordance Probability Estimates in Survival Analysis")
    (description
     "Concordance probability estimate (CPE) is a commonly used performance measure in
survival analysis that evaluates the predictive accuracy of a survival model.
It measures how well a model can distinguish between pairs of individuals with
different survival times.  Specifically, it calculate the proportion of all
pairs of individuals whose predicted survival times are correctly ordered.")
    (license license:gpl2+)))

(define-public r-cpd
  (package
    (name "r-cpd")
    (version "0.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cpd" version))
       (sha256
        (base32 "0rffkw87j77k1r1ipi8avibbkfsp97g52amawz2nj1mrkgamj2g2"))))
    (properties `((upstream-name . "cpd")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-hypergeo r-dgof))
    (home-page "https://cran.r-project.org/package=cpd")
    (synopsis "Complex Pearson Distributions")
    (description
     "Probability mass function, distribution function, quantile function and random
generation for the Complex Triparametric Pearson (CTP) and Complex Biparametric
Pearson (CBP) distributions developed by Rodriguez-Avi et al (2003)
<doi:10.1007/s00362-002-0134-7>, Rodriguez-Avi et al (2004)
<doi:10.1007/BF02778271> and Olmo-Jimenez et al (2018)
<doi:10.1080/00949655.2018.1482897>.  The package also contains
maximum-likelihood fitting functions for these models.")
    (license license:gpl2+)))

(define-public r-cpcg
  (package
    (name "r-cpcg")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cPCG" version))
       (sha256
        (base32 "1pfbsv2rcjsryn6nr56a7i4yb7k0m3gdfn4q9l1kpzhmv9lic7m1"))))
    (properties `((upstream-name . "cPCG")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cPCG")
    (synopsis
     "Efficient and Customized Preconditioned Conjugate Gradient Method for Solving System of Linear Equations")
    (description
     "Solves system of linear equations using (preconditioned) conjugate gradient
algorithm, with improved efficiency using Armadillo templated C++ linear algebra
library, and flexibility for user-specified preconditioning method.  Please
check <https://github.com/styvon/@code{cPCG>} for latest updates.")
    (license license:gpl2+)))

(define-public r-cpcat
  (package
    (name "r-cpcat")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CPCAT" version))
       (sha256
        (base32 "0vi98pxpmrrkz15rn1b4kcs7x1fbkili10qw2p4ins7lrjvqjvdp"))))
    (properties `((upstream-name . "CPCAT")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CPCAT")
    (synopsis "The Closure Principle Computational Approach Test")
    (description
     "P-values and no/lowest observed (adverse) effect concentration values derived
from the closure principle computational approach test (Lehmann, R. et al.
(2015) <doi:10.1007/s00477-015-1079-4>) are provided.  The package contains
functions to generate intersection hypotheses according to the closure principle
(Bretz, F., Hothorn, T., Westfall, P. (2010) <doi:10.1201/9781420010909>), an
implementation of the computational approach test (Ching-Hui, C., Nabendu, P.,
Jyh-Jiuan, L. (2010) <doi:10.1080/03610918.2010.508860>) and the combination of
both, that is, the closure principle computational approach test.")
    (license license:gpl3+)))

(define-public r-cpc
  (package
    (name "r-cpc")
    (version "2.6.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CPC" version))
       (sha256
        (base32 "0n1vsn7b1rllbsad2bshhi0c6pz7zqz6bmcc176qh50hm4hgp99r"))))
    (properties `((upstream-name . "CPC")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfast r-dbscan r-cluster))
    (home-page "https://imehlhaff.net/CPC/")
    (synopsis "Implementation of Cluster-Polarization Coefficient")
    (description
     "This package implements cluster-polarization coefficient for measuring
distributional polarization in single or multiple dimensions, as well as
associated functions.  Contains support for hierarchical clustering, k-means,
partitioning around medoids, density-based spatial clustering with noise, and
manually imposed cluster membership.  Mehlhaff (forthcoming)
<doi:10.1017/S0003055423001041>.")
    (license license:cc0)))

(define-public r-cpbayes
  (package
    (name "r-cpbayes")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CPBayes" version))
       (sha256
        (base32 "1kw0r8spqm0s7cb3w5gplw67mhfmcbbf3ligngbary77ghkzirnb"))))
    (properties `((upstream-name . "CPBayes")))
    (build-system r-build-system)
    (propagated-inputs (list r-purrr r-mvtnorm r-mass r-forestplot))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ArunabhaCodes/CPBayes")
    (synopsis
     "Bayesian Meta Analysis for Studying Cross-Phenotype Genetic Associations")
    (description
     "This package provides a Bayesian meta-analysis method for studying
cross-phenotype genetic associations.  It uses summary-level data across
multiple phenotypes to simultaneously measure the evidence of aggregate-level
pleiotropic association and estimate an optimal subset of traits associated with
the risk locus.  CPBayes is based on a spike and slab prior.  The methodology is
available from: A Majumdar, T Haldar, S Bhattacharya, JS Witte (2018)
<doi:10.1371/journal.pgen.1007139>.")
    (license license:gpl3)))

(define-public r-cpat
  (package
    (name "r-cpat")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CPAT" version))
       (sha256
        (base32 "0zygncwww3cazwmx06bhzq0g41xcqfpw307azdhygc8jmcy6qj71"))))
    (properties `((upstream-name . "CPAT")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-rcpparmadillo r-rcpp r-purrr))
    (home-page "https://cran.r-project.org/package=CPAT")
    (synopsis "Change Point Analysis Tests")
    (description
     "This package implements several statistical tests for structural change,
specifically the tests featured in HorvÃ¡th, Rice and Miller (in press): CUSUM
(with weighted/trimmed variants), Darling-ErdÃ¶s, Hidalgo-Seo, Andrews, and the
new RÃ©nyi-type test.")
    (license license:expat)))

(define-public r-cpa
  (package
    (name "r-cpa")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cpa" version))
       (sha256
        (base32 "10g2pvjz396m3mis1bp8bggx9gvbhdd5yqf3sgwkimn9wgccymbq"))))
    (properties `((upstream-name . "cpa")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cpa")
    (synopsis "Confirmatory Path Analysis Through 'd-sep' Tests")
    (description
     "This package provides functions to test and compare causal models using
Confirmatory Path Analysis.")
    (license license:gpl2+)))

(define-public r-cp4p
  (package
    (name "r-cp4p")
    (version "0.3.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cp4p" version))
       (sha256
        (base32 "1zddkkj0ynvfck3kw1682wffbxw0d3dc4flmxxp03lclq70fc8bd"))))
    (properties `((upstream-name . "cp4p")))
    (build-system r-build-system)
    (propagated-inputs (list r-qvalue r-multtest r-mess r-limma))
    (home-page "https://cran.r-project.org/package=cp4p")
    (synopsis "Calibration Plot for Proteomics")
    (description
     "This package provides functions to check whether a vector of p-values respects
the assumptions of FDR (false discovery rate) control procedures and to compute
adjusted p-values.")
    (license license:gpl3)))

(define-public r-cp
  (package
    (name "r-cp")
    (version "1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CP" version))
       (sha256
        (base32 "1ydpkk3zqz3r2szny68wqa4hz5iczq1q0hkkcbw7na8sg68sgriq"))))
    (properties `((upstream-name . "CP")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival))
    (home-page "https://www.genstat.imise.uni-leipzig.de/")
    (synopsis "Conditional Power Calculations")
    (description
     "This package provides functions for calculating the conditional power for
different models in survival time analysis within randomized clinical trials
with two different treatments to be compared and survival as an endpoint.")
    (license license:gpl3)))

(define-public r-coxsei
  (package
    (name "r-coxsei")
    (version "0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coxsei" version))
       (sha256
        (base32 "1k3xsjwv1ji8n2qry2j93svr8a114mxkdl5y2zwz7mp82dmv0ld6"))))
    (properties `((upstream-name . "coxsei")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=coxsei")
    (synopsis "Fitting a CoxSEI Model")
    (description
     "Fit a @code{CoxSEI} (Cox type Self-Exciting Intensity) model to right-censored
counting process data.")
    (license license:gpl2+)))

(define-public r-coxrt
  (package
    (name "r-coxrt")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coxrt" version))
       (sha256
        (base32 "1xggczjx5psl4m4m83vh4y6swnh3pf9rngnzx3268iznfz1g43h2"))))
    (properties `((upstream-name . "coxrt")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-rcpparmadillo
                             r-rcpp
                             r-inline
                             r-gss
                             r-ggplot2
                             r-bb))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Bella2001/coxrt")
    (synopsis "Cox Proportional Hazards Regression for Right-Truncated Data")
    (description
     "Fits Cox regression based on retrospectively ascertained times-to-event.  The
method uses Inverse-Probability-Weighting estimating equations.")
    (license license:gpl2+)))

(define-public r-coxrobust
  (package
    (name "r-coxrobust")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coxrobust" version))
       (sha256
        (base32 "1g8z82y12b2lkw4ifxiidmwy3nrvgp2y2cwcahhdg616shwc27sb"))))
    (properties `((upstream-name . "coxrobust")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rcpparmadillo r-rcpp))
    (home-page "https://github.com/ShanaScogin/coxrobust")
    (synopsis "Fit Robustly Proportional Hazards Regression Model")
    (description
     "An implementation of robust estimation in Cox model.  Functionality includes
fitting efficiently and robustly Cox proportional hazards regression model in
its basic form, where explanatory variables are time independent with one event
per subject.  Method is based on a smooth modification of the partial
likelihood.")
    (license license:gpl3)))

(define-public r-coxr2
  (package
    (name "r-coxr2")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoxR2" version))
       (sha256
        (base32 "1fjsa403lbx0hi7b0gsdaz0q9axw521q4xzphbfbknify4y72md6"))))
    (properties `((upstream-name . "CoxR2")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival))
    (home-page "https://cran.r-project.org/package=CoxR2")
    (synopsis
     "R-Squared Measure Based on Partial LR Statistic, for the Cox PH Regression Model")
    (description
     "Calculate the R-squared, aka explained randomness, based on the partial
likelihood ratio statistic under the Cox Proportional Hazard model [J O'Quigley,
R Xu, J Stare (2005) <doi:10.1002/sim.1946>].")
    (license license:gpl2)))

(define-public r-coxplus
  (package
    (name "r-coxplus")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoxPlus" version))
       (sha256
        (base32 "038wsz206bgc0pnzx403b5ihcwhxpkrpxmwvrvqcxf8333pb62l5"))))
    (properties `((upstream-name . "CoxPlus")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "https://cran.r-project.org/package=CoxPlus")
    (synopsis
     "Cox Regression (Proportional Hazards Model) with Multiple Causes and Mixed Effects")
    (description
     "This package provides a high performance package estimating Cox Model when an
even has more than one causes.  It also supports random and fixed effects, tied
events, and time-varying variables.")
    (license license:gpl3+)))

(define-public r-coxphw
  (package
    (name "r-coxphw")
    (version "4.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coxphw" version))
       (sha256
        (base32 "06fp31amdqsq35glk1028w5v67i0k9k23gxnyqivi8s4fh66lwi6"))))
    (properties `((upstream-name . "coxphw")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival))
    (native-inputs (list r-knitr gfortran))
    (home-page "https://github.com/biometrician/coxphw")
    (synopsis "Weighted Estimation in Cox Regression")
    (description
     "This package implements weighted estimation in Cox regression as proposed by
Schemper, Wakounig and Heinze (Statistics in Medicine, 2009,
<doi:10.1002/sim.3623>) and as described in Dunkler, Ploner, Schemper and Heinze
(Journal of Statistical Software, 2018, <doi:10.18637/jss.v084.i02>).  Weighted
Cox regression provides unbiased average hazard ratio estimates also in case of
non-proportional hazards.  Approximated generalized concordance probability an
effect size measure for clear-cut decisions can be obtained.  The package
provides options to estimate time-dependent effects conveniently by including
interactions of covariates with arbitrary functions of time, with or without
making use of the weighting option.")
    (license license:gpl3)))

(define-public r-coxphsgd
  (package
    (name "r-coxphsgd")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coxphSGD" version))
       (sha256
        (base32 "17ga33v7a89dsygk5yypkz03x7dvjhibnwlvwfvgb2p7djd8w465"))))
    (properties `((upstream-name . "coxphSGD")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival))
    (home-page
     "https://github.com/MarcinKosinski/coxphSGD/blob/master/README.md")
    (synopsis
     "Stochastic Gradient Descent log-Likelihood Estimation in Cox Proportional Hazards Model")
    (description
     "Estimate coefficients of Cox proportional hazards model using stochastic
gradient descent algorithm for batch data.")
    (license license:gpl2)))

(define-public r-coxphm
  (package
    (name "r-coxphm")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coxphm" version))
       (sha256
        (base32 "0q1vzpqh1cijv1x7n16p7mnbdspbd17h9q6lhhklrk00lcyhinbd"))))
    (properties `((upstream-name . "coxphm")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-mass))
    (home-page "https://cran.r-project.org/package=coxphm")
    (synopsis "Time-to-Event Data Analysis with Missing Survival Times")
    (description
     "Fits a pseudo Cox proprotional hazards model that allow us to analyze
time-to-event data when survival times are missing for control groups.")
    (license license:gpl2+)))

(define-public r-coxphf
  (package
    (name "r-coxphf")
    (version "1.13.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coxphf" version))
       (sha256
        (base32 "1miljwgkrzm4xpy5vbs519pzi1aycgr1n6gdd3m5w9x0fm2i7syw"))))
    (properties `((upstream-name . "coxphf")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-survival r-generics))
    (native-inputs (list gfortran))
    (home-page
     "https://cemsiis.meduniwien.ac.at/kb/wf/software/statistische-software/fccoxphf/")
    (synopsis "Cox Regression with Firth's Penalized Likelihood")
    (description
     "This package implements Firth's penalized maximum likelihood bias reduction
method for Cox regression which has been shown to provide a solution in case of
monotone likelihood (nonconvergence of likelihood function), see Heinze and
Schemper (2001) and Heinze and Dunkler (2008).  The program fits profile
penalized likelihood confidence intervals which were proved to outperform Wald
confidence intervals.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-coxmos
  (package
    (name "r-coxmos")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Coxmos" version))
       (sha256
        (base32 "052af5hx820wmvflvz4pv3jlmmwap9d0lzx9k7v1ps6cidarz0wm"))))
    (properties `((upstream-name . "Coxmos")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-svglite
                             r-survminer
                             r-survival
                             r-survcomp
                             r-scattermore
                             r-rdpack
                             r-purrr
                             r-progress
                             r-mixomics
                             r-mass
                             r-glmnet
                             r-ggrepel
                             r-ggpubr
                             r-ggplot2
                             r-future
                             r-furrr
                             r-cowplot
                             r-caret))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/BiostatOmics/Coxmos")
    (synopsis "Cox MultiBlock Survival")
    (description
     "This software package provides Cox survival analysis for high-dimensional and
multiblock datasets.  It encompasses a suite of functions dedicated from the
classical Cox regression to newest analysis, including Cox proportional hazards
model, Stepwise Cox regression, and Elastic-Net Cox regression, Sparse Partial
Least Squares Cox regression (@code{sPLS-COX}) incorporating three distinct
strategies, and two Multiblock-PLS Cox regression (MB-@code{sPLS-COX}) methods.
This tool is designed to adeptly handle high-dimensional data, and provides
tools for cross-validation, plot generation, and additional resources for
interpreting results.  While references are available within the corresponding
functions, key literature is mentioned below.  Terry M Therneau (2024)
<https://CRAN.R-project.org/package=survival>, Noah Simon et al. (2011)
<doi:10.18637/jss.v039.i05>, Philippe Bastien et al. (2005)
<doi:10.1016/j.csda.2004.02.005>, Philippe Bastien (2008)
<doi:10.1016/j.chemolab.2007.09.009>, Philippe Bastien et al. (2014)
<doi:10.1093/bioinformatics/btu660>, Kassu Mehari Beyene and Anouar El Ghouch
(2020) <doi:10.1002/sim.8671>, Florian Rohart et al. (2017)
<doi:10.1371/journal.pcbi.1005752>.")
    (license (license:fsdg-compatible "CC BY 4.0"))))

(define-public r-coxme
  (package
    (name "r-coxme")
    (version "2.2-22")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coxme" version))
       (sha256
        (base32 "09p179ks8f2s6qmgsvcyl2d3vwwrwwjmbv50c41kl9ymikm95d0v"))))
    (properties `((upstream-name . "coxme")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-nlme r-matrix r-bdsmatrix))
    (home-page "https://cran.r-project.org/package=coxme")
    (synopsis "Mixed Effects Cox Models")
    (description
     "Fit Cox proportional hazards models containing both fixed and random effects.
The random effects can have a general form, of which familial interactions (a
\"kinship\" matrix) is a particular special case.  Note that the simplest case of
a mixed effects Cox model, i.e.  a single random per-group intercept, is also
called a \"frailty\" model.  The approach is based on Ripatti and Palmgren,
Biometrics 2002.")
    (license license:lgpl2.0)))

(define-public r-coxicpen
  (package
    (name "r-coxicpen")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoxICPen" version))
       (sha256
        (base32 "0m6g4gi33y5vmpf790x38y8g8vpxvr5935lcz9vjw5kkmsjkln0g"))))
    (properties `((upstream-name . "CoxICPen")))
    (build-system r-build-system)
    (propagated-inputs (list r-foreach))
    (home-page "https://doi.org/10.1080/01621459.2018.1537922")
    (synopsis "Variable Selection for Cox's Model with Interval-Censored Data")
    (description
     "Perform variable selection for Cox regression model with interval-censored data.
 Can deal with both low-dimensional and high-dimensional data.  Case-cohort
design can be incorporated.  Two sets of covariates scenario can also be
considered.  The references are listed in the URL below.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-coxerr
  (package
    (name "r-coxerr")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coxerr" version))
       (sha256
        (base32 "1lsfd2in82i2qp5l04k8d7jm3x0lii81f3xnfpxlhlzsypf96cia"))))
    (properties `((upstream-name . "coxerr")))
    (build-system r-build-system)
    (native-inputs (list r-knitr gfortran))
    (home-page "https://cran.r-project.org/package=coxerr")
    (synopsis "Cox Regression with Dependent Error in Covariates")
    (description
     "Perform the functional modeling methods of Huang and Wang (2018)
<doi:10.1111/biom.12741> to accommodate dependent error in covariates of the
proportional hazards model.  The adopted measurement error model has minimal
assumptions on the dependence structure, and an instrumental variable is
supposed to be available.")
    (license license:gpl2+)))

(define-public r-coxed
  (package
    (name "r-coxed")
    (version "0.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coxed" version))
       (sha256
        (base32 "09jnqza8wp2palayb0vsz43qmh8470gxil1l7g3b65lmxa7wpmnh"))))
    (properties `((upstream-name . "coxed")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-survival
                             r-rms
                             r-permalgo
                             r-mgcv
                             r-mediation
                             r-gridextra
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jkropko/coxed")
    (synopsis
     "Duration-Based Quantities of Interest for the Cox Proportional Hazards Model")
    (description
     "This package provides functions for generating, simulating, and visualizing
expected durations and marginal changes in duration from the Cox proportional
hazards model as described in Kropko and Harden (2017)
<doi:10.1017/S000712341700045X> and Harden and Kropko (2018)
<doi:10.1017/psrm.2018.19>.")
    (license license:gpl2)))

(define-public r-coxbcv
  (package
    (name "r-coxbcv")
    (version "0.0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoxBcv" version))
       (sha256
        (base32 "14lrvkv983hq5fvy1p7n8y435w6yfp1iq7g50l8qy4ppaaixgwq0"))))
    (properties `((upstream-name . "CoxBcv")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-pracma))
    (home-page "https://cran.r-project.org/package=CoxBcv")
    (synopsis
     "Bias-Corrected Sandwich Variance Estimators for Marginal Cox Analysis of Cluster Randomized Trials")
    (description
     "The implementation of bias-corrected sandwich variance estimators for the
analysis of cluster randomized trials with time-to-event outcomes using the
marginal Cox model, proposed by Wang et al. (under review).")
    (license license:gpl2+)))

(define-public r-coxaipw
  (package
    (name "r-coxaipw")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoxAIPW" version))
       (sha256
        (base32 "1cdky1xx79dda48wkpwavyzn0ibqydr005cplbmam3dnsvd1byka"))))
    (properties `((upstream-name . "CoxAIPW")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-survival
                             r-ranger
                             r-randomforestsrc
                             r-pracma
                             r-polspline
                             r-gbm))
    (home-page "https://github.com/charlesluo1002/CoxAIPW")
    (synopsis
     "Doubly Robust Inference for Cox Marginal Structural Model with Informative Censoring")
    (description
     "Doubly robust estimation and inference of log hazard ratio under the Cox
marginal structural model with informative censoring.  An augmented inverse
probability weighted estimator that involves 3 working models, one for
conditional failure time T, one for conditional censoring time C and one for
propensity score.  Both models for T and C can depend on both a binary treatment
A and additional baseline covariates Z, while the propensity score model only
depends on Z. With the help of cross-fitting techniques, achieves the
rate-doubly robust property that allows the use of most machine learning or
non-parametric methods for all 3 working models, which are not permitted in
classic inverse probability weighting or doubly robust estimators.  When the
proportional hazard assumption is violated, @code{CoxAIPW} estimates a causal
estimated that is a weighted average of the time-varying log hazard ratio.
Reference: Luo, J. (2023).  Statistical Robustness - Distributed Linear
Regression, Informative Censoring, Causal Inference, and Non-Proportional
Hazards [Unpublished doctoral dissertation].  University of California San
Diego.; Luo & Xu (2022) <doi:10.48550/@code{arXiv.2206.02296>}; Rava (2021)
<https://escholarship.org/uc/item/8h1846gs>.")
    (license license:gpl3)))

(define-public r-cowsay
  (package
    (name "r-cowsay")
    (version "0.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cowsay" version))
       (sha256
        (base32 "18jr8v0c4vvwvixklcl3kggwzhq1xnpi3brdjiby48zh873b2chd"))))
    (properties `((upstream-name . "cowsay")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmsfact r-fortunes r-crayon))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/sckott/cowsay")
    (synopsis "Messages, Warnings, Strings with Ascii Animals")
    (description
     "Allows printing of character strings as messages/warnings/etc.  with ASCII
animals, including cats, cows, frogs, chickens, ghosts, and more.")
    (license license:expat)))

(define-public r-cowbell
  (package
    (name "r-cowbell")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cowbell" version))
       (sha256
        (base32 "1zz0g30zvqfk5lh09y90iq3s7x2wwbs852i3d56mfp926gxdxc2y"))))
    (properties `((upstream-name . "cowbell")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgl r-misc3d r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cowbell")
    (synopsis
     "Performs Segmented Linear Regression on Two Independent Variables")
    (description
     "This package implements a specific form of segmented linear regression with two
independent variables.  The visualization of that function looks like a quarter
segment of a cowbell giving the package its name.  The package has been
specifically constructed for the case where minimum and maximum value of the
dependent and two independent variables are known a prior, which is usually the
case when those values are derived from Likert scales.")
    (license license:gpl3)))

(define-public r-covtracer
  (package
    (name "r-covtracer")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covtracer" version))
       (sha256
        (base32 "1ndps8hmj8qpd4wl9p14ahr8n62rlgb2psvncfjmxs26p8dx90r3"))))
    (properties `((upstream-name . "covtracer")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/genentech/covtracer")
    (synopsis "Contextualizing Tests")
    (description
     "Dissects a package environment or covr coverage object in order to cross
reference tested code with the lines that are evaluated, as well as linking
those evaluated lines to the documentation that they are described within.
Connecting these three pieces of information provides a mechanism of linking
tests to documented behaviors.")
    (license license:expat)))

(define-public r-covtools
  (package
    (name "r-covtools")
    (version "0.5.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CovTools" version))
       (sha256
        (base32 "1bkqg3kzy2ahjqldcf6x55wkrmb4s6y72y9cj0jwb1fph0a1p3sm"))))
    (properties `((upstream-name . "CovTools")))
    (build-system r-build-system)
    (propagated-inputs (list r-sht
                             r-shapes
                             r-rdpack
                             r-rcpparmadillo
                             r-rcpp
                             r-pracma
                             r-mvtnorm
                             r-matrix
                             r-geigen
                             r-foreach
                             r-expm
                             r-doparallel))
    (home-page "https://github.com/kisungyou/CovTools")
    (synopsis "Statistical Tools for Covariance Analysis")
    (description
     "Covariance is of universal prevalence across various disciplines within
statistics.  We provide a rich collection of geometric and inferential tools for
convenient analysis of covariance structures, topics including distance
measures, mean covariance estimator, covariance hypothesis test for one-sample
and two-sample cases, and covariance estimation.  For an introduction to
covariance in multivariate statistical analysis, see Schervish (1987)
<doi:10.1214/ss/1177013111>.")
    (license license:gpl3+)))

(define-public r-covtestr
  (package
    (name "r-covtestr")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covTestR" version))
       (sha256
        (base32 "0j9kay8lwkhpdyg0fbfars1m58v0i58v1v5sm7m72s7kz8qh2yfs"))))
    (properties `((upstream-name . "covTestR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-rcpparmadillo r-rcpp r-purrr))
    (home-page "https://covtestr.bearstatistics.com")
    (synopsis "Covariance Matrix Tests")
    (description
     "Testing functions for Covariance Matrices.  These tests include high-dimension
homogeneity of covariance matrix testing described by Schott (2007)
<doi:10.1016/j.csda.2007.03.004> and high-dimensional one-sample tests of
covariance matrix structure described by Fisher, et al. (2010)
<doi:10.1016/j.jmva.2010.07.004>.  Covariance matrix tests use C++ to speed
performance and allow larger data sets.")
    (license license:gpl2)))

(define-public r-covsim
  (package
    (name "r-covsim")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covsim" version))
       (sha256
        (base32 "0pk6jfh7bcpqm63zdlrkz1cqdgwwkkdjlflw8yb8fq6p25bmppih"))))
    (properties `((upstream-name . "covsim")))
    (build-system r-build-system)
    (propagated-inputs (list r-tmvtnorm
                             r-rvinecopulib
                             r-pearsonds
                             r-nleqslv
                             r-matrix
                             r-mass
                             r-lavaan))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=covsim")
    (synopsis
     "VITA, IG and PLSIM Simulation for Given Covariance and Marginals")
    (description
     "Random sampling from distributions with user-specified population covariance
matrix.  Marginal information may be fully specified, for which the package
implements the VITA (VIne-To-Anything) algorithm GrÃ¸nneberg and Foldnes (2017)
<doi:10.1007/s11336-017-9569-6>.  See also GrÃ¸nneberg, Foldnes and Marcoulides
(2022) <doi:10.18637/jss.v102.i03>.  Alternatively, marginal skewness and
kurtosis may be specified, for which the package implements the IG (independent
generator) and PLSIM (piecewise linear) algorithms, see Foldnes and Olsson
(2016) <doi:10.1080/00273171.2015.1133274> and Foldnes and GrÃ¸nneberg (2021)
<doi:10.1080/10705511.2021.1949323>, respectively.")
    (license license:gpl2+)))

(define-public r-covsep
  (package
    (name "r-covsep")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covsep" version))
       (sha256
        (base32 "19dvwhl85yx9ddwxvnq5sdd534s6llcw61gckrav48hq49x1bqld"))))
    (properties `((upstream-name . "covsep")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm))
    (home-page "http://arxiv.org/abs/1505.02023")
    (synopsis
     "Tests for Determining if the Covariance Structure of 2-Dimensional Data is Separable")
    (description
     "This package provides functions for testing if the covariance structure of
2-dimensional data (e.g. samples of surfaces X_i = X_i(s,t)) is separable, i.e.
if covariance(X) = C_1 x C_2.  A complete descriptions of the implemented tests
can be found in the paper Aston, John A. D.; Pigoli, Davide; Tavakoli, Shahin.
Tests for separability in nonparametric covariance operators of random surfaces.
 Ann.  Statist.  45 (2017), no.  4, 1431--1461. <doi:10.1214/16-AOS1495>
<https://projecteuclid.org/euclid.aos/1498636862> <@code{arXiv:1505.02023>}.")
    (license license:gpl2)))

(define-public r-covsel
  (package
    (name "r-covsel")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CovSel" version))
       (sha256
        (base32 "02fsiykbg96ynqw25vfyrams7fs39xjmfhvb23zjbqb7ql6d0xdk"))))
    (properties `((upstream-name . "CovSel")))
    (build-system r-build-system)
    (propagated-inputs (list r-np r-mass r-dr))
    (home-page "https://cran.r-project.org/package=CovSel")
    (synopsis "Model-Free Covariate Selection")
    (description
     "Model-free selection of covariates under unconfoundedness for situations where
the parameter of interest is an average causal effect.  This package is based on
model-free backward elimination algorithms proposed in de Luna, Waernbaum and
Richardson (2011).  Marginal co-ordinate hypothesis testing is used in
situations where all covariates are continuous while kernel-based smoothing
appropriate for mixed data is used otherwise.")
    (license license:gpl3)))

(define-public r-covrobust
  (package
    (name "r-covrobust")
    (version "1.1-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covRobust" version))
       (sha256
        (base32 "0zcfala4l0j4w0sx5hlw40vxiypans3d7pgkxy25nj0d2m1jkvba"))))
    (properties `((upstream-name . "covRobust")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=covRobust")
    (synopsis "Robust Covariance Estimation via Nearest Neighbor Cleaning")
    (description
     "The cov.nnve() function implements robust covariance estimation by the nearest
neighbor variance estimation (NNVE) method of Wang and Raftery (2002)
<DOI:10.1198/016214502388618780>.")
    (license license:gpl2+)))

(define-public r-covregrf
  (package
    (name "r-covregrf")
    (version "2.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CovRegRF" version))
       (sha256
        (base32 "0pzcdbwj1an8fls04g7znhbfaybqdp4rsjgnsvrh8rcmphnh48c9"))))
    (properties `((upstream-name . "CovRegRF")))
    (build-system r-build-system)
    (propagated-inputs (list r-diagrammer r-data-tree r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CovRegRF")
    (synopsis "Covariance Regression with Random Forests")
    (description
     "Covariance Regression with Random Forests (@code{CovRegRF}) is a random forest
method for estimating the covariance matrix of a multivariate response given a
set of covariates.  Random forest trees are built with a new splitting rule
which is designed to maximize the distance between the sample covariance matrix
estimates of the child nodes.  The method is described in Alakus et al. (2023)
<doi:10.1186/s12859-023-05377-y>. @code{CovRegRF} uses @code{randomForestSRC}
package (Ishwaran and Kogalur, 2022)
<https://cran.r-project.org/package=@code{randomForestSRC>} by freezing at the
version 3.1.0.  The custom splitting rule feature is utilised to apply the
proposed splitting rule.  The @code{randomForestSRC} package implements
@code{OpenMP} by default, contingent upon the support provided by the target
architecture and operating system.  In this package, LAPACK and BLAS libraries
are used for matrix decompositions.")
    (license license:gpl3+)))

(define-public r-covkcd
  (package
    (name "r-covkcd")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covKCD" version))
       (sha256
        (base32 "0rbrhdrrb47gkm8nk8mmlgrr1fsk53fycl9zspgr9085xax2bf2r"))))
    (properties `((upstream-name . "covKCD")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=covKCD")
    (synopsis
     "Covariance Estimation for Matrix Data with the Kronecker-Core Decomposition")
    (description
     "Matrix-variate covariance estimation via the Kronecker-core decomposition.
Computes the Kronecker and core covariance matrices corresponding to an
arbitrary covariance matrix, and provides an empirical Bayes covariance
estimator that adaptively shrinks towards the space of separable covariance
matrices.  For details, see Hoff, @code{McCormack} and Zhang (2022)
<@code{arXiv:2207.12484>} \"Core Shrinkage Covariance Estimation for
Matrix-variate data\".")
    (license license:gpl3)))

(define-public r-covidsymptom
  (package
    (name "r-covidsymptom")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covidsymptom" version))
       (sha256
        (base32 "03whr9qnsflpa3l9lb5f5w7c26yva74jbkykjb7xj5pnhazpm985"))))
    (properties `((upstream-name . "covidsymptom")))
    (build-system r-build-system)
    (propagated-inputs (list r-usethis r-stringi))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/hugofitipaldi/covidsymptom")
    (synopsis "COVID Symptom Study Sweden Open Dataset")
    (description
     "The COVID Symptom Study is a non-commercial project that uses a free mobile app
to facilitate real-time data collection of symptoms, exposures, and risk factors
related to COVID19.  The package allows easy access to summary statistics data
from COVID Symptom Study Sweden.")
    (license license:expat)))

(define-public r-covidprobability
  (package
    (name "r-covidprobability")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covidprobability" version))
       (sha256
        (base32 "00kiwxhkbq70650azgd6ylh7w7w4h5l8l7rmr2bijlm05xn3g154"))))
    (properties `((upstream-name . "covidprobability")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/eebrown/covidprobability")
    (synopsis "Estimate the Unit-Wide Probability of COVID-19")
    (description
     "We propose a method to estimate the probability of an undetected case of
COVID-19 in a defined setting, when a given number of people have been exposed,
with a given pretest probability of having COVID-19 as a result of that
exposure.  Since we are interested in undetected COVID-19, we assume no person
has developed symptoms (which would warrant further investigation) and that
everyone was tested on a given day, and all tested negative.")
    (license license:gpl3)))

(define-public r-covidnor
  (package
    (name "r-covidnor")
    (version "2023.05.18")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covidnor" version))
       (sha256
        (base32 "1aidi1bwsp1a8iym5b6chmv95cxrafhjgzn1zaajbijlgrjdqixc"))))
    (properties `((upstream-name . "covidnor")))
    (build-system r-build-system)
    (propagated-inputs (list r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://www.csids.no/covidnor/")
    (synopsis "Public COVID-19 Data for Norway")
    (description
     "Publicly available COVID-19 data for Norway cleaned and merged into one dataset,
including PCR confirmed cases, tests, hospitalisation and vaccination.")
    (license license:expat)))

(define-public r-covidmx
  (package
    (name "r-covidmx")
    (version "0.7.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covidmx" version))
       (sha256
        (base32 "1m73pxpn080w7sby88spz2pfjw1v479m9fa74ag25mkdymfbh02d"))))
    (properties `((upstream-name . "covidmx")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-readxl
                             r-readr
                             r-rcurl
                             r-pins
                             r-fs
                             r-duckdb
                             r-dplyr
                             r-dbi
                             r-cli))
    (home-page "https://github.com/RodrigoZepeda/covidmx")
    (synopsis "Descarga y analiza datos de COVID-19 en MÃ©xico")
    (description
     "Herramientas para el anÃ¡lisis de datos de COVID-19 en MÃ©xico.  Descarga y
analiza los datos para COVID-19 de la Direccion General de EpidemiologÃ­a de
MÃ©xico (DGE) <https://www.gob.mx/salud/documentos/datos-abiertos-152127>, la
Red de Infecciones Respiratorias Agudas Graves (Red IRAG)
<https://www.gits.igg.unam.mx/red-irag-dashboard/@code{reviewHome>} y la
Iniciativa Global para compartir todos los datos de influenza (GISAID)
<https://gisaid.org/>.  English: Downloads and analyzes data of COVID-19 from
the Mexican General Directorate of Epidemiology (DGE), the Network of Severe
Acute Respiratory Infections (IRAG network),and the Global Initiative on Sharing
All Influenza Data GISAID.")
    (license license:expat)))

(define-public r-covidmutations
  (package
    (name "r-covidmutations")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CovidMutations" version))
       (sha256
        (base32 "03bl9frjfj8i7ydgi245113yzyg8rkgqxasicmqcjdd68zbz00kn"))))
    (properties `((upstream-name . "CovidMutations")))
    (build-system r-build-system)
    (propagated-inputs (list r-venndiagram
                             r-stringr
                             r-seqinr
                             r-ggpubr
                             r-ggplot2
                             r-dplyr
                             r-cowplot))
    (home-page "https://github.com/MSQ-123/CovidMutations")
    (synopsis
     "Mutation Analysis Toolkit for COVID-19 (Coronavirus Disease 2019)")
    (description
     "This package provides a feasible framework for mutation analysis and reverse
transcription polymerase chain reaction (RT-PCR) assay evaluation of COVID-19,
including mutation profile visualization, statistics and mutation ratio of each
assay.  The mutation ratio is conducive to evaluating the coverage of RT-PCR
assays in large-sized samples.  Mercatelli, D. and Giorgi, F. M. (2020)
<doi:10.20944/preprints202004.0529.v1>.")
    (license license:artistic2.0)))

(define-public r-covidibge
  (package
    (name "r-covidibge")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "COVIDIBGE" version))
       (sha256
        (base32 "1clbqpaz9awkhsglwbv84j277hh92141sla67dlzrs6j5iv4zkcs"))))
    (properties `((upstream-name . "COVIDIBGE")))
    (build-system r-build-system)
    (propagated-inputs (list r-timedate
                             r-tibble
                             r-survey
                             r-readxl
                             r-readr
                             r-rcurl
                             r-projmgr
                             r-magrittr
                             r-httr
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=COVIDIBGE")
    (synopsis "Downloading, Reading and Analyzing PNAD COVID19 Microdata")
    (description
     "This package provides tools for downloading, reading and analyzing the COVID19
National Household Sample Survey - PNAD COVID19, a household survey from
Brazilian Institute of Geography and Statistics - IBGE. The data must be
downloaded from the official website <https://www.ibge.gov.br/>.  Further
analysis must be made using package survey'.")
    (license license:gpl3)))

(define-public r-covidcast
  (package
    (name "r-covidcast")
    (version "0.5.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covidcast" version))
       (sha256
        (base32 "0d4x3cydjng0f0gzn8fly44hf2viypym6ag7mzwips7791rhcm6k"))))
    (properties `((upstream-name . "covidcast")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-tidyr
                             r-sf
                             r-rlang
                             r-purrr
                             r-mmwrweek
                             r-httr
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cmu-delphi.github.io/covidcast/covidcastR/")
    (synopsis "Client for Delphi's 'COVIDcast Epidata' API")
    (description
     "This package provides tools for Delphi's COVIDcast Epidata API: data access,
maps and time series plotting, and basic signal processing.  The API includes a
collection of numerous indicators relevant to the COVID-19 pandemic in the
United States, including official reports, de-identified aggregated medical
claims data, large-scale surveys of symptoms and public behavior, and mobility
data, typically updated daily and at the county level.  All data sources are
documented at <https://cmu-delphi.github.io/delphi-epidata/api/covidcast.html>.")
    (license license:expat)))

(define-public r-covid19us
  (package
    (name "r-covid19us")
    (version "0.1.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covid19us" version))
       (sha256
        (base32 "1vzxvrifs49v66mc85nxfmpk82hcjrr3lpw0mwy3wj7r5vxdrwh0"))))
    (properties `((upstream-name . "covid19us")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-snakecase
                             r-purrr
                             r-magrittr
                             r-lubridate
                             r-httr
                             r-glue
                             r-dplyr
                             r-curl))
    (home-page "https://cran.r-project.org/package=covid19us")
    (synopsis "Cases of COVID-19 in the United States")
    (description
     "This package provides a wrapper around the COVID Tracking Project API
<https://covidtracking.com/api/> providing data on cases of COVID-19 in the US.")
    (license license:expat)))

(define-public r-covid19tunisia
  (package
    (name "r-covid19tunisia")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covid19tunisia" version))
       (sha256
        (base32 "1qx1rrv7ak77brg80bcj8k7vn26193njda7pg93lj1x3dpfh13dm"))))
    (properties `((upstream-name . "covid19tunisia")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-readr
                             r-magrittr
                             r-lubridate
                             r-knitr
                             r-glue
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/MounaBelaid/covid19tunisia")
    (synopsis "Cases of COVID-19 in Tunisia")
    (description
     "Data personally collected about the spread of COVID-19 (SARS-COV-2) in Tunisia
<https://github.com/@code{MounaBelaid/covid19datatunisia>}.")
    (license license:expat)))

(define-public r-covid19swiss
  (package
    (name "r-covid19swiss")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covid19swiss" version))
       (sha256
        (base32 "083j4568j7yk7l4qj6097zp0ijq70ycvwvmbfqp3dwazmibamy34"))))
    (properties `((upstream-name . "covid19swiss")))
    (build-system r-build-system)
    (propagated-inputs (list r-devtools))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Covid19R/covid19swiss")
    (synopsis
     "COVID-19 Cases in Switzerland and Principality of Liechtenstein")
    (description
     "This package provides a daily summary of the Coronavirus (COVID-19) cases in
Switzerland cantons and Principality of Liechtenstein.  Data source: Specialist
Unit for Open Government Data Canton of Zurich
<https://www.zh.ch/de/politik-staat/opendata.html>.")
    (license license:expat)))

(define-public r-covid19srilanka
  (package
    (name "r-covid19srilanka")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covid19srilanka" version))
       (sha256
        (base32 "08s0c33f890i6lnwxa3gw5xf8qirj7bi1hzcs5cr2dzmfs28m5yb"))))
    (properties `((upstream-name . "covid19srilanka")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=covid19srilanka")
    (synopsis
     "The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data in Sri Lanka")
    (description
     "This package provides a daily counts of the Coronavirus (COVID19) cases by
districts and country.  Data source: Epidemiological Unit, Ministry of Health,
Sri Lanka <https://www.epid.gov.lk/web/>.")
    (license license:expat)))

(define-public r-covid19sf
  (package
    (name "r-covid19sf")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covid19sf" version))
       (sha256
        (base32 "0x89j94sg539qc7qd2n2vi8bi1lagqkdc2ss5ld7vj4l78r5zk4l"))))
    (properties `((upstream-name . "covid19sf")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf
                             r-plotly
                             r-mapview
                             r-magrittr
                             r-lubridate
                             r-dplyr
                             r-devtools))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/RamiKrispin/covid19sf")
    (synopsis "The Covid19 San Francisco Dataset")
    (description
     "This package provides a verity of summary tables of the Covid19 cases in San
Francisco.  Data source: San Francisco, Department of Public Health - Population
Health Division <https://datasf.org/opendata/>.")
    (license license:expat)))

(define-public r-covid19italy
  (package
    (name "r-covid19italy")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covid19italy" version))
       (sha256
        (base32 "1737lv9w039g5nmwh0kfk5np95ql9skqngk29nqx52zw1yxvwlnh"))))
    (properties `((upstream-name . "covid19italy")))
    (build-system r-build-system)
    (propagated-inputs (list r-devtools))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/RamiKrispin/covid19italy")
    (synopsis "The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Italy Dataset")
    (description
     "This package provides a daily summary of the Coronavirus (COVID-19) cases in
Italy by country, region and province level.  Data source: Presidenza del
Consiglio dei Ministri - Dipartimento della Protezione Civile
<https://www.protezionecivile.it/>.")
    (license license:expat)))

(define-public r-covid19india
  (package
    (name "r-covid19india")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covid19india" version))
       (sha256
        (base32 "18xjgal49rhwif07irb1ad0qvi6c2p1ya52knx0wspb56fv849z1"))))
    (properties `((upstream-name . "covid19india")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-scales
                             r-magrittr
                             r-janitor
                             r-httr
                             r-gt
                             r-glue
                             r-epiestim
                             r-data-table
                             r-cli))
    (home-page "https://github.com/maxsal/covid19india")
    (synopsis "Pulling Clean Data from Covid19india.org")
    (description
     "Pull raw and pre-cleaned versions of national and state-level COVID-19
time-series data from covid19india.org <https://www.covid19india.org>.  Easily
obtain and merge case count data, testing data, and vaccine data.  Also assists
in calculating the time-varying effective reproduction number with sensible
parameters for COVID-19.")
    (license license:expat)))

(define-public r-covid19france
  (package
    (name "r-covid19france")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covid19france" version))
       (sha256
        (base32 "11072mc794l0m84k2b08zhyfvxf6n6ym91i7kkm3cbirxp6bhnqy"))))
    (properties `((upstream-name . "covid19france")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-readr
                             r-magrittr
                             r-lubridate
                             r-glue
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=covid19france")
    (synopsis "Cases of COVID-19 in France")
    (description
     "Imports and cleans opencovid19-fr <https://github.com/opencovid19-fr/data> data
on COVID-19 in France.")
    (license license:expat)))

(define-public r-covid19dbcand
  (package
    (name "r-covid19dbcand")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covid19dbcand" version))
       (sha256
        (base32 "0864xixdxzaj697al0c2gq3nk05q1pn0pc9lc2dyki71g5r67i7h"))))
    (properties `((upstream-name . "covid19dbcand")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/MohammedFCIS/covid19dbcand")
    (synopsis
     "Selected 'Drugbank' Drugs for COVID-19 Treatment Related Data in R Format")
    (description
     "This package provides different datasets parsed from Drugbank
<https://www.drugbank.ca/covid-19> database using dbparser package.  It is a
smaller version from dbdataset package.  It contains only information about
COVID-19 possible treatment.")
    (license license:cc0)))

(define-public r-covid19brazil
  (package
    (name "r-covid19brazil")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covid19brazil" version))
       (sha256
        (base32 "014i0wnr7nn6knyz28hv9dymkr5yy2qwd2jqybzjdlfikf42baba"))))
    (properties `((upstream-name . "covid19brazil")))
    (build-system r-build-system)
    (propagated-inputs (list r-dplyr r-devtools))
    (home-page "https://github.com/alexandreloures/covid19Brazil")
    (synopsis "COVID-19 Dataset for Brazil")
    (description
     "Dataset with strategic information about COVID-19 in Brazil.  Data for
municipalities, states, region and Brazil.  Data source: Sistema Unico de Saude
- SUS.")
    (license license:expat)))

(define-public r-covid19br
  (package
    (name "r-covid19br")
    (version "0.1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covid19br" version))
       (sha256
        (base32 "1jcxwyxc2rdarniy7bqkx7m300i1i0lvqdvzvkr9synvhpgcv4b0"))))
    (properties `((upstream-name . "covid19br")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-sf
                             r-rlang
                             r-httr
                             r-dplyr
                             r-data-table
                             r-curl))
    (home-page "https://fndemarqui.github.io/covid19br/")
    (synopsis "Brazilian COVID-19 Pandemic Data")
    (description
     "Set of functions to import COVID-19 pandemic data into R. The Brazilian COVID-19
data, obtained from the official Brazilian repository at
<https://covid.saude.gov.br/>, is available at country, region, state, and
city-levels.  The package also downloads the world-level COVID-19 data from the
John Hopkins University's repository.")
    (license license:expat)))

(define-public r-covid19-analytics
  (package
    (name "r-covid19-analytics")
    (version "2.1.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covid19.analytics" version))
       (sha256
        (base32 "009cqf1xnhkw11vi1z0c0zm8ld3ifgricn0rlik5gycvz8ygwprn"))))
    (properties `((upstream-name . "covid19.analytics")))
    (build-system r-build-system)
    (propagated-inputs (list r-shinydashboard
                             r-shinycssloaders
                             r-shiny
                             r-rentrez
                             r-readxl
                             r-plotly
                             r-pheatmap
                             r-htmlwidgets
                             r-gplots
                             r-dt
                             r-dplyr
                             r-desolve
                             r-curl
                             r-collapsibletree
                             r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://mponce0.github.io/covid19.analytics/")
    (synopsis "Load and Analyze Live Data from the COVID-19 Pandemic")
    (description
     "Load and analyze updated time series worldwide data of reported cases for the
Novel Coronavirus Disease (COVID-19) from different sources, including the Johns
Hopkins University Center for Systems Science and Engineering (JHU CSSE) data
repository <https://github.com/CSSEGI@code{SandData/COVID-19>}, \"Our World in
Data\" <https://github.com/owid/> among several others.  The datasets reporting
the COVID-19 cases are available in two main modalities, as a time series
sequences and aggregated data for the last day with greater spatial resolution.
Several analysis, visualization and modelling functions are available in the
package that will allow the user to compute and visualize total number of cases,
total number of changes and growth rate globally or for an specific geographical
location, while at the same time generating models using these trends; generate
interactive visualizations and generate Susceptible-Infected-Recovered (SIR)
model for the disease spread.")
    (license license:gpl2+)))

(define-public r-covid19
  (package
    (name "r-covid19")
    (version "3.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "COVID19" version))
       (sha256
        (base32 "0idvqsqdsjm2dn7iipr0mh0xlgxfwavajxbz08wigngcaic192iy"))))
    (properties `((upstream-name . "COVID19")))
    (build-system r-build-system)
    (propagated-inputs (list r-r-utils r-data-table))
    (home-page "https://covid19datahub.io")
    (synopsis "R Interface to COVID-19 Data Hub")
    (description
     "This package provides a daily summary of COVID-19 cases, deaths, recovered,
tests, vaccinations, and hospitalizations for 230+ countries, 760+ regions, and
12000+ administrative divisions of lower level.  Includes policy measures,
mobility data, and geospatial identifiers.  Data source: COVID-19 Data Hub
<https://covid19datahub.io>.")
    (license license:expat)))

(define-public r-covglasso
  (package
    (name "r-covglasso")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covglasso" version))
       (sha256
        (base32 "1201z49w7lacf479gp7q2v5lv8vmprppj656zzi5a4yynm7x2sll"))))
    (properties `((upstream-name . "covglasso")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "https://cran.r-project.org/package=covglasso")
    (synopsis "Sparse Covariance Matrix Estimation")
    (description
     "Direct sparse covariance matrix estimation via the covariance graphical lasso by
Bien, Tibshirani (2011) <doi:10.1093/biomet/asr054> using the fast coordinate
descent algorithm of Wang (2014) <doi:10.1007/s11222-013-9385-5>.")
    (license license:gpl3)))

(define-public r-covfefe
  (package
    (name "r-covfefe")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covfefe" version))
       (sha256
        (base32 "178qc77y4bn04qad3g70wr8y4v0ggyg807w67m8wvhbcxqr8yq7c"))))
    (properties `((upstream-name . "covfefe")))
    (build-system r-build-system)
    (propagated-inputs (list r-tokenizers))
    (home-page "https://github.com/mkirch/covfefe")
    (synopsis "Covfefy Any Word, Sentence or Speech")
    (description
     "Converts any word, sentence or speech into Trump's infamous \"covfefe\" format.
Reference:
<https://www.nytimes.com/2017/05/31/us/politics/covfefe-trump-twitter.html>.
Inspiration thanks to:
<https://codegolf.stackexchange.com/questions/123685/covfefify-a-string>.")
    (license license:gpl3)))

(define-public r-cover2
  (package
    (name "r-cover2")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coveR2" version))
       (sha256
        (base32 "00jldj11f7chnvf4mv4wshr9g1yxpy24g31z4r9h4mhvhn9i304i"))))
    (properties `((upstream-name . "coveR2")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-terra
                             r-mgc
                             r-lubridate
                             r-jpeg
                             r-dplyr
                             r-autothresholdr))
    (home-page "https://cran.r-project.org/package=coveR2")
    (synopsis "Process Digital Cover Photography Images of Tree Crowns")
    (description
     "Process Digital Cover Photography images of tree canopies to get canopy
attributes like Foliage Cover and Leaf Area Index.  Detailed description of the
methods in Chianucci et al. (2022) <doi:10.1007/s00468-018-1666-3>.")
    (license license:expat)))

(define-public r-covequal
  (package
    (name "r-covequal")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covequal" version))
       (sha256
        (base32 "1qj6djqf1rnjmnaz1nryj9dc104082w258dzjjp5q18gg1ck8v0c"))))
    (properties `((upstream-name . "covequal")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmtstat r-corpcor))
    (home-page "http://github.com/turgeonmaxime/covequal")
    (synopsis "Test for Equality of Covariance Matrices")
    (description
     "Computes p-values using the largest root test using an approximation to the null
distribution by Johnstone (2008) <DOI:10.1214/08-AOS605>.")
    (license license:expat)))

(define-public r-coveffectsplot
  (package
    (name "r-coveffectsplot")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coveffectsplot" version))
       (sha256
        (base32 "0arh7i7dyz67q6lmq9hf4wws0712mmmlip62bcwrxw8aiy1mn5nz"))))
    (properties `((upstream-name . "coveffectsplot")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-ggplot2 r-egg r-data-table
                             r-colourpicker))
    (native-inputs (list r-knitr))
    (home-page "https://smouksassi.github.io/coveffectsplot/")
    (synopsis "Produce Forest Plots to Visualize Covariate Effects")
    (description
     "Produce forest plots to visualize covariate effects using either the command
line or an interactive Shiny application.")
    (license license:expat)))

(define-public r-covdepge
  (package
    (name "r-covdepge")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covdepGE" version))
       (sha256
        (base32 "0xlz01h6lnp7g9vi9s84l8cmgqvr4pql1fs0c1n51gsx4pkaz5l1"))))
    (properties `((upstream-name . "covdepGE")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2
                             r-rcpparmadillo
                             r-rcpp
                             r-mass
                             r-latex2exp
                             r-glmnet
                             r-ggplot2
                             r-foreach
                             r-doparallel))
    (home-page "https://github.com/JacobHelwig/covdepGE")
    (synopsis "Covariate Dependent Graph Estimation")
    (description
     "This package provides a covariate-dependent approach to Gaussian graphical
modeling as described in Dasgupta et al. (2022).  Employs a novel weighted
pseudo-likelihood approach to model the conditional dependence structure of data
as a continuous function of an extraneous covariate.  The main function,
@code{covdepGE::covdepGE}(), estimates a graphical representation of the
conditional dependence structure via a block mean-field variational
approximation, while several auxiliary functions (@code{inclusionCurve}(),
@code{matViz}(), and plot.@code{covdepGE}()) are included for visualizing the
resulting estimates.")
    (license license:gpl3+)))

(define-public r-covcombr
  (package
    (name "r-covcombr")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CovCombR" version))
       (sha256
        (base32 "07yd0zbvc9db2jw6xigfhxnbkxwb3gxlmywadz7fs3rva2if2ffx"))))
    (properties `((upstream-name . "CovCombR")))
    (build-system r-build-system)
    (propagated-inputs (list r-nlme r-matrix r-cholwishart))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CovCombR")
    (synopsis "Combine Partial Covariance / Relationship Matrices")
    (description
     "Combine partial covariance matrices using a Wishart-EM algorithm.  Methods are
described in the November 2019 article by Akdemir et al.
<https://www.biorxiv.org/content/10.1101/857425v1>.  It can be used to combine
partially overlapping covariance matrices from independent trials, partially
overlapping multi-view relationship data from genomic experiments, partially
overlapping Gaussian graphs described by their covariance structures.  High
dimensional covariance estimation, multi-view data integration.  high
dimensional covariance graph estimation.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-covbm
  (package
    (name "r-covbm")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covBM" version))
       (sha256
        (base32 "0ky1lhr8m4hy2ss1nr2xymf6cmj1rr8px8zsxna6bsisf5bq4j4w"))))
    (properties `((upstream-name . "covBM")))
    (build-system r-build-system)
    (propagated-inputs (list r-nlme))
    (home-page "https://cran.r-project.org/package=covBM")
    (synopsis "Brownian Motion Processes for 'nlme'-Models")
    (description
     "Allows Brownian motion, fractional Brownian motion, and integrated
Ornstein-Uhlenbeck process components to be added to linear and non-linear mixed
effects models using the structures and methods of the nlme package.")
    (license license:gpl3)))

(define-public r-covatest
  (package
    (name "r-covatest")
    (version "1.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covatest" version))
       (sha256
        (base32 "04pycgxiq3h2j70vzqac5li0iqsyg005zpqfjr9iw17y0p51jv0a"))))
    (properties `((upstream-name . "covatest")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-v8
                             r-spacetime
                             r-sp
                             r-mathjaxr
                             r-lubridate
                             r-gstat))
    (home-page "https://cran.r-project.org/package=covatest")
    (synopsis "Tests on Properties of Space-Time Covariance Functions")
    (description
     "Tests on properties of space-time covariance functions.  Tests on symmetry,
separability and for assessing different forms of non-separability are
available.  Moreover tests on some classes of covariance functions, such that
the classes of product-sum models, Gneiting models and integrated product models
have been provided.  It is the companion R package to the papers of Cappello,
C., De Iaco, S., Posa, D., 2018, Testing the type of non-separability and some
classes of space-time covariance function models <doi:10.1007/s00477-017-1472-2>
and Cappello, C., De Iaco, S., Posa, D., 2020, covatest: an R package for
selecting a class of space-time covariance functions
<doi:10.18637/jss.v094.i01>.")
    (license license:gpl2+)))

(define-public r-covafillr
  (package
    (name "r-covafillr")
    (version "0.4.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covafillr" version))
       (sha256
        (base32 "1vsay0qlqcw3l6xp18rxrkhwsadsv9rpxwpj9f4d3vlr8inkiv4h"))))
    (properties `((upstream-name . "covafillr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppeigen r-rcpp))
    (native-inputs (list pkg-config))
    (home-page "https://github.com/calbertsen/covafillr")
    (synopsis
     "Local Polynomial Regression of State Dependent Covariates in State-Space Models")
    (description
     "Facilitates local polynomial regression for state dependent covariates in
state-space models.  The functionality can also be used from C++ based model
builder tools such as Rcpp'/'inline', TMB', or JAGS'.")
    (license license:bsd-2)))

(define-public r-covadap
  (package
    (name "r-covadap")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "covadap" version))
       (sha256
        (base32 "14vpd2sm8wc16axfc22f0bfardn60s2l1vc715bf1pbwfi83dfgw"))))
    (properties `((upstream-name . "covadap")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=covadap")
    (synopsis "Implement Covariate-Adaptive Randomization")
    (description
     "Implementing seven Covariate-Adaptive Randomization to assign patients to two
treatments.  Three of these procedures can also accommodate quantitative and
mixed covariates.  Given a set of covariates, the user can generate a single
sequence of allocations or replicate the design multiple times by simulating the
patients covariate profiles.  At the end, an extensive assessment of the
performance of the randomization procedures is provided, calculating several
imbalance measures.  See Baldi Antognini A, Frieri R, Zagoraiou M and Novelli M
(2022) <doi:10.1007/s00362-022-01381-1> for details.")
    (license license:gpl3+)))

(define-public r-coursekata
  (package
    (name "r-coursekata")
    (version "0.18.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coursekata" version))
       (sha256
        (base32 "05rqbi8sxr2fgaldg8fppil43a7pdw86wxpsgizln1bgncjpyywf"))))
    (properties `((upstream-name . "coursekata")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridislite
                             r-vctrs
                             r-supernova
                             r-rlang
                             r-remotes
                             r-purrr
                             r-palmerpenguins
                             r-mosaic
                             r-metrics
                             r-lsr
                             r-glue
                             r-ggplot2
                             r-ggformula
                             r-dslabs
                             r-cli))
    (home-page "https://github.com/coursekata/coursekata-r")
    (synopsis "Packages and Functions for 'CourseKata' Courses")
    (description
     "Easily install and load all packages and functions used in @code{CourseKata}
courses.  Aid teaching with helper functions and augment generic functions to
provide cohesion between the network of packages.  Learn more about
@code{CourseKata} at <https://coursekata.org>.")
    (license license:agpl3+)))

(define-public r-countts
  (package
    (name "r-countts")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "countts" version))
       (sha256
        (base32 "11pyj5s2vyw209inapiw9pvk0s1aq3r2c1xq0dnc83sz82bxx6c4"))))
    (properties `((upstream-name . "countts")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrixstats r-mass r-ggplot2 r-fastdummies))
    (home-page "https://cran.r-project.org/package=countts")
    (synopsis "Thomson Sampling for Zero-Inflated Count Outcomes")
    (description
     "This package provides a specialized tool is designed for assessing contextual
bandit algorithms, particularly those aimed at handling overdispersed and
zero-inflated count data.  It offers a simulated testing environment that
includes various models like Poisson, Overdispersed Poisson, Zero-inflated
Poisson, and Zero-inflated Overdispersed Poisson.  The package is capable of
executing five specific algorithms: Linear Thompson sampling with log
transformation on the outcome, Thompson sampling Poisson, Thompson sampling
Negative Binomial, Thompson sampling Zero-inflated Poisson, and Thompson
sampling Zero-inflated Negative Binomial.  Additionally, it can generate regret
plots to evaluate the performance of contextual bandit algorithms.  This package
is based on the algorithms by Liu et al. (2023) <@code{arXiv:2311.14359>}.")
    (license license:gpl2+)))

(define-public r-counttransformers
  (package
    (name "r-counttransformers")
    (version "0.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "countTransformers" version))
       (sha256
        (base32 "14n2sv7wqzslrzg0ag473ljj9mvha94161p5yh2h9l1vx7xliimf"))))
    (properties `((upstream-name . "countTransformers")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-limma r-biobase))
    (home-page "https://cran.r-project.org/package=countTransformers")
    (synopsis "Transform Counts in RNA-Seq Data Analysis")
    (description
     "Provide data transformation functions to transform counts in RNA-seq data
analysis.  Please see the reference: Zhang Z, Yu D, Seo M, Hersh CP, Weiss ST,
Qiu W. (2019) <doi.org/10.1038/s41598-019-41315-w>.")
    (license license:gpl2+)))

(define-public r-counttofpkm
  (package
    (name "r-counttofpkm")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "countToFPKM" version))
       (sha256
        (base32 "0h89knii8zkbq0lw7yn3qzak30s7bifq53ga4vy6za6hqwc53x2j"))))
    (properties `((upstream-name . "countToFPKM")))
    (build-system r-build-system)
    (propagated-inputs (list r-complexheatmap r-circlize))
    (home-page "https://github.com/AAlhendi1707/countToFPKM")
    (synopsis
     "Convert Counts to Fragments per Kilobase of Transcript per Million (FPKM)")
    (description
     "This package implements the algorithm described in Trapnell,C. et al. (2010)
<doi: 10.1038/nbt.1621>.  This function takes read counts matrix of RNA-Seq
data, feature lengths which can be retrieved using @code{biomaRt} package, and
the mean fragment lengths which can be calculated using the
@code{CollectInsertSizeMetrics(Picard}) tool.  It then returns a matrix of FPKM
normalised data by library size and feature effective length.  It also provides
the user with a quick and reliable function to generate FPKM heatmap plot of the
highly variable features in RNA-Seq dataset.")
    (license license:gpl3)))

(define-public r-countstar
  (package
    (name "r-countstar")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "countSTAR" version))
       (sha256
        (base32 "054y59r7g4g33ix020m90v8g0c09db59bd9vb7461j0il3amcs99"))))
    (properties `((upstream-name . "countSTAR")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncdist
                             r-truncatednormal
                             r-splines2
                             r-spikeslabgam
                             r-rcpparmadillo
                             r-rcpp
                             r-randomforest
                             r-matrix
                             r-kfas
                             r-gbm
                             r-fastgp
                             r-dbarts
                             r-coda))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=countSTAR")
    (synopsis "Flexible Modeling of Count Data")
    (description
     "For Bayesian and classical inference and prediction with count-valued data,
Simultaneous Transformation and Rounding (STAR) Models provide a flexible,
interpretable, and easy-to-use approach.  STAR models the observed count data
using a rounded continuous data model and incorporates a transformation for
greater flexibility.  Implicitly, STAR formalizes the commonly-applied yet
incoherent procedure of (i) transforming count-valued data and subsequently (ii)
modeling the transformed data using Gaussian models.  STAR is well-defined for
count-valued data, which is reflected in predictive accuracy, and is designed to
account for zero-inflation, bounded or censored data, and over- or
underdispersion.  Importantly, STAR is easy to combine with existing MCMC or
point estimation methods for continuous data, which allows seamless adaptation
of continuous data models (such as linear regressions, additive models, BART,
random forests, and gradient boosting machines) for count-valued data.  The
package also includes several methods for modeling count time series data,
namely via warped Dynamic Linear Models.  For more details and background on
these methodologies, see the works of Kowal and Canale (2020)
<doi:10.1214/20-EJS1707>, Kowal and Wu (2022) <doi:10.1111/biom.13617>, King and
Kowal (2022) <@code{arXiv:2110.14790>}, and Kowal and Wu (2023)
<@code{arXiv:2110.12316>}.")
    (license license:gpl2+)))

(define-public r-countsplit
  (package
    (name "r-countsplit")
    (version "4.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "countsplit" version))
       (sha256
        (base32 "0b406mpf5gqspjj828qbqx6mc5ab97mh5w4pip8hb8j74q8szpcc"))))
    (properties `((upstream-name . "countsplit")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-matrix))
    (home-page "https://github.com/anna-neufeld/countsplit")
    (synopsis "Splitting a Count Matrix into Independent Folds")
    (description
     "This package implements the count splitting methodology from Neufeld et al.
(2022) <doi:10.1093/biostatistics/kxac047> and Neufeld et al. (2023)
<@code{arXiv:2307.12985>}.  Intended for turning a matrix of single-cell RNA
sequencing counts, or similar count datasets, into independent folds that can be
used for training/testing or cross validation.  Assumes that the entries in the
matrix are from a Poisson or a negative binomial distribution.")
    (license license:expat)))

(define-public r-countseppm
  (package
    (name "r-countseppm")
    (version "3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CountsEPPM" version))
       (sha256
        (base32 "19lb8m36s3ilvh9jia4b291a8wmfwvh2sb8jbpwxg7ksvj5bvcz6"))))
    (properties `((upstream-name . "CountsEPPM")))
    (build-system r-build-system)
    (propagated-inputs (list r-numderiv r-lmtest r-formula r-expm))
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=CountsEPPM")
    (synopsis "Mean and Variance Modeling of Count Data")
    (description
     "Modeling under- and over-dispersed count data using extended Poisson process
models as in the article Faddy and Smith (2011) <doi:10.18637/jss.v069.i06> .")
    (license license:gpl2)))

(define-public r-countries
  (package
    (name "r-countries")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "countries" version))
       (sha256
        (base32 "15fpw101jiw0fx2jl0ak0bq7dsy6w1iw7mvn72s24ycb3fnpwfz5"))))
    (properties `((upstream-name . "countries")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis
                             r-tidyr
                             r-stringr
                             r-stringdist
                             r-lubridate
                             r-knitr
                             r-jsonlite
                             r-httr
                             r-ggplot2
                             r-fastmatch
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://fbellelli.github.io/countries/")
    (synopsis "Deal with Country Data in an Easy Way")
    (description
     "Wrangle country data more effectively and quickly.  This package contains
functions to easily identify and convert country names, download country
information, merge country data from different sources, and make quick world
maps.")
    (license license:gpl3)))

(define-public r-countr
  (package
    (name "r-countr")
    (version "3.5.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Countr" version))
       (sha256
        (base32 "1bv19ni79f94lrn4656hsxi6nnhrn136mx5y757a4r39avsgbl06"))))
    (properties `((upstream-name . "Countr")))
    (build-system r-build-system)
    (propagated-inputs (list r-xtable
                             r-vgam
                             r-standardize
                             r-rdpack
                             r-rcpparmadillo
                             r-rcpp
                             r-rcolorbrewer
                             r-optimx
                             r-numderiv
                             r-matrix
                             r-mass
                             r-lmtest
                             r-lattice
                             r-formula
                             r-flexsurv
                             r-dplyr
                             r-car
                             r-boot))
    (native-inputs (list r-knitr))
    (home-page "https://geobosh.github.io/Countr/")
    (synopsis "Flexible Univariate Count Models Based on Renewal Processes")
    (description
     "Flexible univariate count models based on renewal processes.  The models may
include covariates and can be specified with familiar formula syntax as in glm()
and package flexsurv'.  The methodology is described by Kharrat et all (2019)
<doi:10.18637/jss.v090.i13> (included as vignette Countr_guide in the package).
If the suggested package pscl is not available from CRAN, it can be installed
with remotes::install_github(\"cran/pscl\")'.  It is no longer used by the
functions in this package but is needed for some of the extended examples.")
    (license license:gpl2+)))

(define-public r-countprop
  (package
    (name "r-countprop")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "countprop" version))
       (sha256
        (base32 "0yzrh8zr95b912p3lv0fw7vv5faylwyda0cwfvyg48j98c8hx3yf"))))
    (properties `((upstream-name . "countprop")))
    (build-system r-build-system)
    (propagated-inputs (list r-zcompositions r-glasso r-compositions))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=countprop")
    (synopsis
     "Calculate Model-Based Metrics of Proportionality on Count-Based Compositional Data")
    (description
     "Calculates metrics of proportionality using the logit-normal multinomial model.
It can also provide empirical and plugin estimates of these metrics.")
    (license license:gpl3+)))

(define-public r-countland
  (package
    (name "r-countland")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "countland" version))
       (sha256
        (base32 "1nlnri7l8v2h35r7ps8byv8mmwnir1pyimaa937wr73f1mk9m0l9"))))
    (properties `((upstream-name . "countland")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-matrix r-ggplot2))
    (home-page "https://github.com/shchurch/countland")
    (synopsis
     "Analysis of Biological Count Data, Especially from Single-Cell RNA-Seq")
    (description
     "This package provides a set of functions for applying a restricted linear
algebra to the analysis of count-based data.  See the accompanying preprint
manuscript: \"Normalizing need not be the norm: count-based math for analyzing
single-cell data\" Church et al (2022) <doi:10.1101/2022.06.01.494334> This tool
is specifically designed to analyze count matrices from single cell RNA
sequencing assays.  The tools implement several count-based approaches for
standard steps in single-cell RNA-seq analysis, including scoring genes and
cells, comparing cells and clustering, calculating differential gene expression,
and several methods for rank reduction.  There are many opportunities for
further optimization that may prove useful in the analysis of other data.  We
provide the source code freely available at
<https://github.com/shchurch/countland> and encourage users and developers to
fork the code for their own purposes.")
    (license license:expat)))

(define-public r-counthmm
  (package
    (name "r-counthmm")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "countHMM" version))
       (sha256
        (base32 "12z0nz7in2msb5wa5yyjxx19ih8psw06m7xwlapvjksslippp6gs"))))
    (properties `((upstream-name . "countHMM")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=countHMM")
    (synopsis
     "Penalized Estimation of Flexible Hidden Markov Models for Time Series of Counts")
    (description
     "This package provides tools for penalized estimation of flexible hidden Markov
models for time series of counts w/o the need to specify a (parametric) family
of distributions.  These include functions for model fitting, model checking,
and state decoding.  For details, see Adam, T., Langrock, R., and WeiÃ, C.H.
(2019): Penalized Estimation of Flexible Hidden Markov Models for Time Series of
Counts. <@code{arXiv:1901.03275>}.")
    (license license:gpl3)))

(define-public r-countgmifs
  (package
    (name "r-countgmifs")
    (version "0.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "countgmifs" version))
       (sha256
        (base32 "0k6fjg0v9n7vi89wd025gdjh1q3l6nnc5yn8i2bfw0i5vmv8rhi3"))))
    (properties `((upstream-name . "countgmifs")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=countgmifs")
    (synopsis "Discrete Response Regression for High-Dimensional Data")
    (description
     "This package provides a function for fitting Poisson and negative binomial
regression models when the number of parameters exceeds the sample size, using
the the generalized monotone incremental forward stagewise method.")
    (license license:gpl2+)))

(define-public r-countfitter
  (package
    (name "r-countfitter")
    (version "1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "countfitteR" version))
       (sha256
        (base32 "1aq7v2fy24pf3r6fkmcwvs18r2xc2l1bqablp53xfc7b6kxq3vqn"))))
    (properties `((upstream-name . "countfitteR")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-pscl r-mass r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/BioGenies/countfitteR")
    (synopsis
     "Comprehensive Automatized Evaluation of Distribution Models for Count Data")
    (description
     "This package provides a large number of measurements generate count data.  This
is a statistical data type that only assumes non-negative integer values and is
generated by counting.  Typically, counting data can be found in biomedical
applications, such as the analysis of DNA double-strand breaks.  The number of
DNA double-strand breaks can be counted in individual cells using various
bioanalytical methods.  For diagnostic applications, it is relevant to record
the distribution of the number data in order to determine their biomedical
significance (Roediger, S. et al., 2018.  Journal of Laboratory and Precision
Medicine. <doi:10.21037/jlpm.2018.04.10>).  The software offers functions for a
comprehensive automated evaluation of distribution models of count data.  In
addition to programmatic interaction, a graphical user interface (web server) is
included, which enables fast and interactive data-scientific analyses.  The user
is supported in selecting the most suitable counting distribution for his own
data set.")
    (license license:gpl3)))

(define-public r-counternull
  (package
    (name "r-counternull")
    (version "0.2.12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Counternull" version))
       (sha256
        (base32 "0kr9xaci7mdh9qgs9h1anpjv6ii2y2gpijs9kz1ywdg1iqwk8bf1"))))
    (properties `((upstream-name . "Counternull")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-randomizr r-ggplot2 r-effsize r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ymabene/Counternull")
    (synopsis "Randomization-Based Inference")
    (description
     "Randomization-Based Inference for customized experiments.  Computes Fisher-Exact
P-Values alongside null randomization distributions.  Retrieves counternull sets
and generates counternull distributions.  Computes Fisher Intervals and
Fisher-Adjusted P-Values.  Package includes visualization of randomization
distributions and Fisher Intervals.  Users can input custom test statistics and
their own methods for randomization.  Rosenthal and Rubin (1994)
<doi:10.1111/j.1467-9280.1994.tb00281.x>.")
    (license license:expat)))

(define-public r-counterfactuals
  (package
    (name "r-counterfactuals")
    (version "0.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "counterfactuals" version))
       (sha256
        (base32 "0qa6a2kp8w1na35i0qcyxpk99b4qw6si1pfvjamjz1qvr2xa8rhz"))))
    (properties `((upstream-name . "counterfactuals")))
    (build-system r-build-system)
    (propagated-inputs (list r-statmatch
                             r-r6
                             r-paradox
                             r-miesmuschel
                             r-iml
                             r-data-table
                             r-checkmate
                             r-bbotk))
    (native-inputs (list r-r-rsp))
    (home-page "https://github.com/dandls/counterfactuals")
    (synopsis "Counterfactual Explanations")
    (description
     "Modular and unified R6-based interface for counterfactual explanation methods.
The following methods are currently implemented: Burghmans et al. (2022)
<doi:10.48550/@code{arXiv.2104.07411>}, Dandl et al. (2020)
<doi:10.1007/978-3-030-58112-1_31> and Wexler et al. (2019)
<doi:10.1109/TVCG.2019.2934619>.  Optional extensions allow these methods to be
applied to a variety of models and use cases.  Once generated, the
counterfactuals can be analyzed and visualized by provided functionalities.")
    (license license:lgpl3)))

(define-public r-counterfactual
  (package
    (name "r-counterfactual")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Counterfactual" version))
       (sha256
        (base32 "1spryxvnkdz728rl4nb7zlqhynnh0b4m7lnhq4i1n13gfsz1m5j4"))))
    (properties `((upstream-name . "Counterfactual")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-quantreg
                             r-hmisc
                             r-foreach
                             r-dorng
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=Counterfactual")
    (synopsis "Estimation and Inference Methods for Counterfactual Analysis")
    (description
     "This package implements the estimation and inference methods for counterfactual
analysis described in Chernozhukov, Fernandez-Val and Melly (2013)
<DOI:10.3982/ECTA10582> \"Inference on Counterfactual Distributions,\"
Econometrica, 81(6).  The counterfactual distributions considered are the result
of changing either the marginal distribution of covariates related to the
outcome variable of interest, or the conditional distribution of the outcome
given the covariates.  They can be applied to estimate quantile treatment
effects and wage decompositions.")
    (license license:gpl2+)))

(define-public r-countdown
  (package
    (name "r-countdown")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "countdown" version))
       (sha256
        (base32 "05mnxq17z867jzi53bcvljcmpswsq9xcknddzs6k57chjl4klrwj"))))
    (properties `((upstream-name . "countdown")))
    (build-system r-build-system)
    (propagated-inputs (list r-whisker r-prismatic r-htmltools))
    (home-page "https://pkg.garrickadenbuie.com/countdown/")
    (synopsis
     "Countdown Timer for HTML Presentations, Documents, and Web Apps")
    (description
     "This package provides a simple countdown timer for slides and HTML documents
written in R Markdown or Quarto'.  Integrates fully into Shiny apps.  Countdown
to something amazing.")
    (license license:expat)))

(define-public r-countdm
  (package
    (name "r-countdm")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "countDM" version))
       (sha256
        (base32 "14mm2pmzfca7z4l8a4pfv7xjcyljrs2k0vbsakxnngn7pwvq2y9v"))))
    (properties `((upstream-name . "countDM")))
    (build-system r-build-system)
    (propagated-inputs (list r-numbers r-misctools r-maxlik r-lamw))
    (home-page "https://cran.r-project.org/package=countDM")
    (synopsis "Estimation of Count Data Models")
    (description
     "The maximum likelihood estimation (MLE) of the count data models along with
standard error of the estimates and Akaike information model section criterion
are provided.  The functions allow to compute the MLE for the following
distributions such as the Bell distribution, the Borel distribution, the Poisson
distribution, zero inflated Bell distribution, zero inflated Bell Touchard
distribution, zero inflated Poisson distribution, zero one inflated Bell
distribution and zero one inflated Poisson distribution.  Moreover, the
probability mass function (PMF), distribution function (CDF), quantile function
(QF) and random numbers generation of the Bell Touchard and zero inflated Bell
Touchard distribution are also provided.")
    (license license:gpl2+)))

(define-public r-countdata
  (package
    (name "r-countdata")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "countdata" version))
       (sha256
        (base32 "1vscm3xq8cds0zd4k8qc9di4yjslfpxl5y0glmp67ldk7mvqz0q6"))))
    (properties `((upstream-name . "countdata")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=countdata")
    (synopsis "The Beta-Binomial Test for Count Data")
    (description
     "The beta-binomial test is used for significance analysis of independent samples
by Pham et al. (2010) <doi:10.1093/bioinformatics/btp677>.  The inverted
beta-binomial test is used for paired sample testing, e.g. pre-treatment and
post-treatment data, by Pham and Jimenez (2012)
<doi:10.1093/bioinformatics/bts394>.")
    (license license:bsd-3)))

(define-public r-countcolors
  (package
    (name "r-countcolors")
    (version "0.9.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "countcolors" version))
       (sha256
        (base32 "1gnwmw3inh8asbk6qba34vzx1k2cnh4m9d1346gxhzhlxvl6xiza"))))
    (properties `((upstream-name . "countcolors")))
    (build-system r-build-system)
    (propagated-inputs (list r-png r-jpeg r-colordistance))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=countcolors")
    (synopsis "Locates and Counts Pixels Within Color Range(s) in Images")
    (description
     "Counts colors within color range(s) in images, and provides a masked version of
the image with targeted pixels changed to a different color.  Output includes
the locations of the pixels in the images, and the proportion of the image
within the target color range with optional background masking.  Users can
specify multiple color ranges for masking.")
    (license license:gpl3)))

(define-public r-count
  (package
    (name "r-count")
    (version "1.3.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "COUNT" version))
       (sha256
        (base32 "02f7779fy0d2bql88x5v9csbxljhnyvl8wb8h83xrmwl7kaxsdpy"))))
    (properties `((upstream-name . "COUNT")))
    (build-system r-build-system)
    (propagated-inputs (list r-sandwich r-msme r-mass))
    (home-page "https://cran.r-project.org/package=COUNT")
    (synopsis "Functions, Data and Code for Count Data")
    (description
     "Functions, data and code for Hilbe, J.M. 2011.  Negative Binomial Regression,
2nd Edition (Cambridge University Press) and Hilbe, J.M. 2014.  Modeling Count
Data (Cambridge University Press).")
    (license license:gpl2)))

(define-public r-cotrend
  (package
    (name "r-cotrend")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cotrend" version))
       (sha256
        (base32 "17h67vnpnlv11bf3ka5mlnah9bizxjhvicsvbygy91dqbhjhj9wb"))))
    (properties `((upstream-name . "cotrend")))
    (build-system r-build-system)
    (propagated-inputs (list r-xts))
    (home-page "https://cran.r-project.org/package=cotrend")
    (synopsis "Consistent Co-Trending Rank Selection")
    (description
     "This package implements cointegration/co-trending rank selection algorithm in
Guo and Shintani (2013) \"Consistent co-trending rank selection when both
stochastic and nonlinear deterministic trends are present\".  The Econometrics
Journal 16: 473-483 <doi:10.1111/j.1368-423X.2012.00392.x>.  Numbered examples
correspond to Feb 2011 preprint
<http://www.fas.nus.edu.sg/ecs/events/seminar/seminar-papers/05Apr11.pdf>.")
    (license license:gpl3)))

(define-public r-cotram
  (package
    (name "r-cotram")
    (version "0.5-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cotram" version))
       (sha256
        (base32 "19z3nsv1cy737mma4q1i8pr8zgnhv8pyrb2airxchbwlf4dxv2vb"))))
    (properties `((upstream-name . "cotram")))
    (build-system r-build-system)
    (propagated-inputs (list r-variables
                             r-tram
                             r-survival
                             r-qrng
                             r-mlt
                             r-matrix
                             r-basefun
                             r-alabama))
    (native-inputs (list r-knitr))
    (home-page "http://ctm.R-forge.R-project.org")
    (synopsis "Count Transformation Models")
    (description
     "Count transformation models featuring parameters interpretable as discrete
hazard ratios, odds ratios, reverse-time discrete hazard ratios, or transformed
expectations.  An appropriate data transformation for a count outcome and
regression coefficients are simultaneously estimated by maximising the exact
discrete log-likelihood using the computational framework provided in package
mlt', technical details are given in Siegfried & Hothorn (2020)
<DOI:10.1111/2041-210X.13383>.  The package also contains an experimental
implementation of multivariate count transformation models with an application
to multi-species distribution models <DOI:10.48550/@code{arXiv.2201.13095>}.")
    (license license:gpl2)))

(define-public r-cotima
  (package
    (name "r-cotima")
    (version "0.8.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoTiMA" version))
       (sha256
        (base32 "15kc15jax3z4bfwq0mf7dahwv68nq4njj5a0gwzbr1ww4rrwg1r1"))))
    (properties `((upstream-name . "CoTiMA")))
    (build-system r-build-system)
    (propagated-inputs (list r-zcurve
                             r-stringi
                             r-scholar
                             r-rpushbullet
                             r-rootsolve
                             r-psych
                             r-openxlsx
                             r-openmx
                             r-mbess
                             r-mass
                             r-lavaan
                             r-foreach
                             r-doparallel
                             r-ctsem
                             r-crayon
                             r-abind))
    (native-inputs (list r-r-rsp))
    (home-page "https://github.com/CoTiMA/CoTiMA")
    (synopsis "Continuous Time Meta-Analysis ('CoTiMA')")
    (description
     "The @code{CoTiMA} package performs meta-analyses of correlation matrices of
repeatedly measured variables taken from studies that used different time
intervals.  Different time intervals between measurement occasions impose
problems for meta-analyses because the effects (e.g. cross-lagged effects)
cannot be simply aggregated, for example, by means of common fixed or random
effects analysis.  However, continuous time math, which is applied in
@code{CoTiMA}', can be used to extrapolate or intrapolate the results from all
studies to any desired time lag.  By this, effects obtained in studies that used
different time intervals can be meta-analyzed. @code{CoTiMA} fits models to
empirical data using the structural equation model (SEM) package ctsem', the
effects specified in a SEM are related to parameters that are not directly
included in the model (i.e., continuous time parameters; together, they
represent the continuous time structural equation model, CTSEM).  Statistical
model comparisons and significance tests are then performed on the continuous
time parameter estimates. @code{CoTiMA} also allows analysis of publication bias
(Egger's test, PET-PEESE estimates, zcurve analysis etc.) and analysis of
statistical power (post hoc power, required sample sizes).  See Dormann, C.,
Guthier, C., & Cortina, J. M. (2019) <doi:10.1177/1094428119847277>.  and
Guthier, C., Dormann, C., & Voelkle, M. C. (2020) <doi:10.1037/bul0000304>.")
    (license license:gpl3)))

(define-public r-costsensitive
  (package
    (name "r-costsensitive")
    (version "0.1.2.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "costsensitive" version))
       (sha256
        (base32 "192q55123yzcjjh4047ppxa3h7gk9afqnvm1nlhzs4ccqz71g411"))))
    (properties `((upstream-name . "costsensitive")))
    (build-system r-build-system)
    (home-page "https://github.com/david-cortes/costsensitive")
    (synopsis "Cost-Sensitive Multi-Class Classification")
    (description
     "Reduction-based techniques for cost-sensitive multi-class classification, in
which each observation has a different cost for classifying it into one class,
and the goal is to predict the class with the minimum expected cost for each new
observation.  Implements Weighted All-Pairs (Beygelzimer, A., Langford, J., &
Zadrozny, B., 2008, <doi:10.1007/978-0-387-79361-0_1>), Weighted One-Vs-Rest
(Beygelzimer, A., Dani, V., Hayes, T., Langford, J., & Zadrozny, B., 2005,
<https://dl.acm.org/citation.cfm?id=1102358>) and Regression One-Vs-Rest.  Works
with arbitrary classifiers taking observation weights, or with regressors.  Also
implements cost-proportionate rejection sampling for working with classifiers
that don't accept observation weights.")
    (license license:bsd-2)))

(define-public r-costat
  (package
    (name "r-costat")
    (version "2.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "costat" version))
       (sha256
        (base32 "1h1gm1an5axgi7bf0f7dmxyxzss1859d4lv89z0q4dkk1nq29qd2"))))
    (properties `((upstream-name . "costat")))
    (build-system r-build-system)
    (propagated-inputs (list r-wavethresh))
    (home-page "https://cran.r-project.org/package=costat")
    (synopsis "Time Series Costationarity Determination")
    (description
     "This package contains functions that can determine whether a time series is
second-order stationary or not (and hence evidence for locally stationarity).
Given two non-stationary series (i.e.  locally stationary series) this package
can then discover time-varying linear combinations that are second-order
stationary.  Cardinali, A. and Nason, G.P. (2013) <doi:10.18637/jss.v055.i01>.")
    (license license:gpl2+)))

(define-public r-cost
  (package
    (name "r-cost")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "COST" version))
       (sha256
        (base32 "06xgnsccd621ihlrdmnnh14vh83q1r2bnp3iqi7vp5553b3y4l3w"))))
    (properties `((upstream-name . "COST")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-copula))
    (home-page "https://cran.r-project.org/package=COST")
    (synopsis "Copula-Based Semiparametric Models for Spatio-Temporal Data")
    (description
     "Parameter estimation, one-step ahead forecast and new location prediction
methods for spatio-temporal data.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-cosso
  (package
    (name "r-cosso")
    (version "2.1-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cosso" version))
       (sha256
        (base32 "0r0gil5fk4zp33syww40va8h964zn38v0ismw0k4xsh7c8nrr8lm"))))
    (properties `((upstream-name . "cosso")))
    (build-system r-build-system)
    (propagated-inputs (list r-rglpk r-quadprog r-glmnet))
    (home-page "https://arxiv.org/abs/math/0702659")
    (synopsis
     "Fit Regularized Nonparametric Regression Models Using COSSO Penalty")
    (description
     "The COSSO regularization method automatically estimates and selects important
function components by a soft-thresholding penalty in the context of smoothing
spline ANOVA models.  Implemented models include mean regression, quantile
regression, logistic regression and the Cox regression models.")
    (license license:gpl2+)))

(define-public r-cosmos
  (package
    (name "r-cosmos")
    (version "2.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoSMoS" version))
       (sha256
        (base32 "149mybfxaqssawp8fqhjiv3xljzflc02y4pfvavz7rklfplidqkb"))))
    (properties `((upstream-name . "CoSMoS")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma
                             r-plot3d
                             r-nloptr
                             r-mvtnorm
                             r-mba
                             r-matrixcalc
                             r-matrix
                             r-mar
                             r-ggquiver
                             r-ggplot2
                             r-directlabels
                             r-data-table
                             r-cowplot
                             r-animation))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/TycheLab/CoSMoS")
    (synopsis "Complete Stochastic Modelling Solution")
    (description
     "Makes univariate, multivariate, or random fields simulations precise and simple.
 Just select the desired time series or random fieldsâ properties and it will
do the rest. @code{CoSMoS} is based on the framework described in Papalexiou
(2018, <doi:10.1016/j.advwatres.2018.02.013>), extended for random fields in
Papalexiou and Serinaldi (2020, <doi:10.1029/2019WR026331>), and further
advanced in Papalexiou et al. (2021, <doi:10.1029/2020WR029466>) to allow
fine-scale space-time simulation of storms (or even cyclone-mimicking fields).")
    (license license:gpl3)))

(define-public r-cosmofns
  (package
    (name "r-cosmofns")
    (version "1.1-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cosmoFns" version))
       (sha256
        (base32 "0py0wmdpxk8ldq1wbwg4x1hxkjblar83x3ya30n4377d4lbc3xb7"))))
    (properties `((upstream-name . "cosmoFns")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cosmoFns")
    (synopsis "Functions for Cosmological Distances, Times, Luminosities, Etc")
    (description
     "Package encapsulates standard expressions for distances, times, luminosities,
and other quantities useful in observational cosmology, including molecular line
observations.  Currently coded for a flat universe only.")
    (license license:gpl2+)))

(define-public r-cosmicsig
  (package
    (name "r-cosmicsig")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cosmicsig" version))
       (sha256
        (base32 "1xwbfinh73rfdww58zpqmk17ixpzq5rr6cdf4zlnj25xwvj5458l"))))
    (properties `((upstream-name . "cosmicsig")))
    (build-system r-build-system)
    (home-page "https://github.com/Rozen-Lab/cosmicsig")
    (synopsis
     "Mutational Signatures from COSMIC (Catalogue of Somatic Mutations in Cancer)")
    (description
     "This package provides a data package with 2 main package variables: signature
and etiology'.  The signature variable contains the latest mutational signature
profiles released on COSMIC <https://cancer.sanger.ac.uk/signatures/> for 3
mutation types: * Single base substitutions in the context of preceding and
following bases, * Doublet base substitutions, and * Small insertions and
deletions.  The etiology variable provides the known or hypothesized causes of
signatures.  cosmicsig stands for COSMIC signatures.  Please run ?'cosmicsig for
more information.")
    (license license:gpl3)))

(define-public r-cosinor2
  (package
    (name "r-cosinor2")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cosinor2" version))
       (sha256
        (base32 "1pp0z86fflqkkllfrzx3vj98kzxjwnawr4a2d8z5q6zhq6v5qrvf"))))
    (properties `((upstream-name . "cosinor2")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-scales
                             r-purrr
                             r-matrixstats
                             r-magrittr
                             r-hmisc
                             r-ggplot2
                             r-cowplot
                             r-cosinor))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/amutak/cosinor2")
    (synopsis "Extended Tools for Cosinor Analysis of Rhythms")
    (description
     "Statistical procedures for calculating populationâmean cosinor,
nonâstationary cosinor, estimation of bestâfitting period, tests of
population rhythm differences and more.  See CornÃ©lissen, G. (2014).
<doi:10.1186/1742-4682-11-16>.")
    (license license:gpl3)))

(define-public r-cosinor
  (package
    (name "r-cosinor")
    (version "1.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cosinor" version))
       (sha256
        (base32 "0nyvzmqk0rhx10fki29hcrz014bv3r40adqd5d6rbcz66kc4sjy3"))))
    (properties `((upstream-name . "cosinor")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/sachsmc/cosinor")
    (synopsis "Tools for Estimating and Predicting the Cosinor Model")
    (description
     "This package provides a set of simple functions that transforms longitudinal
data to estimate the cosinor linear model as described in Tong (1976).  Methods
are given to summarize the mean, amplitude and acrophase, to predict the mean
annual outcome value, and to test the coefficients.")
    (license license:expat)))

(define-public r-cosimmr
  (package
    (name "r-cosimmr")
    (version "1.0.12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cosimmr" version))
       (sha256
        (base32 "1gvkzp0l8zkana78llp4r734cs12dibysh5hylafmi81byibyxyp"))))
    (properties `((upstream-name . "cosimmr")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis
                             r-reshape2
                             r-rcppdist
                             r-rcpparmadillo
                             r-rcpp
                             r-r2jags
                             r-ggplot2
                             r-ggnewscale
                             r-checkmate
                             r-bayesplot))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/emmagovan/cosimmr")
    (synopsis "Fast Fitting of Stable Isotope Mixing Models with Covariates")
    (description
     "Fast fitting of Stable Isotope Mixing Models in R. Allows for the inclusion of
covariates.  Also has built-in summary functions and plot functions which allow
for the creation of isospace plots.  Variational Bayes is used to fit these
models, methods as described in: Tran et al., (2021)
<doi:10.48550/@code{arXiv.2103.01327>}.")
    (license license:gpl2+)))

(define-public r-cosa
  (package
    (name "r-cosa")
    (version "2.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cosa" version))
       (sha256
        (base32 "15ygpaqd48xqx0h08v0nf73yzif63r2nzcznlmk0ck2ydx4n85fp"))))
    (properties `((upstream-name . "cosa")))
    (build-system r-build-system)
    (propagated-inputs (list r-nloptr r-msm))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cosa")
    (synopsis "Bound Constrained Optimal Sample Size Allocation")
    (description
     "This package implements bound constrained optimal sample size allocation
(BCOSSA) framework described in Bulus & Dong (2021)
<doi:10.1080/00220973.2019.1636197> for power analysis of multilevel regression
discontinuity designs (MRDDs) and multilevel randomized trials (MRTs) with
continuous outcomes.  Minimum detectable effect size (MDES) and power
computations for MRDDs allow polynomial functional form specification for the
score variable (with or without interaction with the treatment indicator).  See
Bulus (2021) <doi:10.1080/19345747.2021.1947425>.")
    (license license:gpl3+)))

(define-public r-corx
  (package
    (name "r-corx")
    (version "1.0.7.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corx" version))
       (sha256
        (base32 "0dyrxw90xrs1sqzniqxh8rnafcng38qrm5izwlgpfafihipx9ss8"))))
    (properties `((upstream-name . "corx")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-ppcor
                             r-moments
                             r-glue
                             r-ggpubr
                             r-ggplot2
                             r-ggcorrplot
                             r-crayon
                             r-clipr))
    (home-page "https://github.com/conig/corx")
    (synopsis "Create and Format Correlation Matrices")
    (description
     "Create correlation (or partial correlation) matrices.  Correlation matrices are
formatted with significance stars based on user preferences.  Matrices of
coefficients, p-values, and number of pairwise observations are returned.  Send
resultant formatted matrices to the clipboard to be pasted into excel and other
programs.  A plot method allows users to visualize correlation matrices created
with corx'.")
    (license license:expat)))

(define-public r-corto
  (package
    (name "r-corto")
    (version "1.2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corto" version))
       (sha256
        (base32 "1rlr96kdn59vbcsjwys3brlaa8fm0jkg331dnr6fcq1z798snkb3"))))
    (properties `((upstream-name . "corto")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmarkdown
                             r-plotrix
                             r-pbapply
                             r-knitr
                             r-gplots
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=corto")
    (synopsis "Inference of Gene Regulatory Networks")
    (description
     "We present corto (Correlation Tool), a simple package to infer gene regulatory
networks and visualize master regulators from gene expression data using DPI
(Data Processing Inequality) and bootstrapping to recover edges.  An initial
step is performed to calculate all significant edges between a list of source
nodes (centroids) and target genes.  Then all triplets containing two centroids
and one target are tested in a DPI step which removes edges.  A bootstrapping
process then calculates the robustness of the network, eventually re-adding
edges previously removed by DPI. The algorithm has been optimized to run outside
a computing cluster, using a fast correlation implementation.  The package
finally provides functions to calculate network enrichment analysis from RNA-Seq
and ATAC-Seq signatures as described in the article by Giorgi lab (2020)
<doi:10.1093/bioinformatics/btaa223>.")
    (license license:lgpl3)))

(define-public r-cortestsrd
  (package
    (name "r-cortestsrd")
    (version "1.0-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corTESTsrd" version))
       (sha256
        (base32 "0as1xnc38jm1hay2dqib6y8mas9ip1qz55d1bcnpkaxdfaydzpcw"))))
    (properties `((upstream-name . "corTESTsrd")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=corTESTsrd")
    (synopsis "Significance Testing of Rank Cross-Correlations under SRD")
    (description
     "Significance test of Spearman's Rho or Kendall's Tau between short-range
dependent random variables.")
    (license license:lgpl2.1+)))

(define-public r-cortest
  (package
    (name "r-cortest")
    (version "1.0.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corTest" version))
       (sha256
        (base32 "1gip8rxvbhrckwmjwmxbmycndg4jrl75x8qda9l35znfv9r7p0nq"))))
    (properties `((upstream-name . "corTest")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix
                             r-mass
                             r-igraph
                             r-ggplot2
                             r-clustergeneration
                             r-biobase))
    (home-page "https://cran.r-project.org/package=corTest")
    (synopsis "Robust Tests for Equal Correlation")
    (description
     "There are 6 novel robust tests for equal correlation.  They are all based on
logistic regressions.  The score statistic U is proportion to difference of two
correlations based on different types of correlation in 6 methods.  The ST1() is
based on Pearson correlation.  ST2() improved ST1() by using median absolute
deviation.  ST3() utilized type M correlation and ST4() used Spearman
correlation.  ST5() and ST6() used two different ways to combine ST3() and
ST4().  We highly recommend ST5() according to the article titled New
Statistical Methods for Constructing Robust Differential Correlation Networks to
characterize the interactions among @code{microRNAs} published in Scientific
Reports.  Please see the reference: Yu et al. (2019)
<doi:10.1038/s41598-019-40167-8>.")
    (license license:gpl2+)))

(define-public r-corset
  (package
    (name "r-corset")
    (version "0.1-5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corset" version))
       (sha256
        (base32 "0b4pa450mzig7xmzgz5q8b1492yqcvz5n4i1x74f3vf337d9c4i7"))))
    (properties `((upstream-name . "corset")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=corset")
    (synopsis "Arbitrary Bounding of Series and Time Series Objects")
    (description
     "Set of methods to constrain numerical series and time series within arbitrary
boundaries.")
    (license license:gpl3)))

(define-public r-corrviz
  (package
    (name "r-corrviz")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corrViz" version))
       (sha256
        (base32 "1blwngvvh316ndfrz2gmi6gq2w08sdckqvdsn4xpzhd4q4nbff5q"))))
    (properties `((upstream-name . "corrViz")))
    (build-system r-build-system)
    (propagated-inputs (list r-visnetwork
                             r-shiny
                             r-purrr
                             r-plotly
                             r-igraph
                             r-ggraph
                             r-ggplot2
                             r-gganimate
                             r-ggally
                             r-dendser
                             r-circlize))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=corrViz")
    (synopsis "Visualise Correlations")
    (description
     "An investigative tool designed to help users visualize correlations between
variables in their datasets.  This package aims to provide an easy and effective
way to explore and visualize these correlations, making it easier to interpret
and communicate results.")
    (license license:gpl2+)))

(define-public r-corrtoolbox
  (package
    (name "r-corrtoolbox")
    (version "1.6.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CorrToolBox" version))
       (sha256
        (base32 "1bff6vfyrgrij78l7n6dpk5g434iyr1h3qxdj7r0gvfzhw188h7p"))))
    (properties `((upstream-name . "CorrToolBox")))
    (build-system r-build-system)
    (propagated-inputs (list r-psych
                             r-mvtnorm
                             r-moments
                             r-genord
                             r-binordnonnor
                             r-binnonnor))
    (home-page "https://cran.r-project.org/package=CorrToolBox")
    (synopsis
     "Modeling Correlational Magnitude Transformations in Discretization Contexts")
    (description
     "Modeling the correlation transitions under specified distributional assumptions
within the realm of discretization in the context of the latency and threshold
concepts.  The details of the method are explained in Demirtas, H. and
Vardar-Acar, C. (2017) <DOI:10.1007/978-981-10-3307-0_4>.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-corrtable
  (package
    (name "r-corrtable")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corrtable" version))
       (sha256
        (base32 "0l1kvr62lgixzn0hl5xqzpddksw6w8iwrqg4vycbl0gsgvyhm302"))))
    (properties `((upstream-name . "corrtable")))
    (build-system r-build-system)
    (propagated-inputs (list r-hmisc))
    (home-page "https://cran.r-project.org/package=corrtable")
    (synopsis
     "Creates and Saves Out a Correlation Table with Significance Levels Indicated")
    (description
     "After using this, a publication-ready correlation table with p-values indicated
will be created.  The input can be a full data frame; any string and Boolean
terms will be dropped as part of functionality.  Correlations and p-values are
calculated using the Hmisc framework.  Output of the correlation_matrix()
function is a table of strings; this gets saved out to a .csv2 with the
save_correlation_matrix() function for easy insertion into a paper.  For more
details about the process, consult
<https://paulvanderlaken.com/2020/07/28/publication-ready-correlation-matrix-significance-r/>.")
    (license license:gpl3)))

(define-public r-corrsieve
  (package
    (name "r-corrsieve")
    (version "1.6-9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corrsieve" version))
       (sha256
        (base32 "0v8338j2x9prf3fysp4yzd6x34zjmp4yyiaar6ck1wgcfprk2dd4"))))
    (properties `((upstream-name . "corrsieve")))
    (build-system r-build-system)
    (home-page "https://github.com/campanam/rCorrSieve")
    (synopsis "Software for Summarising and Evaluating STRUCTURE Output")
    (description
     "Statistical summary of STRUCTURE output.  STRUCTURE is a K-means clustering
method for inferring population structure and assigning individuals to
populations using genetic data.  Pritchard JK, Stephens M, Donnelly PJ (2000)
<DOI:10.1093/genetics/155.2.945>.
<https://web.stanford.edu/group/pritchardlab/structure.html>.")
    (license license:gpl3+)))

(define-public r-corrr
  (package
    (name "r-corrr")
    (version "0.4.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corrr" version))
       (sha256
        (base32 "0hdas6pd6adv89wp8s5v4slv6i9agrbbn2jcnfij1l7hq01a30j5"))))
    (properties `((upstream-name . "corrr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-seriation
                             r-rlang
                             r-purrr
                             r-glue
                             r-ggrepel
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/tidymodels/corrr")
    (synopsis "Correlations in R")
    (description
     "This package provides a tool for exploring correlations.  It makes it possible
to easily perform routine tasks when exploring correlation matrices such as
ignoring the diagonal, focusing on the correlations of certain variables against
others, or rearranging and visualizing the matrix in terms of the strength of
the correlations.")
    (license license:expat)))

(define-public r-corrmixed
  (package
    (name "r-corrmixed")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CorrMixed" version))
       (sha256
        (base32 "0y91j59x19syzar17zj22i445qgig8s273f7pbw99dpxx05bbifm"))))
    (properties `((upstream-name . "CorrMixed")))
    (build-system r-build-system)
    (propagated-inputs (list r-psych r-nlme))
    (home-page "https://cran.r-project.org/package=CorrMixed")
    (synopsis
     "Estimate Correlations Between Repeatedly Measured Endpoints (E.g., Reliability) Based on Linear Mixed-Effects Models")
    (description
     "In clinical practice and research settings in medicine and the behavioral
sciences, it is often of interest to quantify the correlation of a continuous
endpoint that was repeatedly measured (e.g., test-retest correlations, ICC,
etc.).  This package allows for estimating these correlations based on
mixed-effects models.  Part of this software has been developed using funding
provided from the European Union's 7th Framework Programme for research,
technological development and demonstration under Grant Agreement no 602552.")
    (license license:gpl2+)))

(define-public r-corrmeta
  (package
    (name "r-corrmeta")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corrmeta" version))
       (sha256
        (base32 "1l6gidn63yykgwr4ghw3hd5fb18pqnn8s657hlii8w6v7fzylg66"))))
    (properties `((upstream-name . "corrmeta")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-polycor r-magrittr r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=corrmeta")
    (synopsis "Correlated Meta-Analysis")
    (description
     "This package performs Correlated Meta-Analysis ('corrmeta') across multiple OMIC
scans, accounting for hidden non-independencies between elements of the scans
due to overlapping samples, related samples, or other information.  For more
information about the method, refer to the paper Province MA. (2013)
<doi:10.1142/9789814447973_0023>.")
    (license license:expat)))

(define-public r-corrmct
  (package
    (name "r-corrmct")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corrMCT" version))
       (sha256
        (base32 "03qhvw2gcxxbv8smphd8dx5gg0zj3b50p5x5gqs3rnns1c2lqbc1"))))
    (properties `((upstream-name . "corrMCT")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-matrix r-magrittr r-glue r-dplyr))
    (home-page "https://cran.r-project.org/package=corrMCT")
    (synopsis "Correlated Weighted Hochberg")
    (description
     "Perform additional multiple testing procedure methods to p.adjust(), such as
weighted Hochberg (Tamhane, A. C., & Liu, L., 2008) <doi:10.1093/biomet/asn018>,
ICC adjusted Bonferroni method (Shi, Q., Pavey, E. S., & Carter, R. E., 2012)
<doi:10.1002/pst.1514> and a new correlation corrected weighted Hochberg for
correlated endpoints.")
    (license license:gpl3+)))

(define-public r-corrgrapher
  (package
    (name "r-corrgrapher")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corrgrapher" version))
       (sha256
        (base32 "0s10n2av6dyjz6x4wvznpcbvpp63v6k3r9whkqsg7fiy9m3d4dr9"))))
    (properties `((upstream-name . "corrgrapher")))
    (build-system r-build-system)
    (propagated-inputs (list r-visnetwork r-knitr r-ingredients r-htmltools
                             r-ggplot2))
    (home-page "https://modeloriented.github.io/corrgrapher/")
    (synopsis
     "Explore Correlations Between Variables in a Machine Learning Model")
    (description
     "When exploring data or models we often examine variables one by one.  This
analysis is incomplete if the relationship between these variables is not taken
into account.  The corrgrapher package facilitates simultaneous exploration of
the Partial Dependence Profiles and the correlation between variables in the
model.  The package corrgrapher is a part of the @code{DrWhy.AI} universe.")
    (license license:gpl2+)))

(define-public r-corrgram
  (package
    (name "r-corrgram")
    (version "1.14")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corrgram" version))
       (sha256
        (base32 "12dhvwaprdmzxxk52w8sb3cx99dmzb9yhcm01pri0vcz671p57v1"))))
    (properties `((upstream-name . "corrgram")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://kwstat.github.io/corrgram/")
    (synopsis "Plot a Correlogram")
    (description
     "Calculates correlation of variables and displays the results graphically.
Included panel functions can display points, shading, ellipses, and correlation
values with confidence intervals.  See Friendly (2002)
<doi:10.1198/000313002533>.")
    (license license:gpl3)))

(define-public r-corrfuns
  (package
    (name "r-corrfuns")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corrfuns" version))
       (sha256
        (base32 "07d15qyp7nbnr5qzvkhfrm0a7rl7asiqkv2s8q0wd4jwiml1v3lj"))))
    (properties `((upstream-name . "corrfuns")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfast))
    (home-page "https://cran.r-project.org/package=corrfuns")
    (synopsis "Correlation Coefficient Related Functions")
    (description
     "Many correlation coefficient related functions are offered, such as
correlations, partial correlations and hypothesis testing using asymptotic tests
and computer intensive methods (bootstrap and permutation).  References include
Mardia K.V., Kent J.T. and Bibby J.M. (1979). \"Multivariate Analysis\".  ISBN:
978-0124712522.  London: Academic Press.")
    (license license:gpl2+)))

(define-public r-correspondencetables
  (package
    (name "r-correspondencetables")
    (version "0.7.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "correspondenceTables" version))
       (sha256
        (base32 "1078da9m8j8ph314f6bdvdcd70rfmjdk7cscchfpq5ggyr2hkrpk"))))
    (properties `((upstream-name . "correspondenceTables")))
    (build-system r-build-system)
    (propagated-inputs (list r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/eurostat/correspondenceTables")
    (synopsis
     "Creating Correspondence Tables Between Two Statistical Classifications")
    (description
     "This package provides a candidate correspondence table between two
classifications can be created when there are correspondence tables leading from
the first classification to the second one via intermediate pivot
classifications.  The correspondence table between two statistical
classifications can be updated when one of the classifications gets updated to a
new version.")
    (license (license:fsdg-compatible "EUPL"))))

(define-public r-correlplot
  (package
    (name "r-correlplot")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Correlplot" version))
       (sha256
        (base32 "1kpan2ifpqhw6nzkx1ww6k5xwr624jysz6l6i9xg35np4xfcgrwz"))))
    (properties `((upstream-name . "Correlplot")))
    (build-system r-build-system)
    (propagated-inputs (list r-xtable
                             r-mass
                             r-lsei
                             r-ggplot2
                             r-corrplot
                             r-calibrate))
    (native-inputs (list r-knitr))
    (home-page "https://www.r-project.org")
    (synopsis "Collection of Functions for Graphing Correlation Matrices")
    (description
     "Routines for the graphical representation of correlation matrices by means of
correlograms, MDS maps and biplots obtained by PCA, PFA or WALS (weighted
alternating least squares); See Graffelman & De Leeuw (2023) <doi:
10.1080/00031305.2023.2186952>.")
    (license license:gpl2+)))

(define-public r-correlbinom
  (package
    (name "r-correlbinom")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "correlbinom" version))
       (sha256
        (base32 "1ix3ccxzr7vqblbda5awsva3h95b69v7kc6adz622bbi8r36xxcq"))))
    (properties `((upstream-name . "correlbinom")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmpfr))
    (home-page "https://cran.r-project.org/package=correlbinom")
    (synopsis "Correlated Binomial Probabilities")
    (description
     "Calculates the probabilities of k successes given n trials of a binomial random
variable with non-negative correlation across trials.  The function takes as
inputs the scalar values the level of correlation or association between trials,
the success probability, the number of trials, an optional input specifying the
number of bits of precision used in the calculation, and an optional input
specifying whether the calculation approach to be used is from Witt (2014)
<doi:10.1080/03610926.2012.725148> or from Kuk (2004)
<doi:10.1046/j.1467-9876.2003.05369.x>.  The output is a (trials+1)-dimensional
vector containing the likelihoods of 0, 1, ..., trials successes.")
    (license license:gpl3+)))

(define-public r-correlationfunnel
  (package
    (name "r-correlationfunnel")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "correlationfunnel" version))
       (sha256
        (base32 "0xil7cihqk7gzpy0q97sg5sw5z0gy7zqvx0f0bizcfks9gwp43cv"))))
    (properties `((upstream-name . "correlationfunnel")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-rstudioapi
                             r-rlang
                             r-recipes
                             r-purrr
                             r-plotly
                             r-magrittr
                             r-ggrepel
                             r-ggplot2
                             r-forcats
                             r-dplyr
                             r-crayon
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/business-science/correlationfunnel")
    (synopsis
     "Speed Up Exploratory Data Analysis (EDA) with the Correlation Funnel")
    (description
     "Speeds up exploratory data analysis (EDA) by providing a succinct workflow and
interactive visualization tools for understanding which features have
relationships to target (response).  Uses binary correlation analysis to
determine relationship.  Default correlation method is the Pearson method.  Lian
Duan, W Nick Street, Yanchi Liu, Songhua Xu, and Brook Wu (2014)
<doi:10.1145/2637484>.")
    (license license:expat)))

(define-public r-correctr
  (package
    (name "r-correctr")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "correctR" version))
       (sha256
        (base32 "1qncaynl0fs06w97wbj4704whbcjs5vjqqhb1mkj95ngwi0rp37l"))))
    (properties `((upstream-name . "correctR")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://hendersontrent.github.io/correctR/")
    (synopsis
     "Corrected Test Statistics for Comparing Machine Learning Models on Correlated Samples")
    (description
     "Calculate a set of corrected test statistics for cases when samples are not
independent, such as when classification accuracy values are obtained over
resamples or through k-fold cross-validation, as proposed by Nadeau and Bengio
(2003) <doi:10.1023/A:1024068626366> and presented in Bouckaert and Frank (2004)
<doi:10.1007/978-3-540-24775-3_3>.")
    (license license:expat)))

(define-public r-correctoverloadedpeaks
  (package
    (name "r-correctoverloadedpeaks")
    (version "1.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CorrectOverloadedPeaks" version))
       (sha256
        (base32 "00zb5wxygb95dmmn31wk6lmsljxpjypmpvwa047shysbyr4y5a4h"))))
    (properties `((upstream-name . "CorrectOverloadedPeaks")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "<doi:10.1021/acs.analchem.6b02515>")
    (synopsis "Correct Overloaded Peaks from GC-APCI-MS Data")
    (description
     "Analyzes and modifies metabolomics raw data (generated using GC-APCI-MS, Gas
Chromatography-Atmospheric Pressure Chemical Ionization-Mass Spectrometry) to
correct overloaded signals, i.e.  ion intensities exceeding detector saturation
leading to a cut-off peak.  Data in @code{xcmsRaw} format are accepted as input
and @code{mzXML} files can be processed alternatively.  Overloaded signals are
detected automatically and modified using an Gaussian or Isotopic-Ratio
approach, QC plots are generated and corrected data are stored within the
original @code{xcmsRaw} or @code{mzXML} respectively to allow further
processing.")
    (license license:gpl3)))

(define-public r-correctedfdr
  (package
    (name "r-correctedfdr")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CorrectedFDR" version))
       (sha256
        (base32 "1p0gp7m7v6nly0kr4pkjwxaa941z80nfc8ji5w0y73i79d024c2s"))))
    (properties `((upstream-name . "CorrectedFDR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CorrectedFDR")
    (synopsis "Correcting False Discovery Rates")
    (description
     "There are many estimators of false discovery rate.  In this package we compute
the Nonlocal False Discovery Rate (NFDR) and the estimators of local false
discovery rate: Corrected False discovery Rate (CFDR), Re-ranked False Discovery
rate (RFDR) and the blended estimator.  Bickel, D.R., Rahal, A. (2019)
<https://tinyurl.com/kkdc9rk8>.")
    (license license:lgpl3)))

(define-public r-correctedauc
  (package
    (name "r-correctedauc")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "correctedAUC" version))
       (sha256
        (base32 "0c2kq7asq5mp48p8niqb84wnw4q2q2985wxbrywrhsszm9p3xspb"))))
    (properties `((upstream-name . "correctedAUC")))
    (build-system r-build-system)
    (propagated-inputs (list r-mnormt r-icc))
    (home-page "https://cran.r-project.org/package=correctedAUC")
    (synopsis "Correcting AUC for Measurement Error")
    (description
     "Correcting area under ROC (AUC) for measurement error based on probit-shift
model.")
    (license license:gpl2+)))

(define-public r-corrdna
  (package
    (name "r-corrdna")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corrDNA" version))
       (sha256
        (base32 "1mfjrzpcb63ydyj1yxa0wd3vh4z0rdwsqv09w0a0l4l7mhb5jz2k"))))
    (properties `((upstream-name . "corrDNA")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm))
    (home-page "https://cran.r-project.org/package=corrDNA")
    (synopsis
     "Finding Associations in Position-Wise Aligned DNA Sequence Dataset")
    (description
     "Can be useful for finding associations among different positions in a
position-wise aligned sequence dataset.  The approach adopted for finding
associations among positions is based on the latent multivariate normal
distribution.")
    (license license:gpl2+)))

(define-public r-corrcoverage
  (package
    (name "r-corrcoverage")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corrcoverage" version))
       (sha256
        (base32 "0r5n2g341jlinwrxxwxkav9i6qsf097pmfi07aiq663b13r3864x"))))
    (properties `((upstream-name . "corrcoverage")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-matrixstats r-magrittr
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://annahutch.github.io/corrcoverage")
    (synopsis
     "Correcting the Coverage of Credible Sets from Bayesian Genetic Fine Mapping")
    (description
     "Using a computationally efficient method, the package can be used to find the
corrected coverage estimate of a credible set of putative causal variants from
Bayesian genetic fine-mapping.  The package can also be used to obtain a
corrected credible set if required; that is, the smallest set of variants
required such that the corrected coverage estimate of the resultant credible set
is within some user defined accuracy of the desired coverage.  Maller et al.
(2012) <doi:10.1038/ng.2435>, Wakefield (2009) <doi:10.1002/gepi.20359>, Fortune
and Wallace (2018) <doi:10.1093/bioinformatics/bty898>.")
    (license license:expat)))

(define-public r-corrbin
  (package
    (name "r-corrbin")
    (version "1.6.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CorrBin" version))
       (sha256
        (base32 "0dzd25a43rr22si9jpscgwglmf5s8q6gg5hch69xcbh3rarxqcd4"))))
    (properties `((upstream-name . "CorrBin")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-dirmult r-combinat r-boot))
    (home-page "https://cran.r-project.org/package=CorrBin")
    (synopsis "Nonparametrics with Clustered Binary and Multinomial Data")
    (description
     "This package implements non-parametric analyses for clustered binary and
multinomial data.  The elements of the cluster are assumed exchangeable, and
identical joint distribution (also known as marginal compatibility, or
reproducibility) is assumed for clusters of different sizes.  A trend test based
on stochastic ordering is implemented.  Szabo A, George EO. (2010)
<doi:10.1093/biomet/asp077>; George EO, Cheon K, Yuan Y, Szabo A (2016)
<doi:10.1093/biomet/asw009>.")
    (license license:gpl2+)))

(define-public r-corrarray
  (package
    (name "r-corrarray")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corrarray" version))
       (sha256
        (base32 "1hsk425xjz9p3wwvia7h78dg24qsr5r977xm2ap5z40ah1bw7bzi"))))
    (properties `((upstream-name . "corrarray")))
    (build-system r-build-system)
    (propagated-inputs (list r-hmisc))
    (home-page "https://github.com/Medicine1/corrarray")
    (synopsis "Correlation Arrays and 2-Sample Correlation Matrices")
    (description
     "The goal of corrarray is to create a multi-sample correlation array by combining
the correlation matrices of a data set stratified by a grouping variable.  For
two specified levels of the variable, corrarray displays one level's correlation
matrix in the lower triangular matrix and the other level's correlation matrix
in the upper triangular matrix.  Such an output can enable visualization of
correlations from two samples in a single correlation matrix or corrgram.")
    (license license:gpl3)))

(define-public r-corr2d
  (package
    (name "r-corr2d")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corr2D" version))
       (sha256
        (base32 "11a05rg08fb64zk3wjlid9fl32r14x0n8p030w05q82bxnynprvg"))))
    (properties `((upstream-name . "corr2D")))
    (build-system r-build-system)
    (propagated-inputs (list r-mmand r-foreach r-fields r-doparallel
                             r-colorspace))
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=corr2D")
    (synopsis "Implementation of 2D Correlation Analysis in R")
    (description
     "Implementation of two-dimensional (2D) correlation analysis based on the
Fourier-transformation approach described by Isao Noda (I. Noda (1993)
<DOI:10.1366/0003702934067694>).  Additionally there are two plot functions for
the resulting correlation matrix: The first one creates colored 2D plots, while
the second one generates 3D plots.")
    (license license:gpl3)))

(define-public r-corpustools
  (package
    (name "r-corpustools")
    (version "0.5.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corpustools" version))
       (sha256
        (base32 "154n9gxzg9cx10sxbb05df9wsr378k2qhkprqr9cyh1q5ll1pki7"))))
    (properties `((upstream-name . "corpustools")))
    (build-system r-build-system)
    (propagated-inputs (list r-wordcloud
                             r-udpipe
                             r-tokenbrowser
                             r-stringi
                             r-rsyntax
                             r-rnewsflow
                             r-rcppprogress
                             r-rcpp
                             r-r6
                             r-quanteda
                             r-pbapply
                             r-matrix
                             r-igraph
                             r-digest
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/kasperwelbers/corpustools")
    (synopsis "Managing, Querying and Analyzing Tokenized Text")
    (description
     "This package provides text analysis in R, focusing on the use of a tokenized
text format.  In this format, the positions of tokens are maintained, and each
token can be annotated (e.g., part-of-speech tags, dependency relations).
Prominent features include advanced Lucene-like querying for specific tokens or
contexts (e.g., documents, sentences), similarity statistics for words and
documents, exporting to DTM for compatibility with many text analysis packages,
and the possibility to reconstruct original text from tokens to facilitate
interpretation.")
    (license license:gpl3)))

(define-public r-corpower
  (package
    (name "r-corpower")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoRpower" version))
       (sha256
        (base32 "08chsbbl74rskinp68pwzpvnxx5lkfqf71j7ryp1cwy7199h3jyw"))))
    (properties `((upstream-name . "CoRpower")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-osdesign))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mjuraska/CoRpower")
    (synopsis
     "Power Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials")
    (description
     "Calculates power for assessment of intermediate biomarker responses as
correlates of risk in the active treatment group in clinical efficacy trials, as
described in Gilbert, Janes, and Huang, Power/Sample Size Calculations for
Assessing Correlates of Risk in Clinical Efficacy Trials (2016, Statistics in
Medicine).  The methods differ from past approaches by accounting for the level
of clinical treatment efficacy overall and in biomarker response subgroups,
which enables the correlates of risk results to be interpreted in terms of
potential correlates of efficacy/protection.  The methods also account for
inter-individual variability of the observed biomarker response that is not
biologically relevant (e.g., due to technical measurement error of the
laboratory assay used to measure the biomarker response), which is important
because power to detect a specified correlate of risk effect size is heavily
affected by the biomarker's measurement error.  The methods can be used for a
general binary clinical endpoint model with a univariate dichotomous,
trichotomous, or continuous biomarker response measured in active treatment
recipients at a fixed timepoint after randomization, with either case-cohort
Bernoulli sampling or case-control without-replacement sampling of the biomarker
(a baseline biomarker is handled as a trivial special case).  In a specified
two-group trial design, the @code{computeN}() function can initially be used for
calculating additional requisite design parameters pertaining to the target
population of active treatment recipients observed to be at risk at the
biomarker sampling timepoint.  Subsequently, the power calculation employs an
inverse probability weighted logistic regression model fitted by the tps()
function in the @code{osDesign} package.  Power results as well as the
relationship between the correlate of risk effect size and treatment efficacy
can be visualized using various plotting functions.  To link power calculations
for detecting a correlate of risk and a correlate of treatment efficacy, a
baseline immunogenicity predictor (BIP) can be simulated according to a
specified classification rule (for dichotomous or trichotomous BIPs) or
correlation with the biomarker response (for continuous BIPs), then outputted
along with biomarker response data under assignment to treatment, and clinical
endpoint data for both treatment and placebo groups.")
    (license license:gpl2)))

(define-public r-corporaexplorer
  (package
    (name "r-corporaexplorer")
    (version "0.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corporaexplorer" version))
       (sha256
        (base32 "1cr5jqdqyr22x31m1qgprdisybzg90s8fifg8c5dvvnmkv9ifp78"))))
    (properties `((upstream-name . "corporaexplorer")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-stringi
                             r-shinywidgets
                             r-shinyjs
                             r-shinydashboard
                             r-shiny
                             r-scales
                             r-rmarkdown
                             r-rlang
                             r-re2
                             r-rcolorbrewer
                             r-plyr
                             r-padr
                             r-magrittr
                             r-lubridate
                             r-ggplot2
                             r-dplyr
                             r-data-table))
    (home-page "https://kgjerde.github.io/corporaexplorer/")
    (synopsis "'Shiny' App for Exploration of Text Collections")
    (description
     "Facilitates dynamic exploration of text collections through an intuitive
graphical user interface and the power of regular expressions.  The package
contains 1) a helper function to convert a data frame to a corporaexplorerobject
and 2) a Shiny app for fast and flexible exploration of a
corporaexplorerobject'.  The package also includes demo apps with which one can
explore Jane Austen's novels and the State of the Union Addresses (data from the
janeaustenr and sotu packages respectively).")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-corpora
  (package
    (name "r-corpora")
    (version "0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corpora" version))
       (sha256
        (base32 "1l1dnnm9zvgxr7jrqrz0a9m5dwz7mra0mr3i9qxjvgrzc6n6cxw8"))))
    (properties `((upstream-name . "corpora")))
    (build-system r-build-system)
    (home-page "http://SIGIL.R-Forge.R-Project.org/")
    (synopsis "Statistics and Data Sets for Corpus Frequency Data")
    (description
     "Utility functions for the statistical analysis of corpus frequency data.  This
package is a companion to the open-source course \"Statistical Inference: A
Gentle Introduction for Computational Linguists and Similar Creatures\"
('SIGIL').")
    (license license:gpl3)))

(define-public r-corpmetrics
  (package
    (name "r-corpmetrics")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corpmetrics" version))
       (sha256
        (base32 "0v4gwd0szzyl7wqcncy5259g05fcagk2zdc6mxrqvdqlf921zn67"))))
    (properties `((upstream-name . "corpmetrics")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=corpmetrics")
    (synopsis
     "Tools for Valuation, Financial Metrics and Modeling in Corporate Finance")
    (description
     "Balance sheet and income statement metrics, investment analysis methods,
valuation methods, loan amortization schedules, and Capital Asset Pricing Model.")
    (license license:gpl2+)))

(define-public r-coronavirus
  (package
    (name "r-coronavirus")
    (version "0.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coronavirus" version))
       (sha256
        (base32 "038133msw161684bzxkwc9z4jkjnsmh13wf4nydphn0hsm961bi5"))))
    (properties `((upstream-name . "coronavirus")))
    (build-system r-build-system)
    (arguments
     (list
      #:modules '((guix build r-build-system)
                  (guix build minify-build-system)
                  (guix build utils)
                  (ice-9 match))
      #:imported-modules `(,@%r-build-system-modules (guix build
                                                      minify-build-system))
      #:phases '(modify-phases %standard-phases
                  (add-after 'unpack 'process-javascript
                    (lambda* (#:key inputs #:allow-other-keys)
                      (with-directory-excursion "inst/"
                        (for-each (match-lambda
                                    ((source . target) (minify source
                                                               #:target target)))
                                  '())))))))
    (propagated-inputs (list r-devtools))
    (native-inputs (list r-knitr esbuild))
    (home-page "https://github.com/RamiKrispin/coronavirus")
    (synopsis "The 2019 Novel Coronavirus COVID-19 (2019-nCoV) Dataset")
    (description
     "This package provides a daily summary of the Coronavirus (COVID-19) cases by
state/province.  Data source: Johns Hopkins University Center for Systems
Science and Engineering (JHU CCSE) Coronavirus
<https://systems.jhu.edu/research/public-health/ncov/>.")
    (license license:expat)))

(define-public r-coronanetr
  (package
    (name "r-coronanetr")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoronaNetR" version))
       (sha256
        (base32 "1qqlkcbwmr9g8rnsgb7dd1npd09sva11y6fy1g7l4wdvmpw07ymh"))))
    (properties `((upstream-name . "CoronaNetR")))
    (build-system r-build-system)
    (propagated-inputs (list r-readr r-r-utils r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/CoronaNetDataScience/CoronaNetR")
    (synopsis "API Access to 'CoronaNet' Data")
    (description
     "Offers access to a database on government responses to the COVID-19 pandemic.
To date, the @code{CoronaNet} dataset provides the most comprehensive and
granular documentation of such government policies in the world, capturing data
for 20 broad policy categories alongside many other dimensions, including the
initiator, target, and timing of a policy.  This package is a programmatic
front-end to up-to-date @code{CoronaNet} policy records and the @code{CoronaNet}
policy intensity index scores.  For more information, see Cheng et al. (2020)
<doi:10.1038/s41562-020-0909-7>.")
    (license license:expat)))

(define-public r-corona
  (package
    (name "r-corona")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corona" version))
       (sha256
        (base32 "1hggsmvmbim7f6bybmdhxznmqib0k2plm370mjs7dp85i564sjkm"))))
    (properties `((upstream-name . "corona")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2
                             r-qicharts2
                             r-plyr
                             r-gridextra
                             r-ggplot2
                             r-gganimate))
    (home-page "https://cran.r-project.org/package=corona")
    (synopsis "Coronavirus ('Rona') Data Exploration")
    (description
     "Manipulate and view coronavirus data and other societally relevant data at a
basic level.")
    (license license:gpl3)))

(define-public r-coroica
  (package
    (name "r-coroica")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coroICA" version))
       (sha256
        (base32 "0pcz2256liczrn2gik8b5331rgzlxjrm7rzn1ialhifkiinifnva"))))
    (properties `((upstream-name . "coroICA")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://github.com/sweichwald/coroICA-R")
    (synopsis
     "Confounding Robust Independent Component Analysis for Noisy and Grouped Data")
    (description
     "This package contains an implementation of a confounding robust independent
component analysis (ICA) for noisy and grouped data.  The main function
@code{coroICA}() performs a blind source separation, by maximizing an
independence across sources and allows to adjust for varying confounding based
on user-specified groups.  Additionally, the package contains the function
uwedge() which can be used to approximately jointly diagonalize a list of
matrices.  For more details see the project website
<https://sweichwald.de/@code{coroICA/>}.")
    (license license:agpl3)))

(define-public r-cornet
  (package
    (name "r-cornet")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cornet" version))
       (sha256
        (base32 "1lh6fszgxzyvxfqpl8fnxxhw521g5pg9ah9jwy9fsj06sa9yrp8i"))))
    (properties `((upstream-name . "cornet")))
    (build-system r-build-system)
    (propagated-inputs (list r-palasso r-glmnet))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/rauschenberger/cornet")
    (synopsis "Penalised Regression for Dichotomised Outcomes")
    (description
     "This package implements lasso and ridge regression for dichotomised outcomes
(<doi:10.1080/02664763.2023.2233057>), i.e., numerical outcomes that were
transformed to binary outcomes.  Such artificial binary outcomes indicate
whether an underlying measurement is greater than a threshold.")
    (license license:gpl3)))

(define-public r-cornerstoner
  (package
    (name "r-cornerstoner")
    (version "2.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CornerstoneR" version))
       (sha256
        (base32 "04dvryhcyi7f6bmm4067cn5vmy7kdqi3bys7ln8nnsc0kkdjxhi5"))))
    (properties `((upstream-name . "CornerstoneR")))
    (build-system r-build-system)
    (propagated-inputs (list r-vcd
                             r-spatialtools
                             r-ranger
                             r-minpack-lm
                             r-data-table
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://gitlab.com/camLine/CornerstoneR/-/issues")
    (synopsis
     "Collection of Scripts for Interface Between 'Cornerstone' and 'R'")
    (description
     "Collection of generic R scripts which enable you to use existing R routines in
Cornerstone'. .  The desktop application Cornerstone
(<https://www.camline.com/en/products/cornerstone/cornerstone-core.html>) is a
data analysis software provided by @code{camLine} that empowers engineering
teams to find solutions even faster.  The engineers incorporate intensified
hands-on statistics into their projects.  They benefit from an intuitive and
uniquely designed graphical Workmap concept: you design experiments (@code{DoE})
and explore data, analyze dependencies, and find answers you can act upon,
immediately, interactively, and without any programming. .  While Cornerstone's
interface to the statistical programming language R has been available since
version 6.0, the latest interface with R is even much more efficient.
Cornerstone release 7.1.1 allows you to integrate user defined R packages
directly into the standard Cornerstone GUI. Your engineering team stays in
Cornerstone's graphical working environment and can apply R routines,
immediately and without the need to deal with programming code.  Additionally,
your R programming team develops corresponding R packages detached from
Cornerstone in their favorite R environment. .  Learn how to use R packages in
Cornerstone 7.1.1 on @code{camLineTV} @code{YouTube} channel
(<https://www.youtube.com/watch?v=HEQHwq_@code{laXU>}) (available in German).")
    (license license:gpl3)))

(define-public r-corncob
  (package
    (name "r-corncob")
    (version "0.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corncob" version))
       (sha256
        (base32 "12ah9z9f68cw40c0hw7i53263qy0yzrpvrr4kqi7xva3d18ywn4n"))))
    (properties `((upstream-name . "corncob")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam
                             r-trust
                             r-scales
                             r-rlang
                             r-numderiv
                             r-magrittr
                             r-ggplot2
                             r-dplyr
                             r-detectseparation))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/statdivlab/corncob")
    (synopsis
     "Count Regression for Correlated Observations with the Beta-Binomial")
    (description
     "Statistical modeling for correlated count data using the beta-binomial
distribution, described in Martin et al. (2020) <doi:10.1214/19-AOAS1283>.  It
allows for both mean and overdispersion covariates.")
    (license license:gpl2+)))

(define-public r-cormid
  (package
    (name "r-cormid")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CorMID" version))
       (sha256
        (base32 "1hj5sr9ig3qaqvc0ah8bqizyjrmwn9c8lm6b9hpamfnm1m9llcy8"))))
    (properties `((upstream-name . "CorMID")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/janlisec/CorMID")
    (synopsis "Correct Mass Isotopologue Distribution Vectors")
    (description
     "In metabolic flux experiments tracer molecules (often glucose containing
labelled carbon) are incorporated in compounds measured using mass spectrometry.
 The mass isotopologue distributions of these compounds needs to be corrected
for natural abundance of labelled carbon and other effects, which are specific
on the compound and ionization technique applied.  This package provides
functions to correct such effects in gas chromatography atmospheric pressure
chemical ionization mass spectrometry analyses.")
    (license license:gpl3+)))

(define-public r-corlink
  (package
    (name "r-corlink")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corlink" version))
       (sha256
        (base32 "06n9pcvbn8y9gy0mn9c0sw05424ss8smpaw3ly6a785cmj3d9b6m"))))
    (properties `((upstream-name . "corlink")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=corlink")
    (synopsis
     "Record Linkage, Incorporating Imputation for Missing Agreement Patterns, and Modeling Correlation Patterns Between Fields")
    (description
     "This package provides a matrix of agreement patterns and counts for record pairs
is the input for the procedure.  An EM algorithm is used to impute plausible
values for missing record pairs.  A second EM algorithm, incorporating possible
correlations between per-field agreement, is used to estimate posterior
probabilities that each pair is a true match - i.e.  constitutes the same
individual.")
    (license license:cc0)))

(define-public r-corkscrew
  (package
    (name "r-corkscrew")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corkscrew" version))
       (sha256
        (base32 "1nb81r4lsrajcj3xz3f7p6xznnb38yg3rnnh44rd3kabca4d8r1s"))))
    (properties `((upstream-name . "corkscrew")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer r-igraph r-gplots r-ggplot2))
    (home-page "https://cran.r-project.org/package=corkscrew")
    (synopsis "Preprocessor for Data Modeling")
    (description
     "Includes binning categorical variables into lesser number of categories based on
t-test, converting categorical variables into continuous features using the mean
of the response variable for the respective categories, understanding the
relationship between the response variable and predictor variables using data
transformations.")
    (license license:gpl2+)))

(define-public r-corhmm
  (package
    (name "r-corhmm")
    (version "2.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corHMM" version))
       (sha256
        (base32 "1pxn5vx5pxrys5ql393bibfij1922pbm2v5vr0h5gcdjym0ndr6n"))))
    (properties `((upstream-name . "corHMM")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis
                             r-rmpfr
                             r-phytools
                             r-phangorn
                             r-numderiv
                             r-nnet
                             r-nloptr
                             r-mass
                             r-igraph
                             r-gensa
                             r-expm
                             r-corpcor
                             r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=corHMM")
    (synopsis "Hidden Markov Models of Character Evolution")
    (description
     "Fits hidden Markov models of discrete character evolution which allow different
transition rate classes on different portions of a phylogeny.  Beaulieu et al
(2013) <doi:10.1093/sysbio/syt034>.")
    (license license:gpl2+)))

(define-public r-coresim
  (package
    (name "r-coresim")
    (version "0.2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coreSim" version))
       (sha256
        (base32 "1fhlss420rhs21l9i2ag5g3j0vnrkpqdh13ca4rwfan6h35qr3sm"))))
    (properties `((upstream-name . "coreSim")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-dplyr))
    (home-page "https://cran.r-project.org/package=coreSim")
    (synopsis
     "Core Functionality for Simulating Quantities of Interest from Generalised Linear Models")
    (description
     "Core functions for simulating quantities of interest from generalised linear
models (GLM).  This package will form the backbone of a series of other packages
that improve the interpretation of GLM estimates.")
    (license license:gpl3+)))

(define-public r-corenlp
  (package
    (name "r-corenlp")
    (version "0.4-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coreNLP" version))
       (sha256
        (base32 "0i08hrkp5slwhwnz34ndl9y37km2zmmysmm9swvvzmisihjrmb2d"))))
    (properties `((upstream-name . "coreNLP")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml r-rjava))
    (home-page "https://cran.r-project.org/package=coreNLP")
    (synopsis "Wrappers Around Stanford CoreNLP Tools")
    (description
     "This package provides a minimal interface for applying annotators from the
Stanford @code{CoreNLP} java library.  Methods are provided for tasks such as
tokenisation, part of speech tagging, lemmatisation, named entity recognition,
coreference detection and sentiment analysis.")
    (license license:gpl2)))

(define-public r-coremicrobiomer
  (package
    (name "r-coremicrobiomer")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoreMicrobiomeR" version))
       (sha256
        (base32 "18zqs14j014qsmqqgn2yyf1djvr92spj46aq474jh6f8sdqvbqqz"))))
    (properties `((upstream-name . "CoreMicrobiomeR")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-srs
                             r-reshape2
                             r-plotly
                             r-ggrepel
                             r-ggplot2
                             r-fastmatch
                             r-edger))
    (home-page "https://cran.r-project.org/package=CoreMicrobiomeR")
    (synopsis "Identification of Core Microbiome")
    (description
     "The Core Microbiome refers to the group of microorganisms that are consistently
present in a particular environment, habitat, or host species.  These
microorganisms play a crucial role in the functioning and stability of that
ecosystem.  Identifying these microorganisms can contribute to the emerging
field of personalized medicine.  The @code{CoreMicrobiomeR} is designed to
facilitate the identification, statistical testing, and visualization of this
group of microorganisms.This package offers three key functions to analyze and
visualize microbial community data.  This package has been developed based on
the research papers published by Pereira et al.(2018)
<doi:10.1186/s12864-018-4637-6> and Beule L, Karlovsky P. (2020)
<doi:10.7717/peerj.9593>.")
    (license license:gpl3)))

(define-public r-corels
  (package
    (name "r-corels")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corels" version))
       (sha256
        (base32 "1ygbvhnz304y4y708ygr4x6kbwv7bfpjd5hhcrcc6lma59h7arfn"))))
    (properties `((upstream-name . "corels")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://github.com/corels/rcppcorels")
    (synopsis
     "R Binding for the 'Certifiably Optimal RulE ListS (Corels)' Learner")
    (description
     "The Certifiably Optimal @code{RulE} @code{ListS} (Corels) learner by Angelino et
al described in <@code{arXiv:1704.01701>} provides interpretable decision rules
with an optimality guarantee, and is made available to R with this package.  See
the file AUTHORS for a list of copyright holders and contributors.")
    (license license:gpl2+)))

(define-public r-corelearn
  (package
    (name "r-corelearn")
    (version "1.57.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CORElearn" version))
       (sha256
        (base32 "1kgnjl8g2njrc4xnsvz76mjzp2z93klps6k1msni1fsjbg0vvl05"))))
    (properties `((upstream-name . "CORElearn")))
    (build-system r-build-system)
    (propagated-inputs (list r-rpart-plot r-plotrix r-nnet r-cluster))
    (home-page "http://lkm.fri.uni-lj.si/rmarko/software/")
    (synopsis "Classification, Regression and Feature Evaluation")
    (description
     "This package provides a suite of machine learning algorithms written in C++ with
the R interface contains several learning techniques for classification and
regression.  Predictive models include e.g., classification and regression trees
with optional constructive induction and models in the leaves, random forests,
@code{kNN}, naive Bayes, and locally weighted regression.  All predictions
obtained with these models can be explained and visualized with the
@code{ExplainPrediction} package.  This package is especially strong in feature
evaluation where it contains several variants of Relief algorithm and many
impurity based attribute evaluation functions, e.g., Gini, information gain,
MDL, and DKM. These methods can be used for feature selection or discretization
of numeric attributes.  The @code{OrdEval} algorithm and its visualization is
used for evaluation of data sets with ordinal features and class, enabling
analysis according to the Kano model of customer satisfaction.  Several
algorithms support parallel multithreaded execution via @code{OpenMP}.  The
top-level documentation is reachable through ?CORElearn.")
    (license license:gpl3)))

(define-public r-corehunter
  (package
    (name "r-corehunter")
    (version "3.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corehunter" version))
       (sha256
        (base32 "1dx8k273jrr8pn2s1czg69si740zin8zcka0m62fip22b0dw4srp"))))
    (properties `((upstream-name . "corehunter")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (propagated-inputs (list r-rjava r-naturalsort))
    (home-page "https://cran.r-project.org/package=corehunter")
    (synopsis "Multi-Purpose Core Subset Selection")
    (description
     "Core Hunter is a tool to sample diverse, representative subsets from large
germplasm collections, with minimum redundancy.  Such so-called core collections
have applications in plant breeding and genetic resource management in general.
Core Hunter can construct cores based on genetic marker data, phenotypic traits
or precomputed distance matrices, optimizing one of many provided evaluation
measures depending on the precise purpose of the core (e.g. high diversity,
representativeness, or allelic richness).  In addition, multiple measures can be
simultaneously optimized as part of a weighted index to bring the different
perspectives closer together.  The Core Hunter library is implemented in Java 8
as an open source project (see <http://www.corehunter.org>).")
    (license license:expat)))

(define-public r-corect
  (package
    (name "r-corect")
    (version "1.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coreCT" version))
       (sha256
        (base32 "18id8vf3saj71lxr0i85s9sfhfxmk5x9bihg4m6fz3i9y1akbvq6"))))
    (properties `((upstream-name . "coreCT")))
    (build-system r-build-system)
    (propagated-inputs (list r-raster r-plyr r-oro-dicom r-igraph))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/troyhill/coreCT")
    (synopsis
     "Programmatic Analysis of Sediment Cores Using Computed Tomography Imaging")
    (description
     "Computed tomography (CT) imaging is a powerful tool for understanding the
composition of sediment cores.  This package streamlines and accelerates the
analysis of CT data generated in the context of environmental science.  Included
are tools for processing raw DICOM images to characterize sediment composition
(sand, peat, etc.).  Root analyses are also enabled, including measures of
external surface area and volumes for user-defined root size classes.  For a
detailed description of the application of computed tomography imaging for
sediment characterization, see: Davey, E., C. Wigand, R. Johnson, K. Sundberg,
J. Morris, and C. Roman. (2011) <DOI: 10.1890/10-2037.1>.")
    (license license:gpl3)))

(define-public r-corecollection
  (package
    (name "r-corecollection")
    (version "0.9.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coreCollection" version))
       (sha256
        (base32 "1r5x5j91k0zfa2krcd0v2hsifv8a3f7czv6yb7zi7qx5wqak5kk9"))))
    (properties `((upstream-name . "coreCollection")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-r6))
    (home-page "https://cran.r-project.org/package=coreCollection")
    (synopsis "Core Collection")
    (description
     "Create a custom sized Core Collection based on a distance matrix and applying
the A-NE (accession nearest entry), E-NE (entry nearest entry) or E-E (entry
entry) method as introduced in Jansen and van Hintum (2007)
<doi:10.1007/s00122-006-0433-9> and further elaborated on in Odong, T.L. (2012)
<https://edepot.wur.nl/212422>.  Optionally a list of preselected accessions to
be included into the core can be set.  For each accession in the computed core,
if available nearby accessions are retrievable that can be used as an
alternative.")
    (license license:gpl2+)))

(define-public r-core
  (package
    (name "r-core")
    (version "3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CORE" version))
       (sha256
        (base32 "10y404xkd4pqlh9w5hcx6laxpqy0831v61nacih094m0q6af9brl"))))
    (properties `((upstream-name . "CORE")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CORE")
    (synopsis "Cores of Recurrent Events")
    (description
     "Given a collection of intervals with integer start and end positions, find
recurrently targeted regions and estimate the significance of finding.
Randomization is implemented by parallel methods, either using local host
machines, or submitting grid engine jobs.")
    (license license:gpl2)))

(define-public r-cordillera
  (package
    (name "r-cordillera")
    (version "1.0-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cordillera" version))
       (sha256
        (base32 "0fr08yzag8a866939bx3l9lqi98kvj3vi7llax1m39nlsr0ihrdk"))))
    (properties `((upstream-name . "cordillera")))
    (build-system r-build-system)
    (propagated-inputs (list r-dbscan))
    (native-inputs (list r-r-rsp))
    (home-page "https://r-forge.r-project.org/projects/stops/")
    (synopsis "Calculation of the OPTICS Cordillera")
    (description
     "This package provides functions for calculating the OPTICS Cordillera.  The
OPTICS Cordillera measures the amount of clusteredness in a numeric data matrix
within a distance-density based framework for a given minimum number of points
comprising a cluster, as described in Rusch, Hornik, Mair (2018)
<doi:10.1080/10618600.2017.1349664>.  We provide an R native version with
methods for printing, summarizing, and plotting the result.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-cord
  (package
    (name "r-cord")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cord" version))
       (sha256
        (base32 "18xj6cwmx1a7p3vqx5img8qf8s75nc6pcv78v15j081pgn786ma5"))))
    (properties `((upstream-name . "cord")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "https://cran.r-project.org/package=cord")
    (synopsis "Community Estimation in G-Models via CORD")
    (description
     "Partition data points (variables) into communities/clusters, similar to
clustering algorithms, such as k-means and hierarchical clustering.  This
package implements a clustering algorithm based on a new metric CORD, defined
for high dimensional parametric or semi-parametric distributions.  Read
http://arxiv.org/abs/1508.01939 for more details.")
    (license license:gpl3)))

(define-public r-corclass
  (package
    (name "r-corclass")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corclass" version))
       (sha256
        (base32 "09g8pvxw7pb1bxz3pviqgarfa41cqfc5k0ablli7sy5iq7jn8alh"))))
    (properties `((upstream-name . "corclass")))
    (build-system r-build-system)
    (propagated-inputs (list r-igraph))
    (home-page "https://cran.r-project.org/package=corclass")
    (synopsis "Correlational Class Analysis")
    (description
     "Perform a correlational class analysis of the data, resulting in a partition of
the data into separate modules.")
    (license license:gpl2)))

(define-public r-corbouli
  (package
    (name "r-corbouli")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corbouli" version))
       (sha256
        (base32 "1r9fvbc1r65rsw96pxhlixm0c0k2r265yf85skdz99kmr09l4adx"))))
    (properties `((upstream-name . "corbouli")))
    (build-system r-build-system)
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://github.com/cadam00/corbouli")
    (synopsis "Corbae-Ouliaris Frequency Domain Filtering")
    (description
     "Corbae-Ouliaris frequency domain filtering.  According to Corbae and Ouliaris
(2006) <doi:10.1017/CBO9781139164863.008>, this is a solution for extracting
cycles from time series, like business cycles etc.  when filtering.  This method
is valid for both stationary and non-stationary time series.")
    (license license:gpl3)))

(define-public r-corbin
  (package
    (name "r-corbin")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CorBin" version))
       (sha256
        (base32 "0mjvhj9cw21xjg96fz5bcyfxgwdw367l1942a38by77ylypdfq3y"))))
    (properties `((upstream-name . "CorBin")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CorBin")
    (synopsis
     "Generate High-Dimensional Binary Data with Correlation Structures")
    (description
     "We design algorithms with linear time complexity with respect to the dimension
for three commonly studied correlation structures, including exchangeable,
decaying-product and K-dependent correlation structures, and extend the
algorithms to generate binary data of general non-negative correlation matrices
with quadratic time complexity.  Jiang, W., Song, S., Hou, L. and Zhao, H. \"A
set of efficient methods to generate high-dimensional binary data with specified
correlation structures.\" The American Statistician.  See
<doi:10.1080/00031305.2020.1816213> for a detailed presentation of the method.")
    (license license:gpl3)))

(define-public r-corbi
  (package
    (name "r-corbi")
    (version "0.6-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Corbi" version))
       (sha256
        (base32 "13lbh6fcfrpgz459mjdnfkd8kys2350s8j0vv9ps18092264gh42"))))
    (properties `((upstream-name . "Corbi")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-mass r-igraph r-crf))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/wulingyun/Corbi")
    (synopsis "Collection of Rudimentary Bioinformatics Tools")
    (description
     "This package provides a bundle of basic and fundamental bioinformatics tools,
such as network querying and alignment, subnetwork extraction and search,
network biomarker identification.")
    (license license:gpl2+)))

(define-public r-corazon
  (package
    (name "r-corazon")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "corazon" version))
       (sha256
        (base32 "1advzmbmnpq18ym2k8rcxhsdzfscl68jss8wbqcir68951x2aqi3"))))
    (properties `((upstream-name . "corazon")))
    (build-system r-build-system)
    (propagated-inputs (list r-htmltools))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/feddelegrand7/corazon")
    (synopsis "Apply 'colorffy' Color Gradients Within 'shiny' Elements")
    (description
     "Allows the user to apply nice color gradients to shiny elements.  The gradients
are extracted from the colorffy website.  See
<https://www.colorffy.com/gradients/catalog>.")
    (license license:expat)))

(define-public r-coranking
  (package
    (name "r-coranking")
    (version "0.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coRanking" version))
       (sha256
        (base32 "1pl44pk6z1zri3lwp6cqhphvxnm02dbmijgfnwp2919jahgk48gc"))))
    (properties `((upstream-name . "coRanking")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://coranking.guido-kraemer.com/")
    (synopsis "Co-Ranking Matrix")
    (description
     "Calculates the co-ranking matrix to assess the quality of a dimensionality
reduction.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-cora
  (package
    (name "r-cora")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cora" version))
       (sha256
        (base32 "0mx7dn05js8hqr3xgrbp2kv25y6qjlm86y6asy17hwbbvbsmama9"))))
    (properties `((upstream-name . "cora")))
    (build-system r-build-system)
    (home-page "https://github.com/resteorts/cora")
    (synopsis "Cora Data for Entity Resolution")
    (description
     "Duplicated publication data (pre-processed and formatted) for entity resolution.
 This data set contains a total of 1879 records.  The following variables are
included in the data set: id, title, book title, authors, address, date, year,
editor, journal, volume, pages, publisher, institution, type, tech, note.  The
data set has a respective gold data set that provides information on which
records match based on id.")
    (license license:cc0)))

(define-public r-cor
  (package
    (name "r-cor")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "COR" version))
       (sha256
        (base32 "0flir1mwqqs418hwcwdg72a1r89hamf6zd8jaf8g7hm4lp3i1cgf"))))
    (properties `((upstream-name . "COR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=COR")
    (synopsis "The COR for Optimal Subset Selection in Distributed Estimation")
    (description
     "An algorithm of optimal subset selection, related to Covariance matrices,
Observation matrices and Response vectors (COR) to select the optimal subsets in
distributed estimation.  The philosophy of the package is described in Guo G.
(2020) <doi:10.1080/02331888.2020.1823979>.")
    (license license:expat)))

(define-public r-copyseparator
  (package
    (name "r-copyseparator")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "copyseparator" version))
       (sha256
        (base32 "0dywnrqjb6x7v8icx117vsjb6zzb0brmmz1xwdc8a26lgcqmbvgv"))))
    (properties `((upstream-name . "copyseparator")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-seqinr
                             r-kmer
                             r-foreach
                             r-doparallel
                             r-decipher
                             r-biostrings
                             r-beepr
                             r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/LeiYang-Fish/copyseparator")
    (synopsis "Assembling Long Gene Copies from Short Read Data")
    (description
     "Assembles two or more gene copies from short-read Next-Generation Sequencing
data.  Works best when there are only two gene copies and read length >=250 base
pairs.  High and relatively even coverage are important.")
    (license license:gpl2)))

(define-public r-copulasim
  (package
    (name "r-copulasim")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "copulaSim" version))
       (sha256
        (base32 "12mnh0gpxz046kywki9jr6gj574kfwcs1gczzr7zfkvkm5qgga65"))))
    (properties `((upstream-name . "copulaSim")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-rlang r-mvtnorm r-magrittr r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/psyen0824/copulaSim")
    (synopsis "Virtual Patient Simulation by Copula Invariance Property")
    (description
     "To optimize clinical trial designs and data analysis methods consistently
through trial simulation, we need to simulate multivariate mixed-type virtual
patient data independent of designs and analysis methods under evaluation.  To
make the outcome of optimization more realistic, relevant empirical patient
level data should be utilized when itâs available.  However, a few problems
arise in simulating trials based on small empirical data, where the underlying
marginal distributions and their dependence structure cannot be understood or
verified thoroughly due to the limited sample size.  To resolve this issue, we
use the copula invariance property, which can generate the joint distribution
without making a strong parametric assumption.  The function copula.sim can
generate virtual patient data with optional data validation methods that are
based on energy distance and ball divergence measurement.  The function
compare.copula.sim can conduct comparison of marginal mean and covariance of
simulated data.  To simulate patient-level data from a hypothetical treatment
arm that would perform differently from the observed data, the function
new.arm.copula.sim can be used to generate new multivariate data with the same
dependence structure of the original data but with a shifted mean vector.")
    (license license:expat)))

(define-public r-copularemada
  (package
    (name "r-copularemada")
    (version "1.7.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CopulaREMADA" version))
       (sha256
        (base32 "1kfw3q3i5nzha6bn74m3xvbv67d24w0m43mhad402wdcyx6rvh8v"))))
    (properties `((upstream-name . "CopulaREMADA")))
    (build-system r-build-system)
    (propagated-inputs (list r-tensor r-statmod r-mc2d r-matlab))
    (home-page "https://cran.r-project.org/package=CopulaREMADA")
    (synopsis
     "Copula Mixed Models for Multivariate Meta-Analysis of Diagnostic Test Accuracy Studies")
    (description
     "The bivariate copula mixed model for meta-analysis of diagnostic test accuracy
studies in Nikoloulopoulos (2015) <doi:10.1002/sim.6595> and Nikoloulopoulos
(2018) <doi:10.1007/s10182-017-0299-y>.  The vine copula mixed model for
meta-analysis of diagnostic test accuracy studies accounting for disease
prevalence in Nikoloulopoulos (2017) <doi:10.1177/0962280215596769> and also
accounting for non-evaluable subjects in Nikoloulopoulos (2020)
<doi:10.1515/ijb-2019-0107>.  The hybrid vine copula mixed model for
meta-analysis of diagnostic test accuracy case-control and cohort studies in
Nikoloulopoulos (2018) <doi:10.1177/0962280216682376>.  The D-vine copula mixed
model for meta-analysis and comparison of two diagnostic tests in
Nikoloulopoulos (2019) <doi:10.1177/0962280218796685>.  The multinomial
quadrivariate D-vine copula mixed model for meta-analysis of diagnostic tests
with non-evaluable subjects in Nikoloulopoulos (2020)
<doi:10.1177/0962280220913898>.  The one-factor copula mixed model for joint
meta-analysis of multiple diagnostic tests in Nikoloulopoulos (2022)
<doi:10.1111/rssa.12838>.  The multinomial six-variate 1-truncated D-vine copula
mixed model for meta-analysis of two diagnostic tests accounting for within and
between studies dependence in Nikoloulopoulos (2024)
<doi:10.1177/09622802241269645>.  The 1-truncated D-vine copula mixed models for
meta-analysis of diagnostic accuracy studies without a gold standard
(Nikoloulopoulos, 2024).")
    (license (license:fsdg-compatible "GPL (>= 3.5.0)"))))

(define-public r-copulareg
  (package
    (name "r-copulareg")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "copulareg" version))
       (sha256
        (base32 "0wn40rvh2dg60h45qbzy7nwcy2rhrnxf1rykl1ycs75mrimaayn9"))))
    (properties `((upstream-name . "copulareg")))
    (build-system r-build-system)
    (propagated-inputs (list r-rvinecopulib))
    (home-page "https://cran.r-project.org/package=copulareg")
    (synopsis "Copula Regression")
    (description
     "Fits multivariate models in an R-vine pair copula construction framework, in
such a way that the conditional copula can be easily evaluated.  In addition,
the package implements functionality to compute or approximate the conditional
expectation via the conditional copula.")
    (license (license:fsdg-compatible "MIT + file LICENCE"))))

(define-public r-copulainference
  (package
    (name "r-copulainference")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CopulaInference" version))
       (sha256
        (base32 "10r2ni62fh6zl0im1n7apjf6kx2fprifn71rnaf7dh7xypdkqyw1"))))
    (properties `((upstream-name . "CopulaInference")))
    (build-system r-build-system)
    (propagated-inputs (list r-rvinecopulib r-matrix r-foreach r-doparallel))
    (home-page "https://cran.r-project.org/package=CopulaInference")
    (synopsis
     "Estimation and Goodness-of-Fit of Copula-Based Models with Arbitrary Distributions")
    (description
     "Estimation and goodness-of-fit functions for copula-based models of bivariate
data with arbitrary distributions (discrete, continuous, mixture of both types).
 The copula families considered here are the Gaussian, Student, Clayton, Frank,
Gumbel, Joe, Plackett, BB1, BB6, BB7,BB8, together with the following
non-central squared copula families in Nasri (2020)
<doi:10.1016/j.spl.2020.108704>: ncs-gaussian, ncs-clayton, ncs-gumbel,
ncs-frank, ncs-joe, and ncs-plackett.  For theoretical details, see, e.g., Nasri
and Remillard (2023) <@code{arXiv:2301.13408>}.")
    (license license:gpl3)))

(define-public r-copulagamm
  (package
    (name "r-copulagamm")
    (version "0.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CopulaGAMM" version))
       (sha256
        (base32 "1n5nbmmqz3jynqpv53kwha5s7h9h3br7y7b6798mskadvqc2x90k"))))
    (properties `((upstream-name . "CopulaGAMM")))
    (build-system r-build-system)
    (propagated-inputs (list r-statmod r-matrixstats))
    (home-page "https://cran.r-project.org/package=CopulaGAMM")
    (synopsis "Copula-Based Mixed Regression Models")
    (description
     "Estimation of 2-level factor copula-based regression models for clustered data
where the response variable can be either discrete or continuous.")
    (license license:gpl2+)))

(define-public r-copulaedas
  (package
    (name "r-copulaedas")
    (version "1.4.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "copulaedas" version))
       (sha256
        (base32 "01wp8jnz7kndknj7lh9ia7mm41k1vbaksalyy9v19bb77yhgzmba"))))
    (properties `((upstream-name . "copulaedas")))
    (build-system r-build-system)
    (propagated-inputs (list r-vines r-truncnorm r-mvtnorm r-copula))
    (home-page "https://github.com/yasserglez/copulaedas")
    (synopsis "Estimation of Distribution Algorithms Based on Copulas")
    (description
     "This package provides a platform where EDAs (estimation of distribution
algorithms) based on copulas can be implemented and studied.  The package offers
complete implementations of various EDAs based on copulas and vines, a group of
well-known optimization problems, and utility functions to study the performance
of the algorithms.  Newly developed EDAs can be easily integrated into the
package by extending an S4 class with generic functions for their main
components.")
    (license license:gpl2+)))

(define-public r-copuladata
  (package
    (name "r-copuladata")
    (version "0.0-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "copulaData" version))
       (sha256
        (base32 "052vr5961pqqfk75yabnna345qgrhrjwzavx5244c6mark4xsyxb"))))
    (properties `((upstream-name . "copulaData")))
    (build-system r-build-system)
    (home-page "https://copula.r-forge.r-project.org/")
    (synopsis "Data Sets for Copula Modeling")
    (description
     "Data sets used for copula modeling in addition to those in the R package
copula'.  These include a random subsample from the US National Education
Longitudinal Study (NELS) of 1988 and nursing home data from Wisconsin.")
    (license (list license:gpl3+
                   (license:fsdg-compatible "file LICENCE")))))

(define-public r-copulacenr
  (package
    (name "r-copulacenr")
    (version "1.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CopulaCenR" version))
       (sha256
        (base32 "1z1a9hrb5v784j46yc2dsbizbis8pb5zdbc4cky8yws7swiax5m1"))))
    (properties `((upstream-name . "CopulaCenR")))
    (build-system r-build-system)
    (propagated-inputs (list r-vinecopula
                             r-survival
                             r-pracma
                             r-plotly
                             r-magrittr
                             r-icenreg
                             r-foreach
                             r-flexsurv
                             r-corpcor
                             r-copula
                             r-copbasic
                             r-caret
                             r-boot))
    (home-page "https://cran.r-project.org/package=CopulaCenR")
    (synopsis "Copula-Based Regression Models for Multivariate Censored Data")
    (description
     "Copula-based regression models for multivariate censored data, including
bivariate right-censored data, bivariate interval-censored data, and
right/interval-censored semi-competing risks data.  Currently supports Clayton,
Gumbel, Frank, Joe, AMH and Copula2 copula models.  For marginal models, it
supports parametric (Weibull, Loglogistic, Gompertz) and semiparametric (Cox and
transformation) models.  Includes methods for convenient prediction and
plotting.  Also provides a bivariate time-to-event simulation function and an
information ratio-based goodness-of-fit test for copula.  Method details can be
found in Sun et.al (2019) Lifetime Data Analysis, Sun et.al (2021)
Biostatistics, Sun et.al (2022) Statistical Methods in Medical Research, Sun
et.al (2022) Biometrics, and Sun et al. (2023+) JRSSC.")
    (license license:gpl3+)))

(define-public r-copulaboost
  (package
    (name "r-copulaboost")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "copulaboost" version))
       (sha256
        (base32 "12mx048mxglaxdkskp9b31rkmhsyfay8m62134nh9k04iqb8zjap"))))
    (properties `((upstream-name . "copulaboost")))
    (build-system r-build-system)
    (propagated-inputs (list r-rvinecopulib))
    (home-page "https://cran.r-project.org/package=copulaboost")
    (synopsis
     "Fitting Additive Copula Regression Models for Binary Outcome Regression")
    (description
     "Additive copula regression for regression problems with binary outcome via
gradient boosting [Brant, HobÃ¦k Haff (2022); <@code{arXiv:2208.04669>}].  The
fitting process includes a specialised model selection algorithm for each
component, where each component is found (by greedy optimisation) among all the
D-vines with only Gaussian pair-copulas of a fixed dimension, as specified by
the user.  When the variables and structure have been selected, the algorithm
then re-fits the component where the pair-copula distributions can be different
from Gaussian, if specified.")
    (license (license:fsdg-compatible "MIT + file LICENCE"))))

(define-public r-copula-surv
  (package
    (name "r-copula-surv")
    (version "1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Copula.surv" version))
       (sha256
        (base32 "177m79nc9gwnfxai0gdw7id0212rxp34rpcp0b7j79r3zncwnb6i"))))
    (properties `((upstream-name . "Copula.surv")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=Copula.surv")
    (synopsis "Analysis of Bivariate Survival Data Based on Copulas")
    (description
     "Simulating bivariate survival data from copula models.  Estimation of the
association parameter in copula models.  Two different ways to estimate the
association parameter in copula models are implemented.  A goodness-of-fit test
for a given copula model is implemented.  See Emura, Lin and Wang (2010)
<doi:10.1016/j.csda.2010.03.013> for details.")
    (license license:gpl2)))

(define-public r-copula-markov-survival
  (package
    (name "r-copula-markov-survival")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Copula.Markov.survival" version))
       (sha256
        (base32 "1sxg0ir39f4hj4m6imija0c88j513j6fflcp7xc0599iglwsrbvs"))))
    (properties `((upstream-name . "Copula.Markov.survival")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival))
    (home-page "https://cran.r-project.org/package=Copula.Markov.survival")
    (synopsis "Copula Markov Model with Dependent Censoring")
    (description
     "Perform likelihood estimation and corresponding analysis under the copula-based
Markov chain model for serially dependent event times with a dependent terminal
event.  Available are statistical methods in Huang, Wang and Emura (2020, JJSD
accepted).")
    (license license:gpl3)))

(define-public r-copula-markov
  (package
    (name "r-copula-markov")
    (version "2.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Copula.Markov" version))
       (sha256
        (base32 "18krq0q5i3j211g88sl153f1fa5crdcgclvl5lqawm7zykyzblh2"))))
    (properties `((upstream-name . "Copula.Markov")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=Copula.Markov")
    (synopsis
     "Copula-Based Estimation and Statistical Process Control for Serially Correlated Time Series")
    (description
     "Estimation and statistical process control are performed under copula-based
time-series models.  Available are statistical methods in Long and Emura (2014
JCSA), Emura et al. (2017 Commun Stat-Simul)
<DOI:10.1080/03610918.2015.1073303>, Huang and Emura (2021 Commun Stat-Simul)
<DOI:10.1080/03610918.2019.1602647>, Lin et al. (2021 Comm Stat-Simul)
<DOI:10.1080/03610918.2019.1652318>, Sun et al. (2020 JSS Series in
Statistics)<DOI:10.1007/978-981-15-4998-4>, and Huang and Emura (2021, in
revision).")
    (license license:gpl2)))

(define-public r-copula
  (package
    (name "r-copula")
    (version "1.1-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "copula" version))
       (sha256
        (base32 "0kshyr77qiidcmi51dyapbdv46dkxv5n4p71vwh7cyb091zqpmzl"))))
    (properties `((upstream-name . "copula")))
    (build-system r-build-system)
    (propagated-inputs (list r-stabledist
                             r-pspline
                             r-pcapp
                             r-numderiv
                             r-mvtnorm
                             r-matrix
                             r-lattice
                             r-gsl
                             r-colorspace
                             r-adgoftest))
    (native-inputs (list r-knitr gfortran))
    (home-page "https://copula.r-forge.r-project.org/")
    (synopsis "Multivariate Dependence with Copulas")
    (description
     "This package provides classes (S4) of commonly used elliptical, Archimedean,
extreme-value and other copula families, as well as their rotations, mixtures
and asymmetrizations.  Nested Archimedean copulas, related tools and special
functions.  Methods for density, distribution, random number generation,
bivariate dependence measures, Rosenblatt transform, Kendall distribution
function, perspective and contour plots.  Fitting of copula models with
potentially partly fixed parameters, including standard errors.  Serial
independence tests, copula specification tests (independence, exchangeability,
radial symmetry, extreme-value dependence, goodness-of-fit) and model selection
based on cross-validation.  Empirical copula, smoothed versions, and
non-parametric estimators of the Pickands dependence function.")
    (license (list license:gpl3+
                   (license:fsdg-compatible "file LICENCE")))))

(define-public r-copsens
  (package
    (name "r-copsens")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CopSens" version))
       (sha256
        (base32 "0ljp2c25zmyiv88mdari08z9845y9niyg90a8vlq75im5w825w8a"))))
    (properties `((upstream-name . "CopSens")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyverse
                             r-tidyr
                             r-pcamethods
                             r-mass
                             r-ggplot2
                             r-dplyr
                             r-cvxr))
    (home-page "https://github.com/JiajingZ/CopSens")
    (synopsis
     "Copula-Based Sensitivity Analysis for Observational Causal Inference")
    (description
     "This package implements the copula-based sensitivity analysis method, as
discussed in Copula-based Sensitivity Analysis for Multi-Treatment Causal
Inference with Unobserved Confounding <@code{arXiv:2102.09412>}, with Gaussian
copula adopted in particular.")
    (license license:gpl3)))

(define-public r-cops
  (package
    (name "r-cops")
    (version "1.12-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cops" version))
       (sha256
        (base32 "0wcan46qnij8qp089ff0g7wr6byv91zd517hkmxg1zmcidcna0ys"))))
    (properties `((upstream-name . "cops")))
    (build-system r-build-system)
    (propagated-inputs (list r-subplex
                             r-smacofx
                             r-smacof
                             r-rsolnp
                             r-rgenoud
                             r-pso
                             r-nloptr
                             r-nlcoptim
                             r-minqa
                             r-gensa
                             r-dfoptim
                             r-crs
                             r-cordillera
                             r-cmaes
                             r-analogue))
    (native-inputs (list r-r-rsp))
    (home-page "https://r-forge.r-project.org/projects/stops/")
    (synopsis "Cluster Optimized Proximity Scaling")
    (description
     "Multidimensional scaling (MDS) methods that aim at pronouncing the clustered
appearance of the configuration (Rusch, Mair & Hornik, 2021,
<doi:10.1080/10618600.2020.1869027>).  They achieve this by transforming
proximities/distances with explicit power functions and penalizing the fitting
criterion with a clusteredness index, the OPTICS Cordillera (Rusch, Hornik &
Mair, 2018, <doi:10.1080/10618600.2017.1349664>).  There are two variants: One
for finding the configuration directly (COPS-C) with given explicit power
transformations and implicit ratio, interval and non-metric optimal scaling
transformations (Borg & Groenen, 2005, ISBN:978-0-387-28981-6), and one for
using the augmented fitting criterion to find optimal hyperparameters for the
explicit transformations (P-COPS).  The package contains various functions,
wrappers, methods and classes for fitting, plotting and displaying a large
number of different MDS models (most of the functionality in smacofx) in the
COPS framework.  The package further contains a function for pattern search
optimization, the ``Adaptive Luus-Jaakola Algorithm (Rusch, Mair & Hornik,
2021,<doi:10.1080/10618600.2020.1869027>) and a functions to calculate the
phi-distances for count data or histograms.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-copre
  (package
    (name "r-copre")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "copre" version))
       (sha256
        (base32 "1lgps3wmjp3ja13xd33q41xb3kc56vmyidjpsmm5c2y263pm1m8i"))))
    (properties `((upstream-name . "copre")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo
                             r-rcpp
                             r-pracma
                             r-dirichletprocess
                             r-bh
                             r-abind))
    (home-page "https://cran.r-project.org/package=copre")
    (synopsis "Tools for Nonparametric Martingale Posterior Sampling")
    (description
     "This package performs Bayesian nonparametric density estimation using Martingale
posterior distributions including the Copula Resampling (@code{CopRe})
algorithm.  Also included are a Gibbs sampler for the marginal Gibbs-type
mixture model and an extension to include full uncertainty quantification via a
predictive sequence resampling (@code{SeqRe}) algorithm.  The @code{CopRe} and
@code{SeqRe} samplers generate random nonparametric distributions as output,
leading to complete nonparametric inference on posterior summaries.  Routines
for calculating arbitrary functionals from the sampled distributions are
included as well as an important algorithm for finding the number and location
of modes, which can then be used to estimate the clusters in the data using, for
example, k-means.  Implements work developed in Moya B., Walker S. G. (2022).
<doi:10.48550/arxiv.2206.08418>, Fong, E., Holmes, C., Walker, S. G. (2021)
<doi:10.48550/arxiv.2103.15671>, and Escobar M. D., West, M. (1995)
<doi:10.1080/01621459.1995.10476550>.")
    (license license:gpl2+)))

(define-public r-coppecosenzar
  (package
    (name "r-coppecosenzar")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coppeCosenzaR" version))
       (sha256
        (base32 "1chwsfyaf5rmlsypr43n7px8b2220dfa5mzcriq1swylgbx4181l"))))
    (properties `((upstream-name . "coppeCosenzaR")))
    (build-system r-build-system)
    (home-page "https://github.com/ptaranti/coppeCosenzaR")
    (synopsis "COPPE-Cosenza Fuzzy Hierarchy Model")
    (description
     "The program implements the COPPE-Cosenza Fuzzy Hierarchy Model.  The model was
based on the evaluation of local alternatives, representing regional
potentialities, so as to fulfill demands of economic projects.  After defining
demand profiles in terms of their technological coefficients, the degree of
importance of factors is defined so as to represent the productive activity.
The method can detect a surplus of supply without the restriction of the
distance of classical algebra, defining a hierarchy of location alternatives.
In COPPE-Cosenza Model, the distance between factors is measured in terms of the
difference between grades of memberships of the same factors belonging to two or
more sets under comparison.  The required factors are classified under the
following linguistic variables: Critical (CR); Conditioning (C); Little
Conditioning (LC); and Irrelevant (I).  And the alternatives can assume the
following linguistic variables: Excellent (Ex), Good (G), Regular (R), Weak (W),
Empty (Em), Zero (Z) and Inexistent (In).  The model also provides flexibility,
allowing different aggregation rules to be performed and defined by the Decision
Maker.  Such feature is considered in this package, allowing the user to define
other aggregation matrices, since it considers the same linguistic variables
mentioned.")
    (license (list license:gpl2
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-cophescan
  (package
    (name "r-cophescan")
    (version "1.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cophescan" version))
       (sha256
        (base32 "0lnc20f1xaijibza4px9m47fy70jz9y9y5m7wk5h50kb4dh6ywxh"))))
    (properties `((upstream-name . "cophescan")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis
                             r-rcpparmadillo
                             r-rcpp
                             r-pheatmap
                             r-matrixstats
                             r-magrittr
                             r-ggrepel
                             r-ggplot2
                             r-dplyr
                             r-data-table
                             r-coloc))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ichcha-m/cophescan")
    (synopsis "Adaptation of the Coloc Method for PheWAS")
    (description
     "This package provides a Bayesian method for Phenome-wide association studies
(@code{PheWAS}) that identifies causal associations between genetic variants and
traits, while simultaneously addressing confounding due to linkage
disequilibrium.  For details see Manipur et al (2023)
<doi:10.1101/2023.06.29.546856>.")
    (license license:gpl3)))

(define-public r-copernicusmarine
  (package
    (name "r-copernicusmarine")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CopernicusMarine" version))
       (sha256
        (base32 "09kv2c7lkbnpzfs0i48dp3gvx6mwn89q0y3f4hbmm9iiyksrdw2i"))))
    (properties `((upstream-name . "CopernicusMarine")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-tidyr
                             r-stringr
                             r-sf
                             r-rvest
                             r-rlang
                             r-readr
                             r-purrr
                             r-leaflet
                             r-httr2
                             r-dplyr
                             r-crayon))
    (home-page "https://github.com/pepijn-devries/CopernicusMarine")
    (synopsis
     "Search Download and Handle Data from Copernicus Marine Service Information")
    (description
     "Subset and download data from EU Copernicus Marine Service Information:
<https://data.marine.copernicus.eu>.  Import data on the oceans physical and
biogeochemical state from Copernicus into R without the need of external
software.")
    (license license:gpl3+)))

(define-public r-copernicusdem
  (package
    (name "r-copernicusdem")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CopernicusDEM" version))
       (sha256
        (base32 "00rpdfspyd94jr2ahw7dc661wdgxnxzcxgg40yn48c1v6hxjhfhp"))))
    (properties `((upstream-name . "CopernicusDEM")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf r-glue r-foreach r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mlampros/CopernicusDEM")
    (synopsis "Copernicus Digital Elevation Models")
    (description
     "Copernicus Digital Elevation Model datasets (DEM) of 90 and 30 meters resolution
using the awscli command line tool.  The Copernicus (DEM) is included in the
Registry of Open Data on AWS (Amazon Web Services) and represents the surface of
the Earth including buildings, infrastructure and vegetation.")
    (license license:gpl3)))

(define-public r-copent
  (package
    (name "r-copent")
    (version "0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "copent" version))
       (sha256
        (base32 "0ymjpwqbdfbyrvszi5avpbx086i4lwrxgxysr0rlnh2wfm849vsj"))))
    (properties `((upstream-name . "copent")))
    (build-system r-build-system)
    (home-page "https://github.com/majianthu/copent")
    (synopsis "Estimating Copula Entropy and Transfer Entropy")
    (description
     "The nonparametric methods for estimating copula entropy, transfer entropy, and
the statistics for multivariate normality test and two-sample test are
implemented.  The methods for estimating transfer entropy and the statistics for
multivariate normality test and two-sample test are based on the method for
estimating copula entropy.  The method for change point detection with copula
entropy based two-sample test is also implemented.  Please refer to Ma and Sun
(2011) <doi:10.1016/S1007-0214(11)70008-6>, Ma (2019)
<doi:10.48550/@code{arXiv.1910.04375>}, Ma (2022)
<doi:10.48550/@code{arXiv.2206.05956>}, Ma (2023)
<doi:10.48550/@code{arXiv.2307.07247>}, and Ma (2024)
<doi:10.48550/@code{arXiv.2403.07892>} for more information.")
    (license license:gpl2+)))

(define-public r-cope
  (package
    (name "r-cope")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cope" version))
       (sha256
        (base32 "1r02nb6wy25ixhdcbqqz167s7ny3hydpxfxry5ar4136qvcamgyy"))))
    (properties `((upstream-name . "cope")))
    (build-system r-build-system)
    (propagated-inputs (list r-nlme
                             r-mvtnorm
                             r-matrix
                             r-mass
                             r-maps
                             r-fields
                             r-abind))
    (home-page "https://cran.r-project.org/package=cope")
    (synopsis "Coverage Probability Excursion (CoPE) Sets")
    (description
     "This package provides functions to compute and plot Coverage Probability
Excursion (@code{CoPE}) sets for real valued functions on a 2-dimensional
domain. @code{CoPE} sets are obtained from repeated noisy observations of the
function on the entire domain.  They are designed to bound the excursion set of
the target function at a given level from above and below with a predefined
probability.  The target function can be a parameter in spatially-indexed linear
regression.  Support by NIH grant R01 CA157528 is gratefully acknowledged.")
    (license license:gpl2)))

(define-public r-copcts
  (package
    (name "r-copcts")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CopCTS" version))
       (sha256
        (base32 "1j0bhkjk181y9k69442diswgwax5whmh5vfqydhf3b1r5ll1wkm3"))))
    (properties `((upstream-name . "CopCTS")))
    (build-system r-build-system)
    (propagated-inputs (list r-msm r-copula r-copbasic))
    (home-page "https://cran.r-project.org/package=CopCTS")
    (synopsis
     "Copula-Based Semiparametric Analysis for Time Series Data with Detection Limits")
    (description
     "Semiparametric estimation for censored time series with lower detection limit.
The latent response is a sequence of stationary process with Markov property of
order one.  Estimation of copula parameter(COPC) and Conditional quantile
estimation are included for five available copula functions.  Copula selection
methods based on L2 distance from empirical copula function are also included.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-copcor
  (package
    (name "r-copcor")
    (version "2024.7-31")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "copcor" version))
       (sha256
        (base32 "1m9a831m290q6ihxriknpbysp1694lcbb7j7knkcgnnqfkh08y5n"))))
    (properties `((upstream-name . "copcor")))
    (build-system r-build-system)
    (propagated-inputs (list r-kyotil))
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=copcor")
    (synopsis "Correlates of Protection and Correlates of Risk Functions")
    (description
     "Correlates of protection (@code{CoP}) and correlates of risk (@code{CoR}) study
the immune biomarkers associated with an infectious disease outcome, e.g. COVID
or HIV-1 infection.  This package contains shared functions for analyzing
@code{CoP} and @code{CoR}, including bootstrapping procedures, competing risk
estimation, and bootstrapping marginalized risks.")
    (license license:gpl2+)))

(define-public r-copcar
  (package
    (name "r-copcar")
    (version "2.0-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "copCAR" version))
       (sha256
        (base32 "1wvp7khp0f0x6skiq1d6npndb09ak6d6ijmx907gfrd6b0ydaklb"))))
    (properties `((upstream-name . "copCAR")))
    (build-system r-build-system)
    (propagated-inputs (list r-spam r-rcpparmadillo r-rcpp r-numderiv r-mcmcse))
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=copCAR")
    (synopsis "Fitting the copCAR Regression Model for Discrete Areal Data")
    (description
     "This package provides tools for fitting the @code{copCAR} (Hughes, 2015)
<DOI:10.1080/10618600.2014.948178> regression model for discrete areal data.
Three types of estimation are supported (continuous extension, composite
marginal likelihood, and distributional transform), for three types of outcomes
(Bernoulli, negative binomial, and Poisson).")
    (license license:gpl2+)))

(define-public r-copbasic
  (package
    (name "r-copbasic")
    (version "2.2.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "copBasic" version))
       (sha256
        (base32 "01yi81v1s893b8wqwkwz5613a7j7dcb41mdnd7hbxfg3s443w8iv"))))
    (properties `((upstream-name . "copBasic")))
    (build-system r-build-system)
    (propagated-inputs (list r-randtoolbox r-lmomco))
    (home-page "https://cran.r-project.org/package=copBasic")
    (synopsis "General Bivariate Copula Theory and Many Utility Functions")
    (description
     "Extensive functions for bivariate copula (bicopula) computations and related
operations for bicopula theory.  The lower, upper, product, and select other
bicopula are implemented along with operations including the diagonal, survival
copula, dual of a copula, co-copula, and numerical bicopula density.  Level
sets, horizontal and vertical sections are supported.  Numerical derivatives and
inverses of a bicopula are provided through which simulation is implemented.
Bicopula composition, convex combination, asymmetry extension, and products also
are provided.  Support extends to the Kendall Function as well as the Lmoments
thereof.  Kendall Tau, Spearman Rho and Footrule, Gini Gamma, Blomqvist Beta,
Hoeffding Phi, Schweizer- Wolff Sigma, tail dependency, tail order, skewness,
and bivariate Lmoments are implemented, and positive/negative quadrant
dependency, left (right) increasing (decreasing) are available.  Other features
include Kullback-Leibler Divergence, Vuong Procedure, spectral measure, and
Lcomoments for inference, maximum likelihood, and AIC, BIC, and RMSE for
goodness-of-fit.")
    (license license:gpl2)))

(define-public r-coortweet
  (package
    (name "r-coortweet")
    (version "2.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CooRTweet" version))
       (sha256
        (base32 "0gziybfp640p2gskbz80kx9ikmg3mpk0m937iq44k1906lrvp9p2"))))
    (properties `((upstream-name . "CooRTweet")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidytable
                             r-stringi
                             r-rcppsimdjson
                             r-lubridate
                             r-igraph
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/nicolarighetti/CooRTweet")
    (synopsis "Coordinated Networks Detection on Social Media")
    (description
     "Detects a variety of coordinated actions on social media and outputs the network
of coordinated users along with related information.")
    (license license:expat)))

(define-public r-coordinatecleaner
  (package
    (name "r-coordinatecleaner")
    (version "3.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoordinateCleaner" version))
       (sha256
        (base32 "0bs1vr145ab42i7x0jcsin6sfaxy05ly2i4qcrlvyvz303ynj0rf"))))
    (properties `((upstream-name . "CoordinateCleaner")))
    (build-system r-build-system)
    (inputs (list gdal))
    (propagated-inputs (list r-tidyselect
                             r-terra
                             r-rnaturalearth
                             r-rgbif
                             r-ggplot2
                             r-geosphere
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://ropensci.github.io/CoordinateCleaner/")
    (synopsis
     "Automated Cleaning of Occurrence Records from Biological Collections")
    (description
     "Automated flagging of common spatial and temporal errors in biological and
paleontological collection data, for the use in conservation, ecology and
paleontology.  Includes automated tests to easily flag (and exclude) records
assigned to country or province centroid, the open ocean, the headquarters of
the Global Biodiversity Information Facility, urban areas or the location of
biodiversity institutions (museums, zoos, botanical gardens, universities).
Furthermore identifies per species outlier coordinates, zero coordinates,
identical latitude/longitude and invalid coordinates.  Also implements an
algorithm to identify data sets with a significant proportion of rounded
coordinates.  Especially suited for large data sets.  The reference for the
methodology is: Zizka et al. (2019) <doi:10.1111/2041-210X.13152>.")
    (license license:gpl3)))

(define-public r-coopgame
  (package
    (name "r-coopgame")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoopGame" version))
       (sha256
        (base32 "0i4yw2nznmcps9s9f592nbs8dvncb0w2bynvsfkp21lzd4pfsp4n"))))
    (properties `((upstream-name . "CoopGame")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcdd r-gtools r-geometry))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://cran.r-project.org/package=CoopGame")
    (synopsis "Important Concepts of Cooperative Game Theory")
    (description
     "The theory of cooperative games with transferable utility offers useful insights
into the way parties can share gains from cooperation and secure sustainable
agreements, see e.g. one of the books by Chakravarty, Mitra and Sarkar (2015,
ISBN:978-1107058798) or by Driessen (1988, ISBN:978-9027727299) for more
details.  A comprehensive set of tools for cooperative game theory with
transferable utility is provided.  Users can create special families of
cooperative games, like e.g. bankruptcy games, cost sharing games and weighted
voting games.  There are functions to check various game properties and to
compute five different set-valued solution concepts for cooperative games.  A
large number of point-valued solution concepts is available reflecting the
diverse application areas of cooperative game theory.  Some of these
point-valued solution concepts can be used to analyze weighted voting games and
measure the influence of individual voters within a voting body.  There are
routines for visualizing both set-valued and point-valued solutions in the case
of three or four players.")
    (license license:gpl2)))

(define-public r-coop
  (package
    (name "r-coop")
    (version "0.6-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coop" version))
       (sha256
        (base32 "0ww99ssgawsgn6rqy838wbx6iirzdrzyxirvz084ih8j50blx420"))))
    (properties `((upstream-name . "coop")))
    (build-system r-build-system)
    (home-page "https://github.com/wrathematics/coop")
    (synopsis
     "Co-Operation: Fast Covariance, Correlation, and Cosine Similarity Operations")
    (description
     "Fast implementations of the co-operations: covariance, correlation, and cosine
similarity.  The implementations are fast and memory-efficient and their use is
resolved automatically based on the input data, handled by R's S3 methods.  Full
descriptions of the algorithms and benchmarks are available in the package
vignettes.")
    (license (license:fsdg-compatible "BSD 2-clause License + file LICENSE"))))

(define-public r-cooltools
  (package
    (name "r-cooltools")
    (version "2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cooltools" version))
       (sha256
        (base32 "1ammi354y2cbaarf29s9kjks8k0zdimcxif6crakn9p3vi30h0nk"))))
    (properties `((upstream-name . "cooltools")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp
                             r-rcpp
                             r-raster
                             r-randtoolbox
                             r-pracma
                             r-png
                             r-plotrix
                             r-mass
                             r-jpeg
                             r-fnn
                             r-data-table
                             r-cubature
                             r-celestial
                             r-bit64))
    (home-page "https://cran.r-project.org/package=cooltools")
    (synopsis "Practical Tools for Scientific Computations and Visualizations")
    (description
     "Collection of routines for efficient scientific computations in physics and
astrophysics.  These routines include utility functions, numerical computation
tools, as well as visualisation tools.  They can be used, for example, for
generating random numbers from spherical and custom distributions, information
and entropy analysis, special Fourier transforms, two-point correlation
estimation (e.g. as in Landy & Szalay (1993) <doi:10.1086/172900>), binning &
gridding of point sets, 2D interpolation, Monte Carlo integration, vector
arithmetic and coordinate transformations.  Also included is a non-exhaustive
list of important constants and cosmological conversion functions.  The graphics
routines can be used to produce and export publication-ready scientific plots
and movies, e.g. as used in Obreschkow et al. (2020, MNRAS Vol 493, Issue 3,
Pages 4551â4569).  These routines include special color scales, projection
functions, and bitmap handling routines.")
    (license license:gpl3)))

(define-public r-cool
  (package
    (name "r-cool")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoOL" version))
       (sha256
        (base32 "18z7s8bvnym4xj0hh5m6bwm86ddmsgivqv4g5zbd9m87l7khl9pn"))))
    (properties `((upstream-name . "CoOL")))
    (build-system r-build-system)
    (propagated-inputs (list r-wesanderson
                             r-rcpparmadillo
                             r-rcpp
                             r-proc
                             r-plyr
                             r-mltools
                             r-ggplot2
                             r-data-table
                             r-clustgeo))
    (home-page "https://bioconductor.org")
    (synopsis "Causes of Outcome Learning")
    (description
     "Implementing the computational phase of the Causes of Outcome Learning approach
as described in Rieckmann, Dworzynski, Arras, Lapuschkin, Samek, Arah, Rod,
Ekstrom.  2022.  Causes of outcome learning: A causal inference-inspired machine
learning approach to disentangling common combinations of potential causes of a
health outcome.  International Journal of Epidemiology
<doi:10.1093/ije/dyac078>.  The optional ggtree package can be obtained through
Bioconductor.")
    (license license:gpl2)))

(define-public r-cookies
  (package
    (name "r-cookies")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cookies" version))
       (sha256
        (base32 "1dpil57grnqn34b682fakzsrh2xghc566nhqdgnrjd7ly59v0z3x"))))
    (properties `((upstream-name . "cookies")))
    (build-system r-build-system)
    (arguments
     (list
      #:modules '((guix build r-build-system)
                  (guix build minify-build-system)
                  (guix build utils)
                  (ice-9 match))
      #:imported-modules `(,@%r-build-system-modules (guix build
                                                      minify-build-system))
      #:phases '(modify-phases %standard-phases
                  (add-after 'unpack 'process-javascript
                    (lambda* (#:key inputs #:allow-other-keys)
                      (with-directory-excursion "inst/"
                        (for-each (match-lambda
                                    ((source . target) (minify source
                                                               #:target target)))
                                  '())))))))
    (propagated-inputs (list r-vctrs
                             r-shiny
                             r-rlang
                             r-purrr
                             r-jsonlite
                             r-httpuv
                             r-htmltools
                             r-glue
                             r-clock
                             r-cli))
    (native-inputs (list esbuild))
    (home-page "https://github.com/r4ds/cookies")
    (synopsis "Use Browser Cookies with 'shiny'")
    (description
     "Browser cookies are name-value pairs that are saved in a user's browser by a
website.  Cookies allow websites to persist information about the user and their
use of the website.  Here we provide tools for working with cookies in shiny
apps, in part by wrapping the js-cookie @code{JavaScript} library
<https://github.com/js-cookie/js-cookie>.")
    (license license:expat)))

(define-public r-cookiemonster
  (package
    (name "r-cookiemonster")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cookiemonster" version))
       (sha256
        (base32 "1fs8a7i2h1v4xvcjnccnvxapiprffyz49pgrdjp67k14r6nk2fha"))))
    (properties `((upstream-name . "cookiemonster")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-urltools
                             r-tibble
                             r-stringi
                             r-rappdirs
                             r-openssl
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cookiemonster")
    (synopsis "Your Friendly Solution to Managing Browser Cookies")
    (description
     "This package provides a convenient tool to store and format browser cookies and
use them in HTTP requests (for example, through httr2', httr or curl').")
    (license license:gpl3+)))

(define-public r-cookiecutter
  (package
    (name "r-cookiecutter")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cookiecutter" version))
       (sha256
        (base32 "0kpyn20xk2sfb5zh18yxl5qjf628max186v1knq4f2mik1n4lwbd"))))
    (properties `((upstream-name . "cookiecutter")))
    (build-system r-build-system)
    (propagated-inputs (list r-whisker
                             r-stringr
                             r-rlang
                             r-readr
                             r-purrr
                             r-mime
                             r-jsonlite
                             r-fs))
    (home-page "https://github.com/felixhenninger/cookiecutter/")
    (synopsis "Generate Project Files from a Template")
    (description
     "Generate project files and directories following a pre-made template.  You can
specify variables to customize file names and content, and flexibly adapt the
template to your needs.  cookiecutter for R implements a subset of the excellent
cookiecutter package for the Python programming language
(<https://github.com/cookiecutter/>), and aims to be largely compatible with the
original cookiecutter template format.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-cooccurrenceaffinity
  (package
    (name "r-cooccurrenceaffinity")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CooccurrenceAffinity" version))
       (sha256
        (base32 "0wn8jkvm5x30vj1vy196l691kbs5aa3j09s5dsa2r54cr34d16mn"))))
    (properties `((upstream-name . "CooccurrenceAffinity")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape r-plyr r-ggplot2 r-cowplot r-biasedurn))
    (home-page "https://github.com/kpmainali/CooccurrenceAffinity")
    (synopsis "Affinity in Co-Occurrence Data")
    (description
     "Computes a novel metric of affinity between two entities based on their
co-occurrence (using binary presence/absence data).  The metric and its MLE,
alpha hat, were advanced in Mainali, Slud, et al, 2021
<doi:10.1126/sciadv.abj9204>.  Various types of confidence intervals and median
interval were developed in Mainali and Slud, 2022
<doi:10.1101/2022.11.01.514801>.")
    (license license:expat)))

(define-public r-cooccur
  (package
    (name "r-cooccur")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cooccur" version))
       (sha256
        (base32 "1wlaghhi4f3v8kzwhcgq3c6as7v3zlpkzhb232qz1amr7f0058kv"))))
    (properties `((upstream-name . "cooccur")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2 r-gmp r-ggplot2))
    (home-page "https://cran.r-project.org/package=cooccur")
    (synopsis "Probabilistic Species Co-Occurrence Analysis in R")
    (description
     "This R package applies the probabilistic model of species co-occurrence (Veech
2013) to a set of species distributed among a set of survey or sampling sites.
The algorithm calculates the observed and expected frequencies of co-occurrence
between each pair of species.  The expected frequency is based on the
distribution of each species being random and independent of the other species.
The analysis returns the probabilities that a more extreme (either low or high)
value of co-occurrence could have been obtained by chance.  The package also
includes functions for visualizing species co-occurrence results and preparing
data for downstream analyses.")
    (license license:gpl2)))

(define-public r-convospat
  (package
    (name "r-convospat")
    (version "1.2.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "convoSPAT" version))
       (sha256
        (base32 "1pmiirigjdkrb3pzqcw6qlh6418z384mvaxqw5mrcm1gxzrqp649"))))
    (properties `((upstream-name . "convoSPAT")))
    (build-system r-build-system)
    (propagated-inputs (list r-statmatch r-plotrix r-mass r-fields r-ellipse))
    (home-page "http://github.com/markdrisser/convoSPAT")
    (synopsis "Convolution-Based Nonstationary Spatial Modeling")
    (description
     "Fits convolution-based nonstationary Gaussian process models to point-referenced
spatial data.  The nonstationary covariance function allows the user to specify
the underlying correlation structure and which spatial dependence parameters
should be allowed to vary over space: the anisotropy, nugget variance, and
process variance.  The parameters are estimated via maximum likelihood, using a
local likelihood approach.  Also provided are functions to fit stationary
spatial models for comparison, calculate the Kriging predictor and standard
errors, and create various plots to visualize nonstationarity.")
    (license license:expat)))

(define-public r-convolutioner
  (package
    (name "r-convolutioner")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Convolutioner" version))
       (sha256
        (base32 "1ria4ii7zdqgrzgdx4c82dj4lg791iwy2y66fv1qyibws0ag3bhq"))))
    (properties `((upstream-name . "Convolutioner")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=Convolutioner")
    (synopsis "Convolution of Data")
    (description
     "General functions for convolutions of data.  Moving average, running median, and
other filters are available.  Bibliography regarding the functions can be found
in the following text.  Richard G. Brereton (2003) <ISBN:9780471489771>.")
    (license license:gpl3)))

(define-public r-convey
  (package
    (name "r-convey")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "convey" version))
       (sha256
        (base32 "1i85j4wam81iskmynjr81xh065gh2d0wi01gprs7vg5dsvshxfh9"))))
    (properties `((upstream-name . "convey")))
    (build-system r-build-system)
    (propagated-inputs (list r-survey))
    (home-page "https://www.convey-r.org/")
    (synopsis "Income Concentration Analysis with Complex Survey Samples")
    (description
     "Variance estimation on indicators of income concentration and poverty using
complex sample survey designs.  Wrapper around the survey package.")
    (license license:gpl3)))

(define-public r-convevol
  (package
    (name "r-convevol")
    (version "2.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "convevol" version))
       (sha256
        (base32 "0j4vbas5lhgbyia15if2hcvjldgln2017n62bs17h7z66n3ps6cv"))))
    (properties `((upstream-name . "convevol")))
    (build-system r-build-system)
    (propagated-inputs (list r-phytools r-magick r-geiger r-cluster r-ape))
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=convevol")
    (synopsis "Analysis of Convergent Evolution")
    (description
     "Quantifies and assesses the significance of convergent evolution using multiple
methods and measures as described in Stayton (2015) <DOI: 10.1111/evo.12729> and
Grossnickle et al.  2023.  Also displays results in various ways.")
    (license license:gpl3)))

(define-public r-convertr
  (package
    (name "r-convertr")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "convertr" version))
       (sha256
        (base32 "1y9aq5in2qv1323amblmq3g22flpqvpkgkrw12kahg56mqf2b3iq"))))
    (properties `((upstream-name . "convertr")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-rstudioapi r-miniui r-dt))
    (home-page "https://cran.r-project.org/package=convertr")
    (synopsis "Convert Between Units")
    (description
     "This package provides conversion functionality between a broad range of
scientific, historical, and industrial unit types.")
    (license license:expat)))

(define-public r-convertpar
  (package
    (name "r-convertpar")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConvertPar" version))
       (sha256
        (base32 "1czw97ya73dinad0n664045s9918a21kv97bpkal40kg029vnw59"))))
    (properties `((upstream-name . "ConvertPar")))
    (build-system r-build-system)
    (propagated-inputs (list r-rweka r-neuralnet r-mirt))
    (home-page "https://cran.r-project.org/package=ConvertPar")
    (synopsis "Estimating IRT Parameters via Machine Learning Algorithms")
    (description
     "This package provides a tool to estimate IRT item parameters (2 PL) using
CTT-based item statistics from small samples via artificial neural networks and
regression trees.")
    (license license:gpl3+)))

(define-public r-convertid
  (package
    (name "r-convertid")
    (version "0.1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "convertid" version))
       (sha256
        (base32 "0mprymgh5wbh9x6kn98q4r6c6rp2l108ddmp2g7lh9m635ys6v8m"))))
    (properties `((upstream-name . "convertid")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-stringr
                             r-rappdirs
                             r-plyr
                             r-org-mm-eg-db
                             r-org-hs-eg-db
                             r-httr
                             r-biomart
                             r-biocfilecache
                             r-assertthat
                             r-annotationdbi))
    (home-page "https://cran.r-project.org/package=convertid")
    (synopsis
     "Convert Gene IDs Between Each Other and Fetch Annotations from Biomart")
    (description
     "Gene Symbols or Ensembl Gene IDs are converted using the Bimap interface in
@code{AnnotationDbi} in @code{convertId2}() but that function is only provided
as fallback mechanism for the most common use cases in data analysis.  The main
function in the package is convert.bm() which queries @code{BioMart} using the
full capacity of the API provided through the @code{biomaRt} package.  Presets
and defaults are provided for convenience but all \"marts\", \"filters\" and
\"attributes\" can be set by the user.  Function convert.alias() converts Gene
Symbols to Aliases and vice versa and function likely_symbol() attempts to
determine the most likely current Gene Symbol.")
    (license license:gpl3)))

(define-public r-convertbonds
  (package
    (name "r-convertbonds")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "convertbonds" version))
       (sha256
        (base32 "0xb6b5xqcgapmvrq3ivcknsbg9m4zkwff7i7l7j78nqafdm45jni"))))
    (properties `((upstream-name . "convertbonds")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=convertbonds")
    (synopsis
     "Use the Given Parameters to Calculate the European Option Value")
    (description
     "Calculate the theoretical value of convertible bonds by given parameters,
including B-S theory and Monte Carlo method.")
    (license license:gpl2)))

(define-public r-convertbcd
  (package
    (name "r-convertbcd")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "convertBCD" version))
       (sha256
        (base32 "1lk87kppzr8wzbjx04grhc29srv22199c17nvch3c7pf1lw5v1nr"))))
    (properties `((upstream-name . "convertBCD")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmpfr r-gmp))
    (home-page "https://cran.r-project.org/package=convertBCD")
    (synopsis
     "Convert Decimal to Binary-Coded Decimal (BCD) Form and Vice Versa")
    (description
     "Convert BCD (raw bytes) to decimal numbers and vice versa.  BCD format is used
to preserve decimals exactly, as opposed to the binary rounding errors inherent
in \"numeric\" or \"floating-point\" formats.")
    (license license:lgpl3)))

(define-public r-conversim
  (package
    (name "r-conversim")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conversim" version))
       (sha256
        (base32 "19s4hy1v7ib4zg393cp0b5hwalw999n2szcigcfijrhfycyk8nsy"))))
    (properties `((upstream-name . "conversim")))
    (build-system r-build-system)
    (propagated-inputs (list r-word2vec
                             r-topicmodels
                             r-tm
                             r-slam
                             r-sentimentr
                             r-lsa
                             r-lme4
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/chaoliu-cl/conversim")
    (synopsis "Conversation Similarity Analysis")
    (description
     "Analyze and compare conversations using various similarity measures including
topic, lexical, semantic, structural, stylistic, sentiment, participant, and
timing similarities.  Supports both pairwise conversation comparisons and
analysis of multiple dyads.  Methods are based on established research: Topic
modeling: Blei et al. (2003) <doi:10.1162/jmlr.2003.3.4-5.993>; Landauer et al.
(1998) <doi:10.1080/01638539809545028>; Lexical similarity: Jaccard (1912)
<doi:10.1111/j.1469-8137.1912.tb05611.x>; Semantic similarity: Salton & Buckley
(1988) <doi:10.1016/0306-4573(88)90021-0>; Mikolov et al. (2013)
<doi:10.48550/@code{arXiv.1301.3781>}; Pennington et al. (2014)
<doi:10.3115/v1/D14-1162>; Structural and stylistic analysis: Graesser et al.
(2004) <doi:10.1075/target.21131.ryu>; Sentiment analysis: Rinker (2019)
<https://github.com/trinker/sentimentr>.")
    (license license:gpl3+)))

(define-public r-convergeu
  (package
    (name "r-convergeu")
    (version "0.7.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "convergEU" version))
       (sha256
        (base32 "01ajzjj0ahlbv0q708hj7cw98b0dahnhkxrd79nrs1wb06rr2j9x"))))
    (properties `((upstream-name . "convergEU")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rmarkdown
                             r-rlang
                             r-purrr
                             r-leaflet
                             r-ggpubr
                             r-ggplot2
                             r-eurostat
                             r-dplyr
                             r-catools
                             r-broom))
    (native-inputs (list r-knitr))
    (home-page
     "https://www.eurofound.europa.eu/system/files/2022-04/introduction-to-the-convergeu-package-0.6.4-tutorial-v2-apr2022.pdf")
    (synopsis "Monitoring Convergence of EU Countries")
    (description
     "Indicators and measures by country and time describe what happens at economic
and social levels.  This package provides functions to calculate several
measures of convergence after imputing missing values.  The automated
downloading of Eurostat data, followed by the production of country fiches and
indicator fiches, makes possible to produce automated reports.  The Eurofound
report (<doi:10.2806/68012>) \"Upward convergence in the EU: Concepts,
measurements and indicators\", 2018, is a detailed presentation of convergence.")
    (license (list license:gpl3 license:bsd-3))))

(define-public r-convergenceconcepts
  (package
    (name "r-convergenceconcepts")
    (version "1.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConvergenceConcepts" version))
       (sha256
        (base32 "1y4kh00z63a9j8bsjgnf6lmwkivsf5zk8yw6i9d72a8jr2bhb78w"))))
    (properties `((upstream-name . "ConvergenceConcepts")))
    (build-system r-build-system)
    (propagated-inputs (list r-tkrplot r-lattice))
    (home-page "https://cran.r-project.org/package=ConvergenceConcepts")
    (synopsis "Seeing Convergence Concepts in Action")
    (description
     "This is a pedagogical package, designed to help students understanding
convergence of random variables.  It provides a way to investigate interactively
various modes of convergence (in probability, almost surely, in law and in mean)
of a sequence of i.i.d.  random variables.  Visualisation of simulated sample
paths is possible through interactive plots.  The approach is illustrated by
examples and exercises through the function investigate', as described in Lafaye
de Micheaux and Liquet (2009) <doi:10.1198/tas.2009.0032>.  The user can study
his/her own sequences of random variables.")
    (license license:gpl2+)))

(define-public r-convergenceclubs
  (package
    (name "r-convergenceclubs")
    (version "2.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConvergenceClubs" version))
       (sha256
        (base32 "0vlfkxipcqapffs57kjy3agcqx8bpl12ypgwvmkxlrpr8lsf12p4"))))
    (properties `((upstream-name . "ConvergenceClubs")))
    (build-system r-build-system)
    (propagated-inputs (list r-sandwich r-lmtest))
    (home-page "https://CRAN.R-project.org/package=ConvergenceClubs")
    (synopsis "Finding Convergence Clubs")
    (description
     "This package provides functions for clustering regions that form convergence
clubs, according to the definition of Phillips and Sul (2009)
<doi:10.1002/jae.1080>.  A package description is available in Sichera and
Pizzuto (2019).")
    (license license:gpl3)))

(define-public r-convdistr
  (package
    (name "r-convdistr")
    (version "1.6.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "convdistr" version))
       (sha256
        (base32 "1mi5sa9lyn9pdmdlrah8fvxdzm1gqblh3r50y1g40902cryf5yds"))))
    (properties `((upstream-name . "convdistr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-shiny
                             r-shelf
                             r-rcolorbrewer
                             r-pryr
                             r-mass
                             r-ggplot2
                             r-extradistr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/johnaponte/convdistr")
    (synopsis "Convolute Probabilistic Distributions")
    (description
     "Convolute probabilistic distributions using the random generator function of
each distribution.  A new random number generator function is created that
perform the mathematical operation on the individual random samples from the
random generator function of each distribution.  See the documentation for
examples.")
    (license license:gpl3+)))

(define-public r-conttimecausal
  (package
    (name "r-conttimecausal")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "contTimeCausal" version))
       (sha256
        (base32 "0r2mg0b65xk020v0im2nzfq9644nx0ns2vddiybwz3x5c7z1bpvg"))))
    (properties `((upstream-name . "contTimeCausal")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-survival r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=contTimeCausal")
    (synopsis "Continuous Time Causal Models")
    (description
     "This package implements the semiparametric efficient estimators of
continuous-time causal models for time-varying treatments and confounders in the
presence of dependent censoring (including structural failure time model and Cox
proportional hazards marginal structural model).  S. Yang, K. Pieper, and F.
Cools (2019) <doi:10.1111/biom.12845>.")
    (license license:gpl2+)))

(define-public r-contsurvplot
  (package
    (name "r-contsurvplot")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "contsurvplot" version))
       (sha256
        (base32 "0z0s1ym9np9l8pmgbja46w25zr415laa1w68mjz04hq9wrzjjaca"))))
    (properties `((upstream-name . "contsurvplot")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-riskregression r-ggplot2 r-foreach
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/RobinDenz1/contsurvplot")
    (synopsis
     "Visualize the Effect of a Continuous Variable on a Time-to-Event Outcome")
    (description
     "Graphically display the (causal) effect of a continuous variable on a
time-to-event outcome using multiple different types of plots based on
g-computation.  Those functions include, among others, survival area plots,
survival contour plots, survival quantile plots and 3D surface plots.  Due to
the use of g-computation, all plot allow confounder-adjustment naturally.  For
details, see Robin Denz, Nina Timmesfeld (2023)
<doi:10.1097/EDE.0000000000001630>.")
    (license license:gpl3+)))

(define-public r-controltest
  (package
    (name "r-controltest")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "controlTest" version))
       (sha256
        (base32 "19r8nvi35ldzgayifskjj706fv76hv6sj68yvggybp27rgyqbjfl"))))
    (properties `((upstream-name . "controlTest")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival))
    (home-page "https://cran.r-project.org/package=controlTest")
    (synopsis
     "Quantile Comparison for Two-Sample Right-Censored Survival Data")
    (description
     "Nonparametric two-sample procedure for comparing survival quantiles.")
    (license license:gpl3)))

(define-public r-controlfunctioniv
  (package
    (name "r-controlfunctioniv")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "controlfunctionIV" version))
       (sha256
        (base32 "0g0nakc1mss7837xhs8bymy4cncljjkj7k0n4dvw44gxbc2l8j15"))))
    (properties `((upstream-name . "controlfunctionIV")))
    (build-system r-build-system)
    (propagated-inputs (list r-orthodr r-formula r-dr r-aer))
    (home-page "https://github.com/zijguo/controlfunctionIV")
    (synopsis
     "Control Function Methods with Possibly Invalid Instrumental Variables")
    (description
     "Inference with control function methods for nonlinear outcome models when the
model is known ('Guo and Small (2016) <@code{arXiv:1602.01051>}) and when
unknown but semiparametric ('Li and Guo (2021) <@code{arXiv:2010.09922>}).")
    (license license:gpl3)))

(define-public r-control
  (package
    (name "r-control")
    (version "0.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "control" version))
       (sha256
        (base32 "02s8h5kwpzfrivx3ign84gwlybkcs03ibawyxdny9zz5yhb7x3bs"))))
    (properties `((upstream-name . "control")))
    (build-system r-build-system)
    (propagated-inputs (list r-signal r-pracma r-matrix r-expm))
    (home-page "https://cran.r-project.org/package=control")
    (synopsis "Control Systems Toolbox")
    (description
     "Solves control systems problems relating to time/frequency response, LTI systems
design and analysis, transfer function manipulations, and system conversion.")
    (license license:gpl2)))

(define-public r-contribution
  (package
    (name "r-contribution")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "contribution" version))
       (sha256
        (base32 "11v179zikr3lr3zdm53zgz43vydcpg29q58qavxmhg5nl60c6581"))))
    (properties `((upstream-name . "contribution")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rlang
                             r-magrittr
                             r-gh
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/openbiox/contribution")
    (synopsis "Tiny Contribution Table Generator Based on 'ggplot2'")
    (description
     "Contribution table for credit assignment based on ggplot2'.  This can improve
the author contribution information in academic journals and personal CV.")
    (license license:expat)))

(define-public r-contresppp
  (package
    (name "r-contresppp")
    (version "0.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ContRespPP" version))
       (sha256
        (base32 "1pp5j1bwrdf5sgvrqr1xcr7asinpp4mqdx358q6v2f8096lwgd9b"))))
    (properties `((upstream-name . "ContRespPP")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jcliff89/ContRespPP")
    (synopsis
     "Predictive Probability for a Continuous Response with an ANOVA Structure")
    (description
     "This package provides a Bayesian approach to using predictive probability in an
ANOVA construct with a continuous normal response, when threshold values must be
obtained for the question of interest to be evaluated as successful (Sieck and
Christensen (2021) <doi:10.1002/qre.2802>).  The Bayesian Mission Mean (BMM) is
used to evaluate a question of interest (that is, a mean that randomly selects
combination of factor levels based on their probability of occurring instead of
averaging over the factor levels, as in the grand mean).  Under this construct,
in contrast to a Gibbs sampler (or Metropolis-within-Gibbs sampler), a two-stage
sampling method is required.  The nested sampler determines the conditional
posterior distribution of the model parameters, given Y, and the outside sampler
determines the marginal posterior distribution of Y (also commonly called the
predictive distribution for Y).  This approach provides a sample from the joint
posterior distribution of Y and the model parameters, while also accounting for
the threshold value that must be obtained in order for the question of interest
to be evaluated as successful.")
    (license license:cc0)))

(define-public r-contree
  (package
    (name "r-contree")
    (version "0.3-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conTree" version))
       (sha256
        (base32 "033rxc0sh4crilqqahypd1yhzcxa1m7q10yg7paj637f9syaxcdh"))))
    (properties `((upstream-name . "conTree")))
    (build-system r-build-system)
    (native-inputs (list r-knitr gfortran))
    (home-page "https://jhfhub.github.io/conTree_tutorial/")
    (synopsis "Contrast Trees and Boosting")
    (description
     "Contrast trees represent a new approach for assessing the accuracy of many types
of machine learning estimates that are not amenable to standard (cross)
validation methods; see \"Contrast trees and distribution boosting\", Jerome H.
Friedman (2020) <doi:10.1073/pnas.1921562117>.  In situations where inaccuracies
are detected, boosted contrast trees can often improve performance.  Functions
are provided to to build such trees in addition to a special case, distribution
boosting, an assumption free method for estimating the full probability
distribution of an outcome variable given any set of joint input predictor
variable values.")
    (license license:asl2.0)))

(define-public r-contrastable
  (package
    (name "r-contrastable")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "contrastable" version))
       (sha256
        (base32 "0m14p86rhim5lbs3fdx0hwpm87z2sjjf4a1h03cw33f68adqv773"))))
    (properties `((upstream-name . "contrastable")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-rlang
                             r-purrr
                             r-mass
                             r-glue
                             r-crayon
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/tsostarics/contrastable")
    (synopsis "Consistent Contrast Coding for Factors")
    (description
     "Quickly set and summarize contrasts for factors prior to regression analyses.
Intended comparisons, baseline conditions, and intercepts can be explicitly set
and documented without the user needing to directly manipulate matrices.
Reviews and introductions for contrast coding are available in Brehm and Alday
(2022)<doi:10.1016/j.jml.2022.104334> and Schad et al.
(2020)<doi:10.1016/j.jml.2019.104038>.")
    (license license:expat)))

(define-public r-contrast
  (package
    (name "r-contrast")
    (version "0.24.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "contrast" version))
       (sha256
        (base32 "1k7gdjmzgsw3rm90k9gpzlg4b8ma7vxamdj106b6r40q1ypaqha5"))))
    (properties `((upstream-name . "contrast")))
    (build-system r-build-system)
    (propagated-inputs (list r-sandwich r-rms r-nlme))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Alanocallaghan/contrast")
    (synopsis "Collection of Contrast Methods")
    (description
     "One degree of freedom contrasts for lm', glm', gls', and geese objects.")
    (license license:gpl2)))

(define-public r-contourplot
  (package
    (name "r-contourplot")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "contourPlot" version))
       (sha256
        (base32 "0bjwq3p57d6hadln8vwjkh7c9sbb466h3zcq9kpx7kd31z6x8gnz"))))
    (properties `((upstream-name . "contourPlot")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer r-interp))
    (home-page "https://cran.r-project.org/package=contourPlot")
    (synopsis "Plots x,y,z Co-Ordinates in a Contour Map")
    (description
     "Plots a set of x,y,z co-ordinates in a contour map.  Designed to be similar to
plots in base R so additional elements can be added using lines(), points() etc.
 This package is intended to be better suited, than existing packages, to
displaying circular shaped plots such as those often seen in the semi-conductor
industry.")
    (license license:expat)))

(define-public r-contourfunctions
  (package
    (name "r-contourfunctions")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ContourFunctions" version))
       (sha256
        (base32 "0p18zd9fq7p130b47wsbpqhgqximfmrf5pvhbzscrz2ji7rhsnmr"))))
    (properties `((upstream-name . "ContourFunctions")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmarkdown r-rlang r-lhs r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/CollinErickson/ContourFunctions")
    (synopsis "Create Contour Plots from Data or a Function")
    (description
     "This package provides functions for making contour plots.  The contour plot can
be created from grid data, a function, or a data set.  If non-grid data is
given, then a Gaussian process is fit to the data and used to create the contour
plot.")
    (license license:gpl3)))

(define-public r-contourer
  (package
    (name "r-contourer")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "contoureR" version))
       (sha256
        (base32 "1izq1alkf24zd2sf2ir2adyrkwhdj7n89cv6z0dfh5mfqld5bkdn"))))
    (properties `((upstream-name . "contoureR")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape r-rcpp r-plyr r-geometry))
    (home-page "http://contoureR.com")
    (synopsis "Contouring of Non-Regular Three-Dimensional Data")
    (description
     "Create contour lines for a non regular series of points, potentially from a
non-regular canvas.")
    (license license:gpl2+)))

(define-public r-contingencytables
  (package
    (name "r-contingencytables")
    (version "3.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "contingencytables" version))
       (sha256
        (base32 "0fy5rrwkas8rxvl08vvhxzcdddkhd3qy9fxxx0sgjw034k3fps3h"))))
    (properties `((upstream-name . "contingencytables")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-boot))
    (home-page "https://cran.r-project.org/package=contingencytables")
    (synopsis "Statistical Analysis of Contingency Tables")
    (description
     "This package provides functions to perform statistical inference of data
organized in contingency tables.  This package is a companion to the
\"Statistical Analysis of Contingency Tables\" book by Fagerland et al. <ISBN
9781466588172>.")
    (license license:gpl3)))

(define-public r-contingency
  (package
    (name "r-contingency")
    (version "0.0.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "contingency" version))
       (sha256
        (base32 "155pzw1ifm1c4pjd5wxj9lb89a6wc9l5g1v2rhq8rfswzds89gjv"))))
    (properties `((upstream-name . "contingency")))
    (build-system r-build-system)
    (propagated-inputs (list r-rje))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/rje42/contingency")
    (synopsis "Discrete Multivariate Probability Distributions")
    (description
     "This package provides an object class for dealing with many multivariate
probability distributions at once, useful for simulation.")
    (license license:gpl2)))

(define-public r-contfracr
  (package
    (name "r-contfracr")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "contFracR" version))
       (sha256
        (base32 "0yigrrs36q9wl8bla65ks1ykf233j33jwcqbhdhygryfhxp5cxab"))))
    (properties `((upstream-name . "contFracR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmpfr r-go2bigq r-gmp))
    (home-page "https://cran.r-project.org/package=contFracR")
    (synopsis "Continued Fraction Generators and Evaluators")
    (description
     "Converts numbers to continued fractions and back again.  A solver for Pell's
Equation is provided.  The method for calculating roots in continued fraction
form is provided without published attribution in such places as Professor
Emeritus Jonathan Lubin, <http://www.math.brown.edu/jlubin/> and his post to
@code{StackOverflow}, <https://math.stackexchange.com/questions/2215918> , or
Professor Ron Knott, e.g.,
<https://r-knott.surrey.ac.uk/Fibonacci/@code{cfINTRO.html>} .")
    (license license:lgpl3)))

(define-public r-context
  (package
    (name "r-context")
    (version "1.4.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conText" version))
       (sha256
        (base32 "0ahnbmpphzi2xshmsybphkc9vkj2lr2bi1jssdx97288awwcgayb"))))
    (properties `((upstream-name . "conText")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-text2vec
                             r-stringr
                             r-reshape2
                             r-quanteda
                             r-matrix
                             r-ggplot2
                             r-fastdummies
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/prodriguezsosa/EmbeddingRegression")
    (synopsis "'a la Carte' on Text (ConText) Embedding Regression")
    (description
     "This package provides a fast, flexible and transparent framework to estimate
context-specific word and short document embeddings using the a la carte
embeddings approach developed by Khodak et al. (2018) <@code{arXiv:1805.05388>}
and evaluate hypotheses about covariate effects on embeddings using the
regression framework developed by Rodriguez et al.
(2021)<https://github.com/prodriguezsosa/@code{EmbeddingRegression>}.")
    (license license:gpl3)))

(define-public r-contentid
  (package
    (name "r-contentid")
    (version "0.0.18")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "contentid" version))
       (sha256
        (base32 "1lcg7bhvkb3q0c41wlf5hmkx1nhp7h3qv5lc7jcqhsyi80aq8p2s"))))
    (properties `((upstream-name . "contentid")))
    (build-system r-build-system)
    (propagated-inputs (list r-openssl r-httr r-fs r-curl))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/cboettig/contentid")
    (synopsis "An Interface for Content-Based Identifiers")
    (description
     "An interface for creating, registering, and resolving content-based identifiers
for data management.  Content-based identifiers rely on the cryptographic hashes
to refer to the files they identify, thus, anyone possessing the file can
compute the identifier using a well-known standard algorithm, such as SHA256'.
By registering a URL at which the content is accessible to a public archive
(such as Hash Archive) or depositing data in a scientific repository such
Zenodo', @code{DataONE} or @code{SoftwareHeritage}', the content identifier can
serve many functions typically associated with A Digital Object Identifier
('DOI').  Unlike location-based identifiers like DOIs', content-based
identifiers permit the same content to be registered in many locations.")
    (license license:expat)))

(define-public r-contaminatedmixt
  (package
    (name "r-contaminatedmixt")
    (version "1.3.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ContaminatedMixt" version))
       (sha256
        (base32 "1kn1cri5wl3fwkd435sm18ipkkgxccn0q48m1wj3amw4vhg91wag"))))
    (properties `((upstream-name . "ContaminatedMixt")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-mnormt r-mixture r-mclust r-caret))
    (home-page "https://cran.r-project.org/package=ContaminatedMixt")
    (synopsis "Clustering and Classification with the Contaminated Normal")
    (description
     "Fits mixtures of multivariate contaminated normal distributions (with
eigen-decomposed scale matrices) via the expectation conditional- maximization
algorithm under a clustering or classification paradigm Methods are described in
Antonio Punzo, Angelo Mazza, and Paul D @code{McNicholas} (2018)
<doi:10.18637/jss.v085.i10>.")
    (license license:gpl2)))

(define-public r-container
  (package
    (name "r-container")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "container" version))
       (sha256
        (base32 "0vpha9s5d8mxqdzmbfy92qz78b6gfibwgp1ijq70c5vqs2clkzb1"))))
    (properties `((upstream-name . "container")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6 r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://rpahl.github.io/container/")
    (synopsis "Extending Base 'R' Lists")
    (description
     "Extends the functionality of base R lists and provides specialized data
structures deque', set', dict', and dict.table', the latter to extend the
data.table package.")
    (license license:gpl3)))

(define-public r-contactdata
  (package
    (name "r-contactdata")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "contactdata" version))
       (sha256
        (base32 "1dbh13p03md2gvgmsdrdg3b1c5fb2mi6p1jqygvw8kfw1468i1k1"))))
    (properties `((upstream-name . "contactdata")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://hugogruson.fr/contactdata/")
    (synopsis "Social Contact Matrices for 177 Countries")
    (description
     "Data package for the supplementary data in Prem et al. (2017)
<doi:10.1371/journal.pcbi.1005697> and Prem et al.
<doi:10.1371/journal.pcbi.1009098>.  Provides easy access to contact data for
177 countries, for use in epidemiological, demographic or social sciences
research.")
    (license license:expat)))

(define-public r-constructive
  (package
    (name "r-constructive")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "constructive" version))
       (sha256
        (base32 "1w75ydhpm49a4prkb9kys1866jn552i85p71y446qj7cj46m8yih"))))
    (properties `((upstream-name . "constructive")))
    (build-system r-build-system)
    (propagated-inputs (list r-waldo r-rlang r-diffobj r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/cynkra/constructive")
    (synopsis "Display Idiomatic Code to Construct Most R Objects")
    (description
     "Prints code that can be used to recreate R objects.  In a sense it is similar to
base::dput() or base::deparse() but constructive strives to use idiomatic
constructors.")
    (license license:expat)))

(define-public r-construct
  (package
    (name "r-construct")
    (version "1.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conStruct" version))
       (sha256
        (base32 "00mmlmqk3wixjycmn2wybq4vkq91jmvhjab6pyvfzk1nh3nq428i"))))
    (properties `((upstream-name . "conStruct")))
    (build-system r-build-system)
    (propagated-inputs (list r-stanheaders
                             r-rstantools
                             r-rstan
                             r-rcppparallel
                             r-rcppeigen
                             r-rcpp
                             r-gtools
                             r-foreach
                             r-doparallel
                             r-caroline
                             r-bh))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=conStruct")
    (synopsis
     "Models Spatially Continuous and Discrete Population Genetic Structure")
    (description
     "This package provides a method for modeling genetic data as a combination of
discrete layers, within each of which relatedness may decay continuously with
geographic distance.  This package contains code for running analyses (which are
implemented in the modeling language rstan') and visualizing and interpreting
output.  See the paper for more details on the model and its utility.")
    (license license:gpl3)))

(define-public r-constrainedkriging
  (package
    (name "r-constrainedkriging")
    (version "0.2-8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "constrainedKriging" version))
       (sha256
        (base32 "0qbbjb1dhdsrgpnnsfwys28xhlsy8xj35pdqrza8hih5z2vp4nq6"))))
    (properties `((upstream-name . "constrainedKriging")))
    (build-system r-build-system)
    (propagated-inputs (list r-spatialcovariance r-sp r-sf))
    (home-page "https://cran.r-project.org/package=constrainedKriging")
    (synopsis
     "Constrained, Covariance-Matching Constrained and Universal Point or Block Kriging")
    (description
     "This package provides functions for efficient computation of non-linear spatial
predictions with local change of support (Hofer, C. and Papritz, A. (2011)
\"@code{constrainedKriging}: An R-package for customary, constrained and
covariance-matching constrained point or block kriging\"
<doi:10.1016/j.cageo.2011.02.009>).  This package supplies functions for
two-dimensional spatial interpolation by constrained (Cressie, N. (1993)
\"Aggregation in geostatistical problems\" <doi:10.1007/978-94-011-1739-5_3>),
covariance-matching constrained (Aldworth, J. and Cressie, N. (2003) \"Prediction
of nonlinear spatial functionals\" <doi:10.1016/S0378-3758(02)00321-X>) and
universal (external drift) Kriging for points or blocks of any shape from data
with a non-stationary mean function and an isotropic weakly stationary
covariance function.  The linear spatial interpolation methods, constrained and
covariance-matching constrained Kriging, provide approximately unbiased
prediction for non-linear target values under change of support.  This package
extends the range of tools for spatial predictions available in R and provides
an alternative to conditional simulation for non-linear spatial prediction
problems with local change of support.")
    (license license:gpl2+)))

(define-public r-constellation
  (package
    (name "r-constellation")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "constellation" version))
       (sha256
        (base32 "1d49rnyf2z3bvx158nsmgmb0x7xcgxl9f8y98pwg5wlqck7af99q"))))
    (properties `((upstream-name . "constellation")))
    (build-system r-build-system)
    (propagated-inputs (list r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/marksendak/constellation")
    (synopsis "Identify Event Sequences Using Time Series Joins")
    (description
     "Examine any number of time series data frames to identify instances in which
various criteria are met within specified time frames.  In clinical medicine,
these types of events are often called \"constellations of signs and symptoms\",
because a single condition depends on a series of events occurring within a
certain amount of time of each other.  This package was written to work with any
number of time series data frames and is optimized for speed to work well with
data frames with millions of rows.")
    (license license:gpl2+)))

(define-public r-constants
  (package
    (name "r-constants")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "constants" version))
       (sha256
        (base32 "11nliijwphqphik95b3xpawpjg7w4s089wdhjci5bw4va4bgd1xm"))))
    (properties `((upstream-name . "constants")))
    (build-system r-build-system)
    (home-page "https://github.com/r-quantities/constants")
    (synopsis "Reference on Constants, Units and Uncertainty")
    (description
     "CODATA internationally recommended values of the fundamental physical constants,
provided as symbols for direct use within the R language.  Optionally, the
values with uncertainties and/or units are also provided if the errors', units
and/or quantities packages are installed.  The Committee on Data for Science and
Technology (CODATA) is an interdisciplinary committee of the International
Council for Science which periodically provides the internationally accepted set
of values of the fundamental physical constants.  This package contains the
\"2018 CODATA\" version, published on May 2019: Eite Tiesinga, Peter J. Mohr,
David B. Newell, and Barry N. Taylor (2020)
<https://physics.nist.gov/cuu/Constants/>.")
    (license license:expat)))

(define-public r-consreg
  (package
    (name "r-consreg")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConsReg" version))
       (sha256
        (base32 "0ck188ahzprzvqdh2q05bcg9b68dw3xiqqb1xirbm4rp5chyr419"))))
    (properties `((upstream-name . "ConsReg")))
    (build-system r-build-system)
    (propagated-inputs (list r-rsolnp
                             r-rlang
                             r-rcpp
                             r-nloptr
                             r-metrics
                             r-mcmcpack
                             r-ggplot2
                             r-gensa
                             r-ga
                             r-forecast
                             r-fme
                             r-dfoptim
                             r-deoptim
                             r-data-table
                             r-adaptmcmc))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/puigjos/ConsReg")
    (synopsis
     "Fits Regression & ARMA Models Subject to Constraints to the Coefficient")
    (description
     "Fits or generalized linear models either a regression with Autoregressive
moving-average (ARMA) errors for time series data.  The package makes it easy to
incorporate constraints into the model's coefficients.  The model is specified
by an objective function (Gaussian, Binomial or Poisson) or an ARMA order (p,q),
a vector of bound constraints for the coefficients (i.e beta1 > 0) and the
possibility to incorporate restrictions among coefficients (i.e beta1 > beta2).
The references of this packages are the same as stats package for glm() and
arima() functions.  See Brockwell, P. J. and Davis, R. A. (1996, ISBN-10:
9783319298528).  For the different optimizers implemented, it is recommended to
consult the documentation of the corresponding packages.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-consrankclass
  (package
    (name "r-consrankclass")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConsRankClass" version))
       (sha256
        (base32 "02n6a3affm72vfhsjz90jl8x0qrvxsimlm1ng313s4zla515h8ap"))))
    (properties `((upstream-name . "ConsRankClass")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlist r-proxy r-pracma r-janitor r-consrank))
    (home-page "https://www.r-project.org/")
    (synopsis "Classification and Clustering of Preference Rankings")
    (description
     "Tree-based classification and soft-clustering method for preference rankings,
with tools for external validation of fuzzy clustering.  It contains the
recursive partitioning algorithm for preference rankings, non-parametric
tree-based method for a matrix of preference rankings as a response variable.
It contains also the distribution-free soft clustering method for preference
rankings, namely the K-median cluster component analysis (CCA).  The package
depends on the @code{ConsRank} R package.  Options for validate the tree-based
method are both test-set procedure and V-fold cross validation.  The package
contains the routines to compute the adjusted concordance index (a fuzzy version
of the adjusted rand index) and the normalized degree of concordance (the
corresponding fuzzy version of the rand index).  Essential references:
D'Ambrosio, A., Amodio, S., Iorio, C., Pandolfo, G., and Siciliano, R. (2021)
<doi:10.1007/s00357-020-09367-0> D'Ambrosio, A., and Heiser, W.J. (2019)
<doi:10.1007/s41237-018-0069-5>; D'Ambrosio, A., and Heiser W.J. (2016)
<doi:10.1007/s11336-016-9505-1>; Hullermeier, E., Rifqi, M., Henzgen, S., and
Senge, R. (2012) <doi:10.1109/TFUZZ.2011.2179303>.")
    (license license:gpl3)))

(define-public r-conspline
  (package
    (name "r-conspline")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConSpline" version))
       (sha256
        (base32 "16r0v0llj0pri69jqxribp8dpzh6yn6acpq20aaky14fyh3i4q7x"))))
    (properties `((upstream-name . "ConSpline")))
    (build-system r-build-system)
    (propagated-inputs (list r-coneproj))
    (home-page "https://cran.r-project.org/package=ConSpline")
    (synopsis
     "Partial Linear Least-Squares Regression using Constrained Splines")
    (description
     "Given response y, continuous predictor x, and covariate matrix, the relationship
between E(y) and x is estimated with a shape constrained regression spline.
Function outputs fits and various types of inference.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-consortr
  (package
    (name "r-consortr")
    (version "0.9.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "consortr" version))
       (sha256
        (base32 "1c71wvr7sckrv4k65l71l160z6d9amzyydbi6mf2b79zh9zv8g1g"))))
    (properties `((upstream-name . "consortr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-shinydashboard
                             r-shiny
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-dplyr
                             r-diagrammer
                             r-data-table))
    (home-page "https://cran.r-project.org/package=consortr")
    (synopsis "Interactive Consort Flow Diagrams")
    (description
     "Shiny app for creating interactive consort flow diagrams and other types of flow
diagrams, see Moher, Schulz and Altman (2001)
<doi:10.1016/S0140-6736(00)04337-3>.")
    (license license:expat)))

(define-public r-consolechoice
  (package
    (name "r-consolechoice")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "consolechoice" version))
       (sha256
        (base32 "06xlwrjc9bj8r2ii160mclg56mw9fw2wzms3q68rcb8ril0hqvd3"))))
    (properties `((upstream-name . "consolechoice")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=consolechoice")
    (synopsis
     "An Easy and Quick Way to Loop a Character Vector as a Menu in the Console")
    (description
     "This package provides a fast way to loop a character vector or file names as a
menu in the console for the user to choose an option.")
    (license license:expat)))

(define-public r-consibiocloudclient
  (package
    (name "r-consibiocloudclient")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "consibiocloudclient" version))
       (sha256
        (base32 "09miin2w37lgga8r31yd1gk7h5gmmz0mmlvz4skr2ppnfkp9nli6"))))
    (properties `((upstream-name . "consibiocloudclient")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-httr2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=consibiocloudclient")
    (synopsis "Client for the 'Consibio Cloud' API")
    (description
     "Enable seamless interaction with Consibio Cloud <https://consibio.cloud> API
<https://api.v2.consibio.com/api-docs/>.  This package provides tools to query
data from resources like projects, elements, devices, and datalogs.")
    (license license:expat)))

(define-public r-conserver
  (package
    (name "r-conserver")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conserveR" version))
       (sha256
        (base32 "05b1pqgbd9sh4lyg9zqjfg4019dqp8xj3k1w31qqdld8m3g5lrd6"))))
    (properties `((upstream-name . "conserveR")))
    (build-system r-build-system)
    (propagated-inputs (list r-sna
                             r-scales
                             r-rlang
                             r-network
                             r-magrittr
                             r-ggrepel
                             r-ggplot2
                             r-ggally
                             r-cowplot))
    (home-page "https://github.com/azizka/conserveR")
    (synopsis
     "Identifying Conservation Prioritization Methods Based on Data Availability")
    (description
     "Helping biologists to choose the most suitable approach to link their research
to conservation.  After answering few questions on the data available,
geographic and taxonomic scope, @code{conserveR} ranks existing methods for
conservation prioritization and systematic conservation planning by suitability.
 The methods data base of @code{conserveR} contains 133 methods for conservation
prioritization based on a systematic review of > 12,000 scientific publications
from the fields of spatial conservation prioritization, systematic conservation
planning, biogeography and ecology.")
    (license license:expat)))

(define-public r-consensusopls
  (package
    (name "r-consensusopls")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConsensusOPLS" version))
       (sha256
        (base32 "1fv0a3hjqylrbqsfv7gfn33ni7cc8351shianwsp1caqjza85yr2"))))
    (properties `((upstream-name . "ConsensusOPLS")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ConsensusOPLS")
    (synopsis "Consensus OPLS for Multi-Block Data Fusion")
    (description
     "Merging data from multiple sources is a relevant approach for comprehensively
evaluating complex systems.  However, the inherent problems encountered when
analyzing single tables are amplified with the generation of multi-block
datasets, and finding the relationships between data layers of increasing
complexity constitutes a challenging task.  For that purpose, a generic
methodology is proposed by combining the strengths of established data analysis
strategies, i.e.  multi-block approaches and the Orthogonal Partial Least
Squares (OPLS) framework to provide an efficient tool for the fusion of data
obtained from multiple sources.  The package enables quick and efficient
implementation of the consensus OPLS model for any horizontal multi-block data
structure (observation-based matching).  Moreover, it offers an interesting
range of metrics and graphics to help to determine the optimal number of
components and check the validity of the model through permutation tests.
Interpretation tools include scores and loadings plots, as well as Variable
Importance in Projection (VIP), and performance coefficients such as R2, Q2 and
DQ2 coefficients.  J. Boccard and D.N. Rutledge (2013)
<doi:10.1016/j.aca.2013.01.022>.")
    (license license:gpl3+)))

(define-public r-consensusclustering
  (package
    (name "r-consensusclustering")
    (version "1.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConsensusClustering" version))
       (sha256
        (base32 "0l9xc39zbxqiq5z9n8qxgwq19hx5n72vq1vyz98dy79p7wrl10nv"))))
    (properties `((upstream-name . "ConsensusClustering")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-igraph r-dplyr r-cluster r-assertthat))
    (home-page "https://cran.r-project.org/package=ConsensusClustering")
    (synopsis "Consensus Clustering")
    (description
     "Clustering, or cluster analysis, is a widely used technique in bioinformatics to
identify groups of similar biological data points.  Consensus clustering is an
extension to clustering algorithms that aims to construct a robust result from
those clustering features that are invariant under different sources of
variation.  For the reference, please cite the following paper: Yousefi,
Melograna, et.  al., (2023) <doi:10.3389/fmicb.2023.1170391>.")
    (license license:gpl3+)))

(define-public r-conrad
  (package
    (name "r-conrad")
    (version "1.0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conrad" version))
       (sha256
        (base32 "19ya71qn898rfrbn5v72dhawsr56b29k3nw9zx096rr6iqws023p"))))
    (properties `((upstream-name . "conrad")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-jsonlite r-httr2))
    (home-page "https://github.com/fhdsl/conrad")
    (synopsis
     "Client for the Microsoft's 'Cognitive Services Text to Speech REST' API")
    (description
     "Convert text into synthesized speech and get a list of supported voices for a
region.  Microsoft's Cognitive Services Text to Speech REST API
<https://learn.microsoft.com/en-us/azure/cognitive-services/speech-service/rest-text-to-speech?tabs=streaming>
supports neural text to speech voices, which support specific languages and
dialects that are identified by locale.")
    (license license:expat)))

(define-public r-conquestr
  (package
    (name "r-conquestr")
    (version "1.3.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conquestr" version))
       (sha256
        (base32 "12l311bggayxkab5ljkw35qm02m3gzlvrn88a7ka1gs7if4q0d7v"))))
    (properties `((upstream-name . "conquestr")))
    (build-system r-build-system)
    (propagated-inputs (list r-zlib
                             r-tidyselect
                             r-tidyr
                             r-stringr
                             r-rlang
                             r-rcpp
                             r-magrittr
                             r-kableextra
                             r-ggrepel
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://www.acer.org/au/conquest")
    (synopsis "An R Package to Extend 'ACER ConQuest'")
    (description
     "Extends ACER @code{ConQuest} through a family of functions designed to improve
graphical outputs and help with advanced analysis (e.g., differential item
functioning).  Allows R users to call ACER @code{ConQuest} from within R and
read ACER @code{ConQuest} System Files (generated by the command `put`
<https://conquestmanual.acer.org/s4-00.html#put>).  Requires ACER
@code{ConQuest} version 5.39 or later.  A demonstration version can be
downloaded from <https://shop.acer.org/acer-conquest-5.html>.")
    (license license:gpl3)))

(define-public r-conover-test
  (package
    (name "r-conover-test")
    (version "1.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conover.test" version))
       (sha256
        (base32 "0x0wzxdg4pkkr5yqrapvq04i1gc7qa6c7f44skcmq3qpfziq3fpj"))))
    (properties `((upstream-name . "conover.test")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=conover.test")
    (synopsis "Conover-Iman Test of Multiple Comparisons Using Rank Sums")
    (description
     "Computes the Conover-Iman test (1979) for 0th-order stochastic dominance and
reports the results among multiple pairwise comparisons after a Kruskal-Wallis
omnibus test for i0th-order stochastic dominance among k groups (Kruskal and
Wallis, 1952).  conover.test makes k(k-1)/2 multiple pairwise comparisons based
on Conover-Iman t-test-statistic of the rank differences.  The null hypothesis
for each pairwise comparison is that the probability of observing a randomly
selected value from the first group that is larger than a randomly selected
value from the second group equals one half; this null hypothesis corresponds to
that of the Wilcoxon-Mann-Whitney rank-sum test.  Like the rank-sum test, if the
data can be assumed to be continuous, and the distributions are assumed
identical except for a difference in location, Conover-Iman test may be
understood as a test for median difference and for mean difference.
conover.test accounts for tied ranks.  The Conover-Iman test is strictly valid
if and only if the corresponding Kruskal-Wallis null hypothesis is rejected.")
    (license license:gpl2)))

(define-public r-conogive
  (package
    (name "r-conogive")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conogive" version))
       (sha256
        (base32 "0a8v7v0fds0psfnbx9x45way8z1f1xn2ncgbrn5rb6fjq0a1zs4x"))))
    (properties `((upstream-name . "conogive")))
    (build-system r-build-system)
    (propagated-inputs (list r-psych r-mvtnorm r-checkmate r-assertthat))
    (home-page "https://github.com/JonasMoss/conogive")
    (synopsis "Congeneric Normal-Ogive Model")
    (description
     "The congeneric normal-ogive model is a popular model for psychometric data
(@code{McDonald}, R. P. (1997) <doi:10.1007/978-1-4757-2691-6_15>).  This model
estimates the model, calculates theoretical and concrete reliability
coefficients, and predicts the latent variable of the model.  This is the
companion package to Moss (2020) <doi:10.31234/osf.io/nvg5d>.")
    (license license:expat)))

(define-public r-connmattools
  (package
    (name "r-connmattools")
    (version "0.3.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConnMatTools" version))
       (sha256
        (base32 "082y4xxnp42xa7db5hnbc9qlvkb50wwb3wzi0my04l55a9s0ril7"))))
    (properties `((upstream-name . "ConnMatTools")))
    (build-system r-build-system)
    (home-page "https://github.com/dmkaplan2000/ConnMatTools.git")
    (synopsis "Tools for Working with Connectivity Data")
    (description
     "Collects several different methods for analyzing and working with connectivity
data in R. Though primarily oriented towards marine larval dispersal, many of
the methods are general and useful for terrestrial systems as well.")
    (license license:gpl2+)))

(define-public r-connectwidgets
  (package
    (name "r-connectwidgets")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "connectwidgets" version))
       (sha256
        (base32 "0lgr36699hnjwkjx56akwwnzkl5qm587yhqamxr6a53nh1j3h11y"))))
    (properties `((upstream-name . "connectwidgets")))
    (build-system r-build-system)
    (arguments
     (list
      #:modules '((guix build r-build-system)
                  (guix build minify-build-system)
                  (guix build utils)
                  (ice-9 match))
      #:imported-modules `(,@%r-build-system-modules (guix build
                                                      minify-build-system))
      #:phases '(modify-phases %standard-phases
                  (add-after 'unpack 'process-javascript
                    (lambda* (#:key inputs #:allow-other-keys)
                      (with-directory-excursion "inst/"
                        (for-each (match-lambda
                                    ((source . target) (minify source
                                                               #:target target)))
                                  '())))))))
    (propagated-inputs (list r-tibble
                             r-sass
                             r-rlang
                             r-reactr
                             r-reactable
                             r-r6
                             r-purrr
                             r-magrittr
                             r-jsonlite
                             r-httr
                             r-htmlwidgets
                             r-htmltools
                             r-glue
                             r-dplyr
                             r-digest
                             r-crosstalk
                             r-bslib))
    (native-inputs (list r-knitr esbuild))
    (home-page "https://rstudio.github.io/connectwidgets/")
    (synopsis "Organize and Curate Your Content Within 'Posit Connect'")
    (description
     "This package provides a collection of helper functions and htmlwidgets to help
publishers curate content collections on Posit Connect'.  The components, Card,
Grid, Table, Search, and Filter can be used to produce a showcase page or
gallery contained within a static or interactive R Markdown page.")
    (license license:expat)))

(define-public r-connectomoda
  (package
    (name "r-connectomoda")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "connectoModa" version))
       (sha256
        (base32 "0gnmrx6li9yx231nn73m921sp8wwxrd9pbmni37gsqjj7lcyglp8"))))
    (properties `((upstream-name . "connectoModa")))
    (build-system r-build-system)
    (propagated-inputs (list r-readr r-jsonlite r-httr))
    (home-page "https://cran.r-project.org/package=connectoModa")
    (synopsis "Download Data from Moda")
    (description
     "Connect to WFP's Moda platform to R, download data, and obtain the list of
individuals with access to the project along with their access level.")
    (license license:expat)))

(define-public r-connections
  (package
    (name "r-connections")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "connections" version))
       (sha256
        (base32 "1hqsp5y32n0v5rij86clk3wmghc32zh9h3s6pjn0yjjsg3v1bvf6"))))
    (properties `((upstream-name . "connections")))
    (build-system r-build-system)
    (propagated-inputs (list r-uuid
                             r-rscontract
                             r-pins
                             r-dplyr
                             r-dbplyr
                             r-dbi))
    (home-page "https://github.com/rstudio/connections")
    (synopsis "Integrates with the 'RStudio' Connections Pane and 'pins'")
    (description
     "Enables DBI compliant packages to integrate with the RStudio connections pane,
and the pins package.  It automates the display of schemata, tables, views, as
well as the preview of the table's top 1000 records.")
    (license license:expat)))

(define-public r-connectednessapproach
  (package
    (name "r-connectednessapproach")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConnectednessApproach" version))
       (sha256
        (base32 "1vbnj2r4x8pfzdagky33xz9kpb23d7vz5ddgms8fp15zjilsz2nw"))))
    (properties `((upstream-name . "ConnectednessApproach")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-xts
                             r-urca
                             r-rugarch
                             r-rmgarch
                             r-riskparityportfolio
                             r-quantreg
                             r-progress
                             r-performanceanalytics
                             r-moments
                             r-mass
                             r-l1pack
                             r-igraph
                             r-glmnet
                             r-frequencyconnectedness
                             r-car))
    (home-page "https://cran.r-project.org/package=ConnectednessApproach")
    (synopsis "Connectedness Approach")
    (description
     "The estimation of static and dynamic connectedness measures is created in a
modular and user-friendly way.  Besides, the time domain connectedness
approaches, this package further allows to estimate the frequency connectedness
approach, the joint spillover index and the extended joint connectedness
approach.  In addition, all connectedness frameworks can be based upon
orthogonalized and generalized VAR, QVAR, LASSO VAR, Ridge VAR, Elastic Net VAR
and TVP-VAR models.  Furthermore, the package includes the conditional,
decomposed and partial connectedness measures as well as the pairwise
connectedness index, influence index and corrected total connectedness index.
Finally, a battery of datasets are available allowing to replicate a variety of
connectedness papers.")
    (license license:gpl3)))

(define-public r-connectapi
  (package
    (name "r-connectapi")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "connectapi" version))
       (sha256
        (base32 "02vrsfwzwsr0nnb26yp1bfgjzl7cgwdakl1m0gp6s4zirg9nhj9d"))))
    (properties `((upstream-name . "connectapi")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-uuid
                             r-tibble
                             r-rlang
                             r-r6
                             r-purrr
                             r-magrittr
                             r-lifecycle
                             r-jsonlite
                             r-httr
                             r-glue
                             r-fs
                             r-bit64))
    (native-inputs (list r-knitr))
    (home-page "https://pkgs.rstudio.com/connectapi/")
    (synopsis "Utilities for Interacting with the 'Posit Connect' Server API")
    (description
     "This package provides a helpful R6 class and methods for interacting with the
Posit Connect Server API along with some meaningful utility functions for
regular tasks.  API documentation varies by Posit Connect installation and
version, but the latest documentation is also hosted publicly at
<https://docs.posit.co/connect/api/>.")
    (license license:expat)))

(define-public r-connect
  (package
    (name "r-connect")
    (version "0.7.27")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConNEcT" version))
       (sha256
        (base32 "1j66qmvgm9yrgnrcg600s25haq9imcshmy6fv9vd84mhy21md85h"))))
    (properties `((upstream-name . "ConNEcT")))
    (build-system r-build-system)
    (propagated-inputs (list r-qgraph))
    (home-page "https://cran.r-project.org/package=ConNEcT")
    (synopsis "Contingency Measure-Based Networks for Binary Time Series")
    (description
     "The @code{ConNEcT} approach investigates the pairwise association strength of
binary time series by calculating contingency measures and depicts the results
in a network.  The package includes features to explore and visualize the data.
To calculate the pairwise concurrent or temporal sequenced relationship between
the variables, the package provides seven contingency measures (proportion of
agreement, classical & corrected Jaccard, Cohen's kappa, phi correlation
coefficient, odds ratio, and log odds ratio), however, others can easily be
implemented.  The package also includes non-parametric significance tests, that
can be applied to test whether the contingency value quantifying the
relationship between the variables is significantly higher than chance level.
Most importantly this test accounts for auto-dependence and relative
frequency.See Bodner et al.(2021) <doi: 10.1111/bmsp.12222>.Finally, a network
can be drawn.  Variables depicted the nodes of the network, with the node size
adapted to the prevalence.  The association strength between the variables
defines the undirected (concurrent) or directed (temporal sequenced) links
between the nodes.  The results of the non-parametric significance test can be
included by depicting either all links or only the significant ones.  Tutorial
see Bodner et al.(2021) <doi:10.3758/s13428-021-01760-w>.")
    (license license:gpl2+)))

(define-public r-conmet
  (package
    (name "r-conmet")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conmet" version))
       (sha256
        (base32 "0iwr8mmh9lk0psqxkgnd7ldhg57ivbkv0b3a18gli06983mhzjdc"))))
    (properties `((upstream-name . "conmet")))
    (build-system r-build-system)
    (propagated-inputs (list r-waiter
                             r-summarytools
                             r-stringr
                             r-shinywidgets
                             r-shinydashboard
                             r-shiny
                             r-semtools
                             r-purrr
                             r-openxlsx
                             r-lavaan
                             r-hmisc
                             r-foreign
                             r-dt
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=conmet")
    (synopsis "Construct Measurement Evaluation Tool")
    (description
     "With this package you can run @code{ConMET} locally in R. @code{ConMET} is an
R-shiny application that facilitates performing and evaluating confirmatory
factor analyses (CFAs) and is useful for running and reporting typical
measurement models in applied psychology and management journals. @code{ConMET}
automatically creates, compares and summarizes CFA models.  Most common fit
indices (E.g., CFI and SRMR) are put in an overview table. @code{ConMET} also
allows to test for common method variance.  The application is particularly
useful for teaching and instruction of measurement issues in survey research.
The application uses the lavaan package (Rosseel, 2012) to run CFAs.")
    (license license:gpl3)))

(define-public r-conleyreg
  (package
    (name "r-conleyreg")
    (version "0.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conleyreg" version))
       (sha256
        (base32 "1mvbzqd83vd54ig4kbi1v3h4v0j6pyj8a5ja1f3w2n7k8aszy748"))))
    (properties `((upstream-name . "conleyreg")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf
                             r-s2
                             r-rdpack
                             r-rcpparmadillo
                             r-rcpp
                             r-matrix
                             r-lwgeom
                             r-lmtest
                             r-foreach
                             r-fixest
                             r-doparallel
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=conleyreg")
    (synopsis "Estimations using Conley Standard Errors")
    (description
     "This package provides functions calculating Conley (1999)
<doi:10.1016/S0304-4076(98)00084-0> standard errors.  The package started by
merging and extending multiple packages and other published scripts on this
econometric technique.  It strongly emphasizes computational optimization.
Details are available in the function documentation and in the vignette.")
    (license license:expat)))

(define-public r-conjurer
  (package
    (name "r-conjurer")
    (version "1.7.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conjurer" version))
       (sha256
        (base32 "09ypjh8dlf8if9a2fb1sgzp5ds68vr5krk7fk7rhwi16lpxykwh9"))))
    (properties `((upstream-name . "conjurer")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr))
    (native-inputs (list r-knitr))
    (home-page
     "https://www.foyi.co.nz/posts/documentation/documentationconjurer/")
    (synopsis "Parametric Method for Generating Synthetic Data")
    (description
     "Generates synthetic data distributions to enable testing various modelling
techniques in ways that real data does not allow.  Noise can be added in a
controlled manner such that the data seems real.  This methodology is generic
and therefore benefits both the academic and industrial research.")
    (license license:expat)))

(define-public r-conjoint
  (package
    (name "r-conjoint")
    (version "1.41")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conjoint" version))
       (sha256
        (base32 "1iq3226a6fn1gddmh2nxlzvjcvbj7502r9520g9d4xdmk8smfx33"))))
    (properties `((upstream-name . "conjoint")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2
                             r-ggfortify
                             r-fpc
                             r-cluster
                             r-broom
                             r-algdesign))
    (home-page "www.r-project.org")
    (synopsis "An Implementation of Conjoint Analysis Method")
    (description
     "This is a simple R package that allows to measure the stated preferences using
traditional conjoint analysis method.")
    (license license:gpl2+)))

(define-public r-conigrave
  (package
    (name "r-conigrave")
    (version "0.4.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Conigrave" version))
       (sha256
        (base32 "02nvk5ya9gr06ai8qnjw0xq6hfbrr91b6lx9gq08dbrnmpbmyvqz"))))
    (properties `((upstream-name . "Conigrave")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-stringdist
                             r-ppcor
                             r-mitools
                             r-miceadds
                             r-ggplot2
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=Conigrave")
    (synopsis "Flexible Tools for Multiple Imputation")
    (description
     "This package provides a set of tools that can be used across data.frame and
@code{imputationList} objects.")
    (license license:gpl3)))

(define-public r-conicfit
  (package
    (name "r-conicfit")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conicfit" version))
       (sha256
        (base32 "1d704xgiyqmbwfxnsmhqg885x10q8yqxmrk4khqpg3lh696bw97d"))))
    (properties `((upstream-name . "conicfit")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma r-geigen))
    (home-page "https://cran.r-project.org/package=conicfit")
    (synopsis
     "Algorithms for Fitting Circles, Ellipses and Conics Based on the Work by Prof. Nikolai Chernov")
    (description
     "Geometric circle fitting with Levenberg-Marquardt (a, b, R), Levenberg-Marquardt
reduced (a, b), Landau, Spath and Chernov-Lesort.  Algebraic circle fitting with
Taubin, Kasa, Pratt and Fitzgibbon-Pilu-Fisher.  Geometric ellipse fitting with
ellipse LMG (geometric parameters) and conic LMA (algebraic parameters).
Algebraic ellipse fitting with Fitzgibbon-Pilu-Fisher and Taubin.")
    (license license:gpl3+)))

(define-public r-coni
  (package
    (name "r-coni")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoNI" version))
       (sha256
        (base32 "19nyn4gh4bnrvbbh2df8459015fkb2bgwwmq17vqq7r2j4gkgxzh"))))
    (properties `((upstream-name . "CoNI")))
    (build-system r-build-system)
    (inputs (list python-3))
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-rlang
                             r-ppcor
                             r-plyr
                             r-igraph
                             r-hmisc
                             r-gridextra
                             r-gplots
                             r-ggrepel
                             r-ggplot2
                             r-genefilter
                             r-foreach
                             r-forcats
                             r-dplyr
                             r-doparallel
                             r-data-table
                             r-cocor))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CoNI")
    (synopsis "Correlation Guided Network Integration (CoNI)")
    (description
     "Integrates two numerical omics data sets from the same samples using partial
correlations.  The output can be represented as a network, bipartite graph or a
hypergraph structure.  The method used in the package refers to Klaus et al
(2021) <doi:10.1016/j.molmet.2021.101295>.")
    (license license:gpl3)))

(define-public r-congrevelamsdell2016
  (package
    (name "r-congrevelamsdell2016")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CongreveLamsdell2016" version))
       (sha256
        (base32 "06vfcl65zn3xwpai33xxmp54r5hny8cr18ad3w8laa6fii5rfyhb"))))
    (properties `((upstream-name . "CongreveLamsdell2016")))
    (build-system r-build-system)
    (propagated-inputs (list r-ternary))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ms609/CongreveLamsdell2016")
    (synopsis "Distance Metrics for Trees Generated by Congreve and Lamsdell")
    (description
     "Includes the 100 datasets simulated by Congreve and Lamsdell (2016)
<doi:10.1111/pala.12236>, and analyses of the partition and quartet distance of
reconstructed trees from the generative tree, as analysed by Smith (2019)
<doi:10.1098/rsbl.2018.0632>.")
    (license license:gpl2+)))

(define-public r-congressdata
  (package
    (name "r-congressdata")
    (version "1.5.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CongressData" version))
       (sha256
        (base32 "0hbsbszcwj81p2jnsh9k3ggnn2l0xvj0yk0c9fvqnlqhm07zm3l1"))))
    (properties `((upstream-name . "CongressData")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-stringr
                             r-rlang
                             r-fst
                             r-dplyr
                             r-curl))
    (home-page "https://cran.r-project.org/package=CongressData")
    (synopsis "Functional Tool for 'CongressData'")
    (description
     "This package provides a tool that imports, subsets, and exports the
@code{CongressData} dataset. @code{CongressData} contains approximately 800
variables concerning all US congressional districts with data back to 1789.  The
dataset tracks district characteristics, members of Congress, and the political
behavior of those members.  Users with only a basic understanding of R can
subset this data across multiple dimensions, export their search results,
identify the citations associated with their searches, and more.")
    (license license:gpl3)))

(define-public r-congress
  (package
    (name "r-congress")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "congress" version))
       (sha256
        (base32 "12q3424gmam0fcnagbdbxgmrhlsc363frv2qyvh6vn0vkipv0y4y"))))
    (properties `((upstream-name . "congress")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-purrr
                             r-lifecycle
                             r-httr2
                             r-glue
                             r-dplyr
                             r-cli))
    (home-page "https://github.com/christopherkenny/congress")
    (synopsis "Access the Congress.gov API")
    (description
     "Download and read data on United States congressional proceedings.  Data is read
from the Library of Congress's Congress.gov Application Programming Interface
(<https://github.com/@code{LibraryOfCongress/api.congress.gov/>}).  Functions
exist for all version 3 endpoints, including for bills, amendments, congresses,
summaries, members, reports, communications, nominations, and treaties.")
    (license license:expat)))

(define-public r-confzic
  (package
    (name "r-confzic")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConfZIC" version))
       (sha256
        (base32 "0x9933zirfdkg2ljm3kk1nalk9ri0rrqi11q07dkyh78p4w9lmsp"))))
    (properties `((upstream-name . "ConfZIC")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidytable
                             r-psych
                             r-mvtnorm
                             r-mumin
                             r-ltsa
                             r-cmna))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ConfZIC")
    (synopsis
     "Confidence Envelopes for Model Selection Criteria Based on Minimum ZIC")
    (description
     "Narrow down the number of models to look at in model selection using the
confidence envelopes based on the minimum ZIC (Generalized Information Criteria)
values for regression and time series data.  Functions involve the computation
of multivariate normal-probabilities with covariance matrices based on minimum
ZIC inverting the CDF of the minimum ZIC. It involves both the computation of
singular and non-singular probabilities as described in Genz (1992)
<[https:doi.org/10.2307/1390838]https:doi.org/10.2307/1390838>.")
    (license license:gpl2)))

(define-public r-confusiontabler
  (package
    (name "r-confusiontabler")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConfusionTableR" version))
       (sha256
        (base32 "1qyw4shzgaaqmcn6yb52xaxrfwrji980j87baz4ngzckd60n77fi"))))
    (properties `((upstream-name . "ConfusionTableR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-purrr
                             r-magrittr
                             r-furrr
                             r-dplyr
                             r-caret))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ConfusionTableR")
    (synopsis "Confusion Matrix Toolset")
    (description
     "Takes the outputs of a caret confusion matrix and allows for the quick
conversion of these list items to lists.  The intended usage is to allow the
tool to work with the outputs of machine learning classification models.  This
tool works with classification problems for binary and multi-classification
problems and allows for the record level conversion of the confusion matrix
outputs.  This is useful, as it allows quick conversion of these objects for
storage in database systems and to track ML model performance over time.
Traditionally, this approach has been used for highlighting model representation
and feature slippage.")
    (license license:expat)))

(define-public r-confsam
  (package
    (name "r-confsam")
    (version "0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "confSAM" version))
       (sha256
        (base32 "1l67ndya07hh0yqfbabfhsvp3hryklx0022grpr0cb7ff88d1zam"))))
    (properties `((upstream-name . "confSAM")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=confSAM")
    (synopsis
     "Estimates and Bounds for the False Discovery Proportion, by Permutation")
    (description
     "For multiple testing.  Computes estimates and confidence bounds for the False
Discovery Proportion (FDP), the fraction of false positives among all rejected
hypotheses.  The methods in the package use permutations of the data.  Doing so,
they take into account the dependence structure in the data.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-confreq
  (package
    (name "r-confreq")
    (version "1.6.1-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "confreq" version))
       (sha256
        (base32 "05bwsj4xa3k7gngnf3ni8j0qw7yd7iycqkarpxm60dy8ayy68bs8"))))
    (properties `((upstream-name . "confreq")))
    (build-system r-build-system)
    (propagated-inputs (list r-vcd r-gmp))
    (home-page "https://cran.r-project.org/package=confreq")
    (synopsis "Configural Frequencies Analysis Using Log-Linear Modeling")
    (description
     "Offers several functions for Configural Frequencies Analysis (CFA), which is a
useful statistical tool for the analysis of multiway contingency tables.  CFA
was introduced by G. A. Lienert as Konfigurations Frequenz Analyse - KFA'.
Lienert, G. A. (1971).  Die Konfigurationsfrequenzanalyse: I. Ein neuer Weg zu
Typen und Syndromen.  Zeitschrift fÃ¼r Klinische Psychologie und Psychotherapie,
19(2), 99â115.")
    (license license:gpl3)))

(define-public r-conformalsmallest
  (package
    (name "r-conformalsmallest")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConformalSmallest" version))
       (sha256
        (base32 "0r74hbz0dmz69zsw2vdl858vj27p6f2xcpv1l1il4r52cmshg1h8"))))
    (properties `((upstream-name . "ConformalSmallest")))
    (build-system r-build-system)
    (propagated-inputs (list r-quantregforest r-mvtnorm r-mass r-glmnet))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Elsa-Yang98/ConformalSmallest")
    (synopsis "Efficient Tuning-Free Conformal Prediction")
    (description
     "An implementation of efficiency first conformal prediction (EFCP) and validity
first conformal prediction (VFCP) that demonstrates both validity (coverage
guarantee) and efficiency (width guarantee).  To learn how to use it, check the
vignettes for a quick tutorial.  The package is based on the work by Yang Y.,
Kuchibhotla A.,(2021) <arxiv:2104.13871>.")
    (license license:gpl3+)))

(define-public r-conformalpvalue
  (package
    (name "r-conformalpvalue")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conformalpvalue" version))
       (sha256
        (base32 "1hhx305jl75alp3fp2h7nwp4y80jyg8npbfmns774bnxgp2gwab8"))))
    (properties `((upstream-name . "conformalpvalue")))
    (build-system r-build-system)
    (propagated-inputs (list r-e1071))
    (home-page "https://cran.r-project.org/package=conformalpvalue")
    (synopsis "Computes Conformal p-Values")
    (description
     "Computes marginal conformal p-values using conformal prediction in binary
classification tasks.  Conformal prediction is a framework that augments machine
learning algorithms with a measure of uncertainty, in the form of prediction
regions that attain a user-specified level of confidence.  This package
specifically focuses on providing conformal p-values that can be used to assess
the confidence of the classification predictions.  For more details, see Tyagi
and Guo (2023) <https://proceedings.mlr.press/v204/tyagi23a.html>.")
    (license license:expat)))

(define-public r-conformalinference-multi
  (package
    (name "r-conformalinference-multi")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conformalInference.multi" version))
       (sha256
        (base32 "1xc879ygv9avamy29a6rdfb6pknaz82f3k6392c8a90sgfn3bx3d"))))
    (properties `((upstream-name . "conformalInference.multi")))
    (build-system r-build-system)
    (propagated-inputs (list r-hrbrthemes
                             r-gridextra
                             r-glmnet
                             r-ggplot2
                             r-future-apply
                             r-future))
    (home-page "https://github.com/ryantibs/conformal")
    (synopsis
     "Conformal Inference Tools for Regression with Multivariate Response")
    (description
     "It computes full conformal, split conformal and multi split conformal prediction
regions when the response variable is multivariate (i.e.  dimension is greater
than one).  Moreover, the package also contain plot functions to visualize the
output of the full and split conformal functions.  To guarantee consistency, the
package structure mimics the univariate @code{conformalInference} package of
professor Ryan Tibshirani.  The main references for the code are: Lei et al.
(2016) <@code{arXiv:1604.04173>}, Diquigiovanni, Fontana, and Vantini (2021)
<@code{arXiv:2102.06746>}, Diquigiovanni, Fontana, and Vantini (2021)
<@code{arXiv:2106.01792>}, Solari, and Djordjilovic (2021)
<@code{arXiv:2103.00627>}.")
    (license license:gpl2)))

(define-public r-conformalinference-fd
  (package
    (name "r-conformalinference-fd")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conformalInference.fd" version))
       (sha256
        (base32 "08r669apkiyjydz9yy9pdiy9rl2wyg50bypvsm9w5i1aryzgmadr"))))
    (properties `((upstream-name . "conformalInference.fd")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales
                             r-ggpubr
                             r-ggplot2
                             r-ggnewscale
                             r-future-apply
                             r-future
                             r-fda))
    (home-page "https://github.com/ryantibs/conformal")
    (synopsis
     "Tools for Conformal Inference for Regression in Multivariate Functional Setting")
    (description
     "It computes full conformal, split conformal and multi split conformal prediction
regions when the response has functional nature.  Moreover, the package also
contain a plot function to visualize the output of the split conformal.  To
guarantee consistency, the package structure mimics the univariate
@code{conformalInference} package of professor Ryan Tibshirani.  The main
references for the code are: Diquigiovanni, Fontana, and Vantini (2021)
<@code{arXiv:2102.06746>}, Diquigiovanni, Fontana, and Vantini (2021)
<@code{arXiv:2106.01792>}, Solari, and Djordjilovic (2021)
<@code{arXiv:2103.00627>}.")
    (license license:gpl2)))

(define-public r-conformalclassification
  (package
    (name "r-conformalclassification")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conformalClassification" version))
       (sha256
        (base32 "03v6xbgipb97byarqj0d38z9yb2g54mkkw343jxmi2j058z26yw7"))))
    (properties `((upstream-name . "conformalClassification")))
    (build-system r-build-system)
    (propagated-inputs (list r-randomforest r-mlbench r-foreach r-doparallel))
    (home-page "https://cran.r-project.org/package=conformalClassification")
    (synopsis
     "Transductive and Inductive Conformal Predictions for Classification Problems")
    (description
     "Implementation of transductive conformal prediction (see Vovk, 2013,
<doi:10.1007/978-3-642-41142-7_36>) and inductive conformal prediction (see
Balasubramanian et al., 2014, ISBN:9780124017153) for classification problems.")
    (license license:gpl3)))

(define-public r-conformalbayes
  (package
    (name "r-conformalbayes")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conformalbayes" version))
       (sha256
        (base32 "0pl1ajix5v3zckny5angk1rqnalln4agf65yrdva210zl6wp7fzm"))))
    (properties `((upstream-name . "conformalbayes")))
    (build-system r-build-system)
    (propagated-inputs (list r-rstantools r-matrixstats r-loo r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/CoryMcCartan/conformalbayes")
    (synopsis "Jackknife(+) Predictive Intervals for Bayesian Models")
    (description
     "This package provides functions to construct finite-sample calibrated predictive
intervals for Bayesian models, following the approach in Barber et al. (2021)
<doi:10.1214/20-AOS1965>.  These intervals are calculated efficiently using
importance sampling for the leave-one-out residuals.  By default, the intervals
will also reflect the relative uncertainty in the Bayesian model, using the
locally-weighted conformal methods of Lei et al. (2018)
<doi:10.1080/01621459.2017.1307116>.")
    (license license:expat)))

(define-public r-conflr
  (package
    (name "r-conflr")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conflr" version))
       (sha256
        (base32 "1bjdmvi0n8746g7dxwgzh3fi33sq4bgfr0nd3nqd2caj8ryi2gv9"))))
    (properties `((upstream-name . "conflr")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-stringi
                             r-shiny
                             r-rstudioapi
                             r-rmarkdown
                             r-rlang
                             r-r6
                             r-purrr
                             r-miniui
                             r-knitr
                             r-httr
                             r-glue
                             r-curl
                             r-commonmark
                             r-askpass))
    (home-page "https://line.github.io/conflr/")
    (synopsis "Client for 'Confluence' API")
    (description
     "This package provides utilities for working with various Confluence API
<https://docs.atlassian.com/@code{ConfluenceServer/rest/latest/>}, including a
functionality to convert an R Markdown document to Confluence format and upload
it to Confluence automatically.")
    (license license:gpl3)))

(define-public r-confintvariance
  (package
    (name "r-confintvariance")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConfIntVariance" version))
       (sha256
        (base32 "0xm3vh3vmf16faa3934100rnrg4rvlqkgjlsqa2smzcvy5vb86z4"))))
    (properties `((upstream-name . "ConfIntVariance")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ConfIntVariance")
    (synopsis
     "Confidence Interval for the Univariate Population Variance without Normality Assumption")
    (description
     "Surrounds the usual sample variance of a univariate numeric sample with a
confidence interval for the population variance.  This has been done so far only
under the assumption that the underlying distribution is normal.  Under the
hood, this package implements the unique least-variance unbiased estimator of
the variance of the sample variance, in a formula that is equivalent to
estimating kurtosis and square of the population variance in an unbiased way and
combining them according to the classical formula into an estimator of the
variance of the sample variance.  Both the sample variance and the estimator of
its variance are U-statistics.  By the theory of U-statistic, the resulting
estimator is unique.  See Fuchs, Krautenbacher (2016)
<doi:10.1080/15598608.2016.1158675> and the references therein for an overview
of unbiased estimation of variances of U-statistics.")
    (license license:gpl3)))

(define-public r-confintrob
  (package
    (name "r-confintrob")
    (version "1.0-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "confintROB" version))
       (sha256
        (base32 "13fbq4zxs90sy49c55b9i2i8yq3g3p4p45cx30rs7yrb3610zkfb"))))
    (properties `((upstream-name . "confintROB")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-mvtnorm r-mass r-lme4 r-foreach))
    (home-page "https://cran.r-project.org/package=confintROB")
    (synopsis
     "Confidence Intervals for Robust and Classical Linear Mixed Model Estimators")
    (description
     "The main function calculates confidence intervals (CI) for Mixed Models,
utilizing both classical estimators from the lmer() function in the lme4 package
and robust estimators from the rlmer() function in the robustlmm package, as
well as the @code{varComprob}() function in the @code{robustvarComp} package.
Three methods are available: the classical Wald method, the wild bootstrap, and
the parametric bootstrap.  Bootstrap methods offer flexibility in obtaining
lower and upper bounds through percentile or BCa methods.  More details are
given in Mason, F., Cantoni, E., & Ghisletta, P. (2021) <doi:10.5964/meth.6607>
and Mason, F., Cantoni, E., & Ghisletta, P. (2024) <doi:10.1037/met0000643>.")
    (license license:gpl2)))

(define-public r-confinterpret
  (package
    (name "r-confinterpret")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "confinterpret" version))
       (sha256
        (base32 "0qldaqpx7kpk71zfwv465jrscwzc9w3xfv52i4h01k9aw3q6m8ja"))))
    (properties `((upstream-name . "confinterpret")))
    (build-system r-build-system)
    (home-page "https://github.com/jimvine/confinterpret")
    (synopsis "Descriptive Interpretations of Confidence Intervals")
    (description
     "This package produces descriptive interpretations of confidence intervals.
Includes (extensible) support for various test types, specified as sets of
interpretations dependent on where the lower and upper confidence limits sit.
Provides plotting functions for graphical display of interpretations.")
    (license license:agpl3)))

(define-public r-configural
  (package
    (name "r-configural")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "configural" version))
       (sha256
        (base32 "1javknjl9ycb6rz77rhzya8yspm9m6mdjwl1waq1akgpiizk1pnl"))))
    (properties `((upstream-name . "configural")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=configural")
    (synopsis "Multivariate Profile Analysis")
    (description
     "R functions for criterion profile analysis, Davison and Davenport (2002)
<doi:10.1037/1082-989X.7.4.468> and meta-analytic criterion profile analysis,
Wiernik, Wilmot, Davison, and Ones (2020) <doi:10.1037/met0000305>.  Sensitivity
analyses to aid in interpreting criterion profile analysis results are also
included.")
    (license license:gpl3+)))

(define-public r-configr
  (package
    (name "r-configr")
    (version "0.3.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "configr" version))
       (sha256
        (base32 "1qlfza9fwqdhw37gxhgxgp4x2dg1qlvdw0rf9fn6a8hgjaj9z8a3"))))
    (properties `((upstream-name . "configr")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-stringr
                             r-rcpptoml
                             r-jsonlite
                             r-ini
                             r-glue))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Miachol/configr")
    (synopsis
     "An Implementation of Parsing and Writing Configuration File (JSON/INI/YAML/TOML)")
    (description
     "This package implements the JSON, INI, YAML and TOML parser for R setting and
writing of configuration file.  The functionality of this package is similar to
that of package config'.")
    (license license:expat)))

(define-public r-configparser
  (package
    (name "r-configparser")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConfigParser" version))
       (sha256
        (base32 "0jjh6gz5qcqhirzkmg7a4lnf8n3mjly15x2mvbvdpjkk7iv3w9m3"))))
    (properties `((upstream-name . "ConfigParser")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6 r-ini))
    (home-page "https://github.com/hhoeflin/ConfigParser")
    (synopsis "Package to Parse an INI File, Including Variable Interpolation")
    (description
     "Enhances the ini package by adding the ability to interpolate variables.  The
INI configuration file is read into an R6 @code{ConfigParser} object (loosely
inspired by Pythons @code{ConfigParser} module) and the keys can be read, where
%(....)s instances are interpolated by other included options or outside
variables.")
    (license license:gpl3)))

(define-public r-confidenceellipse
  (package
    (name "r-confidenceellipse")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConfidenceEllipse" version))
       (sha256
        (base32 "0p3dkfj1r1prz40cly7apcnvh1m6537h0kjaljgqkhb6ylrxmlci"))))
    (properties `((upstream-name . "ConfidenceEllipse")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-rlang
                             r-rgl
                             r-purrr
                             r-pcapp
                             r-magrittr
                             r-ggplot2
                             r-forcats
                             r-dplyr
                             r-cellwise))
    (native-inputs (list r-knitr))
    (home-page "https://christiangoueguel.github.io/ConfidenceEllipse/")
    (synopsis "Computation of 2D and 3D Elliptical Joint Confidence Regions")
    (description
     "Computing elliptical joint confidence regions at a specified confidence level.
It provides the flexibility to estimate either classical or robust confidence
regions, which can be visualized in 2D or 3D plots.  The classical approach
assumes normality and uses the mean and covariance matrix to define the
confidence regions.  Alternatively, the robustified version employs estimators
like minimum covariance determinant (MCD) and M-estimator, making them less
sensitive to outliers and departures from normality.  Furthermore, the functions
allow users to group the dataset based on categorical variables and estimate
separate confidence regions for each group.  This capability is particularly
useful for exploring potential differences or similarities across subgroups
within a dataset.  Varmuza and Filzmoser (2009, ISBN:978-1-4200-5947-2).
Johnson and Wichern (2007, ISBN:0-13-187715-1).  Raymaekers and Rousseeuw (2019)
<DOI:10.1080/00401706.2019.1677270>.")
    (license license:expat)))

(define-public r-confidence
  (package
    (name "r-confidence")
    (version "1.1-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "confidence" version))
       (sha256
        (base32 "0m6iz59n5jpi0ig3za3nir4d4bdsysf5g47d2nakfmaz03wk520z"))))
    (properties `((upstream-name . "confidence")))
    (build-system r-build-system)
    (propagated-inputs (list r-xtable r-plyr r-markdown r-knitr r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=confidence")
    (synopsis "Confidence Estimation of Environmental State Classifications")
    (description
     "This package provides functions for estimating and reporting multi-year averages
and corresponding confidence intervals and distributions.  A potential use case
is reporting the chemical and ecological status of surface waters according to
the European Water Framework Directive.")
    (license license:gpl3+)))

(define-public r-confcons
  (package
    (name "r-confcons")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "confcons" version))
       (sha256
        (base32 "1a9v2dzldnbmhn5fz30d8y8nhbgczgp20rag6ck6h4xjgwqm4yv1"))))
    (properties `((upstream-name . "confcons")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/bfakos/confcons")
    (synopsis "Confidence and Consistency of Predictive Distribution Models")
    (description
     "Calculate confidence and consistency that measure the goodness-of-fit and
transferability of predictive/potential distribution models (including species
distribution models) as described by Somodi & Bede-Fazekas et al. (2024)
<doi:10.1016/j.ecolmodel.2024.110667>.")
    (license license:gpl3+)))

(define-public r-conf-design
  (package
    (name "r-conf-design")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conf.design" version))
       (sha256
        (base32 "06vdxljkjq1x56xkg041l271an1xv9wq79swxvzzk64dqqnmay51"))))
    (properties `((upstream-name . "conf.design")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=conf.design")
    (synopsis "Construction of factorial designs")
    (description
     "This small library contains a series of simple tools for constructing and
manipulating confounded and fractional factorial designs.")
    (license license:gpl2)))

(define-public r-conf
  (package
    (name "r-conf")
    (version "1.9.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conf" version))
       (sha256
        (base32 "12zc5psfaldgyqmlfa8bf04ibqyxcszmry9fw1ab8brn7fh6vg7i"))))
    (properties `((upstream-name . "conf")))
    (build-system r-build-system)
    (propagated-inputs (list r-statmod r-rootsolve r-pracma r-fitdistrplus))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=conf")
    (synopsis
     "Visualization and Analysis of Statistical Measures of Confidence")
    (description
     "Enables: (1) plotting two-dimensional confidence regions, (2) coverage analysis
of confidence region simulations, (3) calculating confidence intervals and the
associated actual coverage for binomial proportions, (4) calculating the support
values and the probability mass function of the Kaplan-Meier product-limit
estimator, and (5) plotting the actual coverage function associated with a
confidence interval for the survivor function from a randomly right-censored
data set.  Each is given in greater detail next. (1) Plots the two-dimensional
confidence region for probability distribution parameters (supported
distribution suffixes: cauchy, gamma, invgauss, logis, llogis, lnorm, norm,
unif, weibull) corresponding to a user-given complete or right-censored dataset
and level of significance.  The crplot() algorithm plots more points in areas of
greater curvature to ensure a smooth appearance throughout the confidence region
boundary.  An alternative heuristic plots a specified number of points at
roughly uniform intervals along its boundary.  Both heuristics build upon the
radial profile log-likelihood ratio technique for plotting confidence regions
given by Jaeger (2016) <doi:10.1080/00031305.2016.1182946>, and are detailed in
a publication by Weld et al. (2019) <doi:10.1080/00031305.2018.1564696>. (2)
Performs confidence region coverage simulations for a random sample drawn from a
user- specified parametric population distribution, or for a user-specified
dataset and point of interest with coversim(). (3) Calculates confidence
interval bounds for a binomial proportion with @code{binomTest}(), calculates
the actual coverage with @code{binomTestCoverage}(), and plots the actual
coverage with @code{binomTestCoveragePlot}().  Calculates confidence interval
bounds for the binomial proportion using an ensemble of constituent confidence
intervals with @code{binomTestEnsemble}().  Calculates confidence interval
bounds for the binomial proportion using a complete enumeration of all possible
transitions from one actual coverage acceptance curve to another which minimizes
the root mean square error for n <= 15 and follows the transitions for
well-known confidence intervals for n > 15 using @code{binomTestMSE}(). (4) The
km.support() function calculates the support values of the Kaplan-Meier
product-limit estimator for a given sample size n using an induction algorithm
described in Qin et al. (2023) <doi:10.1080/00031305.2022.2070279>.  The
km.outcomes() function generates a matrix containing all possible outcomes (all
possible sequences of failure times and right-censoring times) of the value of
the Kaplan-Meier product-limit estimator for a particular sample size n.  The
km.pmf() function generates the probability mass function for the support values
of the Kaplan-Meier product-limit estimator for a particular sample size n,
probability of observing a failure h at the time of interest expressed as the
cumulative probability percentile associated with X = min(T, C), where T is the
failure time and C is the censoring time under a random-censoring scheme.  The
km.surv() function generates multiple probability mass functions of the
Kaplan-Meier product-limit estimator for the same arguments as those given for
km.pmf(). (5) The km.coverage() function plots the actual coverage function
associated with a confidence interval for the survivor function from a randomly
right-censored data set for one or more of the following confidence intervals:
Greenwood, log-minus-log, Peto, arcsine, and exponential Greenwood.  The actual
coverage function is plotted for a small number of items on test, stated
coverage, failure rate, and censoring rate.  The km.coverage() function can
print an optional table containing all possible failure/censoring orderings,
along with their contribution to the actual coverage function.")
    (license (license:fsdg-compatible "GPL (<= 2)"))))

(define-public r-coneproj
  (package
    (name "r-coneproj")
    (version "1.19")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coneproj" version))
       (sha256
        (base32 "0whnjdc24214kja1qbbyy95rmssabkq2x85p81nslcclr2krnxi2"))))
    (properties `((upstream-name . "coneproj")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "https://cran.r-project.org/package=coneproj")
    (synopsis
     "Primal or Dual Cone Projections with Routines for Constrained Regression")
    (description
     "Routines doing cone projection and quadratic programming, as well as doing
estimation and inference for constrained parametric regression and
shape-restricted regression problems.  See Mary C. Meyer
(2013)<doi:10.1080/03610918.2012.659820> for more details.")
    (license license:gpl2+)))

(define-public r-condvis2
  (package
    (name "r-condvis2")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "condvis2" version))
       (sha256
        (base32 "0zxr0m50gyg5b1ghdx5ysq8f389gg00zx719zqb47ign83xlbn63"))))
    (properties `((upstream-name . "condvis2")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny
                             r-scales
                             r-rcolorbrewer
                             r-plyr
                             r-gower
                             r-ggplot2
                             r-dendser
                             r-colorspace
                             r-cluster))
    (native-inputs (list r-knitr))
    (home-page "https://cbhurley.github.io/condvis2/")
    (synopsis
     "Interactive Conditional Visualization for Supervised and Unsupervised Models in Shiny")
    (description
     "Constructs a shiny app function with interactive displays for conditional
visualization of models, data and density functions.  An extended version of
package condvis'.  Catherine B. Hurley, Mark O'Connell,Katarina Domijan (2021)
<doi:10.1080/10618600.2021.1983439>.")
    (license license:gpl2+)))

(define-public r-condvis
  (package
    (name "r-condvis")
    (version "0.5-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "condvis" version))
       (sha256
        (base32 "1ngxqfa0mr86cv610da4ljypxpdvx0n5pfgj3zfksnwxlwc0dvbj"))))
    (properties `((upstream-name . "condvis")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "http://markajoc.github.io/condvis/")
    (synopsis "Conditional Visualization for Statistical Models")
    (description
     "Exploring fitted models by interactively taking 2-D and 3-D sections in data
space.")
    (license license:gpl2+)))

(define-public r-conductor
  (package
    (name "r-conductor")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conductor" version))
       (sha256
        (base32 "1kjnjpaiya5ym20y1vry53dshna14dvcjfzgbfizg4g1izsg1czy"))))
    (properties `((upstream-name . "conductor")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-r6 r-htmltools))
    (home-page "https://github.com/etiennebacher/conductor")
    (synopsis "Create Tours in 'Shiny' Apps Using 'Shepherd.js'")
    (description
     "Enable the use of Shepherd.js to create tours in Shiny applications.")
    (license license:expat)))

(define-public r-condtruncmvn
  (package
    (name "r-condtruncmvn")
    (version "0.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "condTruncMVN" version))
       (sha256
        (base32 "1dicfa82yg8k83lnb5c17jnqwgkazpb8404kfzdf6ikmndwjn0zg"))))
    (properties `((upstream-name . "condTruncMVN")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncnorm r-tmvtnorm r-tmvmixnorm
                             r-matrixnormal r-condmvnorm))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=condTruncMVN")
    (synopsis "Conditional Truncated Multivariate Normal Distribution")
    (description
     "Computes the density and probability for the conditional truncated multivariate
normal (Horrace (2005) p.  4, <doi:10.1016/j.jmva.2004.10.007>).  Also draws
random samples from this distribution.")
    (license license:gpl3)))

(define-public r-condsurv
  (package
    (name "r-condsurv")
    (version "2.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "condSURV" version))
       (sha256
        (base32 "11ji8q8qhmpyc1zcdckjsq40bg2gbhbp0222fsrdkfglq3h4dg5x"))))
    (properties `((upstream-name . "condSURV")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-np
                             r-kernsmooth
                             r-foreach
                             r-dorng
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=condSURV")
    (synopsis
     "Estimation of the Conditional Survival Function for Ordered Multivariate Failure Time Data")
    (description
     "Method to implement some newly developed methods for the estimation of the
conditional survival function.  See Meira-Machado, Sestelo and Goncalves (2016)
<doi:10.1002/bimj.201500038>.")
    (license license:gpl2+)))

(define-public r-condoroptions
  (package
    (name "r-condoroptions")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "condorOptions" version))
       (sha256
        (base32 "05bc0l62v2js1wd7ll006gjh3iqz99kjw28c7811kgqw3rkdda76"))))
    (properties `((upstream-name . "condorOptions")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-magrittr r-ggplot2 r-dplyr))
    (home-page "https://cran.r-project.org/package=condorOptions")
    (synopsis "Trading Condor Options Strategies")
    (description
     "Trading of Condor Options Strategies is represented here through their Graphs.
The graphic indicators, strategies, calculations, functions and all the
discussions are for academic, research, and educational purposes only and should
not be construed as investment advice and come with absolutely no Liability.
Guy Cohen (âThe Bible of Options Strategies (2nd ed.)â, 2015, ISBN:
9780133964028).  Zura Kakushadze, Juan A. Serur (â151 Trading Strategiesâ,
2018, ISBN: 9783030027919).  John C. Hull (âOptions, Futures, and Other
Derivatives (11th ed.)â, 2022, ISBN: 9780136939979).")
    (license license:gpl3)))

(define-public r-condor
  (package
    (name "r-condor")
    (version "2.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "condor" version))
       (sha256
        (base32 "0v8crlg5pjqa2d37pb6744srn60cqzcih2100y3xh2a7wjml2d4w"))))
    (properties `((upstream-name . "condor")))
    (build-system r-build-system)
    (inputs (list))
    (propagated-inputs (list r-ssh))
    (home-page "https://github.com/PacificCommunity/ofp-sam-condor")
    (synopsis "Interact with 'Condor' from R via SSH")
    (description
     "Interact with Condor from R via SSH connection.  Files are first uploaded from
user machine to submitter machine, and the job is then submitted from the
submitter machine to Condor'.  Functions are provided to submit, list, and
download Condor jobs from R. Condor is an open source high-throughput computing
software framework for distributed parallelization of computationally intensive
tasks.")
    (license license:gpl3)))

(define-public r-condmvt
  (package
    (name "r-condmvt")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CondMVT" version))
       (sha256
        (base32 "010zfd2pdmajbicslz0wamv20gc0im5iwcfpjd14awi2v9pg9vg8"))))
    (properties `((upstream-name . "CondMVT")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm))
    (home-page "https://cran.r-project.org/package=CondMVT")
    (synopsis
     "Conditional Multivariate t Distribution, Expectation Maximization Algorithm, and Its Stochastic Variants")
    (description
     "Computes conditional multivariate t probabilities, random deviates, and
densities.  It can also be used to create missing values at random in a dataset,
resulting in a missing at random (MAR) mechanism.  Inbuilt in the package are
the Expectation-Maximization (EM), Monte Carlo EM, and Stochastic EM algorithms
for imputation of missing values in datasets assuming the multivariate t
distribution.  See Kinyanjui, Tamba, Orawo, and Okenye
(2020)<doi:10.3233/mas-200493>, and Kinyanjui, Tamba, and
Okenye(2021)<http://www.ceser.in/ceserp/index.php/ijamas/article/view/6726/0>
for more details.")
    (license license:expat)))

(define-public r-condmvnorm
  (package
    (name "r-condmvnorm")
    (version "2020.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "condMVNorm" version))
       (sha256
        (base32 "115pxnff2ckdxx0avbs0hfdhh1sljiz1y6h7ggd5hidrxd3559m4"))))
    (properties `((upstream-name . "condMVNorm")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm))
    (home-page "https://cran.r-project.org/package=condMVNorm")
    (synopsis "Conditional Multivariate Normal Distribution")
    (description
     "Computes conditional multivariate normal densities, probabilities, and random
deviates.")
    (license license:gpl2)))

(define-public r-conditionz
  (package
    (name "r-conditionz")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conditionz" version))
       (sha256
        (base32 "0ijnsg6n3p3y8y9il012xg5if57hdzvrgxjcykfrrlil4m7ixn6c"))))
    (properties `((upstream-name . "conditionz")))
    (build-system r-build-system)
    (propagated-inputs (list r-uuid r-r6))
    (home-page "https://github.com/ropenscilabs/conditionz")
    (synopsis "Control How Many Times Conditions are Thrown")
    (description
     "This package provides ability to control how many times in function calls
conditions are thrown (shown to the user).  Includes control of warnings and
messages.")
    (license license:expat)))

(define-public r-conditionalprobnspades
  (package
    (name "r-conditionalprobnspades")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conditionalProbNspades" version))
       (sha256
        (base32 "0z621mnwxcv51r2x6jhp0r2b4d7gbi1095f9cjpwp0cwwvpcazw2"))))
    (properties `((upstream-name . "conditionalProbNspades")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=conditionalProbNspades")
    (synopsis "Conditional Probabilities of Distributions Across Hearts Hands")
    (description
     "This package provides some tabulated data to be be referred to in a discussion
in a vignette accompanying my upcoming R package
@code{playWholeHandDriverPassParams}'.  In addition to that specific purpose,
these may also provide data and illustrate some computational approaches that
are relevant to card games like hearts or bridge.This package refers to
authentic data from Gregory Stoll
<https://gregstoll.com/~gregstoll/bridge/math.html>, and details of performing
the probability calculations from Jeremy L. Martin
<https://jlmartin.ku.edu/~jlmartin/bridge/basics.pdf>.")
    (license license:gpl2+)))

(define-public r-condis
  (package
    (name "r-condis")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CondiS" version))
       (sha256
        (base32 "19l26ajzbi58cnim1kgxb5wrilqpvz6znv01zd42s3w6899km28b"))))
    (properties `((upstream-name . "CondiS")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyverse
                             r-survminer
                             r-survival
                             r-purrr
                             r-kernlab
                             r-caret))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CondiS")
    (synopsis "Censored Data Imputation for Direct Modeling")
    (description
     "Impute the survival times for censored observations based on their conditional
survival distributions derived from the Kaplan-Meier estimator. @code{CondiS}
can replace the censored observations with the best approximations from the
statistical model, allowing for direct application of machine learning-based
methods.  When covariates are available, @code{CondiS} is extended by
incorporating the covariate information through machine learning-based
regression modeling ('@code{CondiS_X}'), which can further improve the imputed
survival time.")
    (license license:gpl2)))

(define-public r-condir
  (package
    (name "r-condir")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "condir" version))
       (sha256
        (base32 "0aknc1qj95wf99kqzcsfqhjpvbgazv7jqpwla1g146b6fkig532h"))))
    (properties `((upstream-name . "condir")))
    (build-system r-build-system)
    (propagated-inputs (list r-xtable
                             r-shiny
                             r-psych
                             r-knitr
                             r-effsize
                             r-bayesfactor))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/AngelosPsy/condir")
    (synopsis
     "Computation of P Values and Bayes Factors for Conditioning Data")
    (description
     "Set of functions for the easy analyses of conditioning data.")
    (license license:gpl3)))

(define-public r-condindtests
  (package
    (name "r-condindtests")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CondIndTests" version))
       (sha256
        (base32 "0km4z8wnj5msg1pmphk2fccbw1cidsxv174817lwcyii9nf5iwsm"))))
    (properties `((upstream-name . "CondIndTests")))
    (build-system r-build-system)
    (propagated-inputs (list r-rptests
                             r-randomforest
                             r-quantregforest
                             r-pracma
                             r-mize
                             r-mgcv
                             r-mass
                             r-lawstat
                             r-kernlab
                             r-catools))
    (home-page
     "https://github.com/christinaheinze/nonlinearICP-and-CondIndTests")
    (synopsis "Nonlinear Conditional Independence Tests")
    (description
     "Code for a variety of nonlinear conditional independence tests: Kernel
conditional independence test (Zhang et al., UAI 2011,
<@code{arXiv:1202.3775>}), Residual Prediction test (based on Shah and
Buehlmann, <@code{arXiv:1511.03334>}), Invariant environment prediction,
Invariant target prediction, Invariant residual distribution test, Invariant
conditional quantile prediction (all from Heinze-Deml et al.,
<@code{arXiv:1706.08576>}).")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-condgee
  (package
    (name "r-condgee")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "condGEE" version))
       (sha256
        (base32 "09vbwpn4i37cn8gs9pr62mvzzbqrfm756370zas97kjbnmx8glbj"))))
    (properties `((upstream-name . "condGEE")))
    (build-system r-build-system)
    (propagated-inputs (list r-rootsolve r-numderiv))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=condGEE")
    (synopsis
     "Parameter Estimation in Conditional GEE for Recurrent Event Gap Times")
    (description
     "Solves for the mean parameters, the variance parameter, and their asymptotic
variance in a conditional GEE for recurrent event gap times, as described by
Clement and Strawderman (2009) in the journal Biostatistics.  Makes a parametric
assumption for the length of the censored gap time.")
    (license license:gpl2+)))

(define-public r-condformat
  (package
    (name "r-condformat")
    (version "0.10.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "condformat" version))
       (sha256
        (base32 "0nyl2wa9vfi65g0v54a4zpppw5yz7rlh2x6l2v9dgvwg533hkf72"))))
    (properties `((upstream-name . "condformat")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tibble
                             r-scales
                             r-rmarkdown
                             r-rlang
                             r-openxlsx
                             r-magrittr
                             r-knitr
                             r-htmltools
                             r-htmltable
                             r-gtable
                             r-gridextra
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://zeehio.github.io/condformat/")
    (synopsis "Conditional Formatting in Data Frames")
    (description
     "Apply and visualize conditional formatting to data frames in R. It renders a
data frame with cells formatted according to criteria defined by rules, using a
tidy evaluation syntax.  The table is printed either opening a web browser or
within the RStudio viewer if available.  The conditional formatting rules allow
to highlight cells matching a condition or add a gradient background to a given
column.  This package supports both HTML and @code{LaTeX} outputs in knitr
reports, and exporting to an xlsx file.")
    (license license:bsd-3)))

(define-public r-condensr
  (package
    (name "r-condensr")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "condensr" version))
       (sha256
        (base32 "0gx8yd7ldm6wzfqxy6axcrpqf3gcvcx0il6rd4jmyx3k43s52y09"))))
    (properties `((upstream-name . "condensr")))
    (build-system r-build-system)
    (propagated-inputs (list r-whisker r-glue r-fs r-assertthat))
    (home-page "http://www.michaellydeamore.com/condensr/")
    (synopsis "Academic Group Website Generator")
    (description
     "Helps automate Quarto website creation for small academic groups.  Builds a
database-like structure of people, projects and publications, linking them
together with a string-based ID system.  Then, provides functions to automate
production of clean markdown for these structures, and in-built CSS formatting
using CSS flexbox.")
    (license license:expat)))

(define-public r-condcopulas
  (package
    (name "r-condcopulas")
    (version "0.1.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CondCopulas" version))
       (sha256
        (base32 "0ad7yapm0vv681d17wqrsvms5nma1wk6hl2ashhrpfzwlndadw0v"))))
    (properties `((upstream-name . "CondCopulas")))
    (build-system r-build-system)
    (propagated-inputs (list r-wdm
                             r-vinecopula
                             r-tree
                             r-statmod
                             r-pbapply
                             r-ordinalnet
                             r-nnet
                             r-glmnet
                             r-data-tree))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/AlexisDerumigny/CondCopulas")
    (synopsis "Estimation and Inference for Conditional Copula Models")
    (description
     "This package provides functions for the estimation of conditional copulas
models, various estimators of conditional Kendall's tau (proposed in Derumigny
and Fermanian (2019a, 2019b, 2020) <doi:10.1515/demo-2019-0016>,
<doi:10.1016/j.csda.2019.01.013>, <doi:10.1016/j.jmva.2020.104610>), and test
procedures for the simplifying assumption (proposed in Derumigny and Fermanian
(2017) <doi:10.1515/demo-2017-0011> and Derumigny, Fermanian and Min (2022)
<doi:10.1002/cjs.11742>).")
    (license license:gpl3)))

(define-public r-cond
  (package
    (name "r-cond")
    (version "1.2-3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cond" version))
       (sha256
        (base32 "1j0gf28mg2j6ahs83nk662bix1lb2c9184vn8sblw433zxqaa2ny"))))
    (properties `((upstream-name . "cond")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-statmod))
    (home-page "https://www.r-project.org")
    (synopsis
     "Approximate Conditional Inference for Logistic and Loglinear Models")
    (description
     "Higher order likelihood-based inference for logistic and loglinear models.")
    (license (list license:gpl2+
                   (license:fsdg-compatible "file LICENCE")))))

(define-public r-concur
  (package
    (name "r-concur")
    (version "1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CONCUR" version))
       (sha256
        (base32 "0455jmc8grcpmipcz2rr6zdhxjfi0gd5zj46lyvh75k6wn2p6265"))))
    (properties `((upstream-name . "CONCUR")))
    (build-system r-build-system)
    (propagated-inputs (list r-mgcv r-dplyr r-compquadform))
    (home-page "https://cran.r-project.org/package=CONCUR")
    (synopsis "Copy Number Profile Curve-Based Association Test")
    (description
     "This package implements a kernel-based association test for copy number
variation (CNV) aggregate analysis in a certain genomic region (e.g., gene set,
chromosome, or genome) that is robust to the within-locus and across-locus
etiological heterogeneity, and bypass the need to define a \"locus\" unit for
CNVs.  Brucker, A., et al. (2020) <doi:10.1101/666875>.")
    (license license:gpl2)))

(define-public r-concstats
  (package
    (name "r-concstats")
    (version "0.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "concstats" version))
       (sha256
        (base32 "1gcv6lsrfdb12alaksmw40fv8p909hifjwrrgy9r12nb4ci3fg0x"))))
    (properties `((upstream-name . "concstats")))
    (build-system r-build-system)
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://github.com/ropensci/concstats/")
    (synopsis "Market Structure, Concentration and Inequality Measures")
    (description
     "Based on individual market shares of all participants in a market or space, the
package offers a set of different structural and concentration measures
frequently - and not so frequently - used in research and in practice.  Measures
can be calculated in groups or individually.  The calculated measure or the
resulting vector in table format should help practitioners make more informed
decisions.  Methods used in this package are from: 1.  Chang, E. J., Guerra, S.
M., de Souza Penaloza, R. A. & Tabak, B. M. (2005) \"Banking concentration: the
Brazilian case\".  2.  Cobham, A. and A. Summer (2013). \"Is It All About the
Tails? The Palma Measure of Income Inequality\".  3.  Garcia Alba Idunate, P.
(1994). \"Un Indice de dominancia para el analisis de la estructura de los
mercados\".  4.  Ginevicius, R. and S. Cirba (2009). \"Additive measurement of
market concentration\" <doi:10.3846/1611-1699.2009.10.191-198>.  5.  Herfindahl,
O. C. (1950), \"Concentration in the steel industry\" (@code{PhD} thesis).  6.
Hirschmann, A. O. (1945), \"National power and structure of foreign trade\".  7.
Melnik, A., O. Shy, and R. Stenbacka (2008), \"Assessing market dominance\"
<doi:10.1016/j.jebo.2008.03.010>.  8.  Palma, J. G. (2006). \"Globalizing
Inequality: Centrifugal and Centripetal Forces at Work\".  9.  Shannon, C. E.
(1948). \"A Mathematical Theory of Communication\".  10.  Simpson, E. H. (1949).
\"Measurement of Diversity\" <doi:10.1038/163688a0>.")
    (license license:gpl3+)))

(define-public r-concorr
  (package
    (name "r-concorr")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "concorR" version))
       (sha256
        (base32 "15pi24xka83p3hm33rfs9vnfkzywmvpz3hpncgqmc9ifwag0zgra"))))
    (properties `((upstream-name . "concorR")))
    (build-system r-build-system)
    (propagated-inputs (list r-sna r-igraph))
    (home-page "https://github.com/ATraxLab/concorR")
    (synopsis "CONCOR and Supplemental Functions")
    (description
     "This package contains the CONCOR (CONvergence of iterated CORrelations)
algorithm and a series of supplemental functions for easy running, plotting, and
blockmodeling.  The CONCOR algorithm is used on social network data to identify
network positions based off a definition of structural equivalence; see Breiger,
Boorman, and Arabie (1975) <doi:10.1016/0022-2496(75)90028-0> and Wasserman and
Faust's book Social Network Analysis: Methods and Applications (1994).  This
version allows multiple relationships for the same set of nodes and uses both
incoming and outgoing ties to find positions.")
    (license license:gpl2+)))

(define-public r-concordancetest
  (package
    (name "r-concordancetest")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConcordanceTest" version))
       (sha256
        (base32 "09avmhmf286g64240l6anmnzyqfx8qa0p0m883hn0r43m63sc2rd"))))
    (properties `((upstream-name . "ConcordanceTest")))
    (build-system r-build-system)
    (propagated-inputs (list r-rglpk))
    (home-page "https://cran.r-project.org/package=ConcordanceTest")
    (synopsis
     "An Alternative to the Kruskal-Wallis Based on the Kendall Tau Distance")
    (description
     "The Concordance Test is a non-parametric method for testing whether two o more
samples originate from the same distribution.  It extends the Kendall Tau
correlation coefficient when there are only two groups.  For details, see
Alcaraz J., Anton-Sanchez L., Monge J.F. (2022) The Concordance Test, an
Alternative to Kruskal-Wallis Based on the Kendall-tau Distance: An R Package.
The R Journal 14, 26â53 <doi:10.32614/RJ-2022-039>.")
    (license license:gpl3)))

(define-public r-concordance
  (package
    (name "r-concordance")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "concordance" version))
       (sha256
        (base32 "1xlm0c91bsbij8dr23fh781c6bg8l74kma6x7nnapkpm7jim279x"))))
    (properties `((upstream-name . "concordance")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-purrr
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=concordance")
    (synopsis "Product Concordance")
    (description
     "This package provides a set of utilities for matching products in different
classification codes used in international trade research.  It supports
concordance between the Harmonized System (HS0, HS1, HS2, HS3, HS4, HS5, HS
combined), the Standard International Trade Classification (SITC1, SITC2, SITC3,
SITC4), the North American Industry Classification System (NAICS combined), as
well as the Broad Economic Categories (BEC), the International Standard of
Industrial Classification (ISIC), and the Standard Industrial Classification
(SIC).  It also provides code nomenclature/descriptions look-up, Rauch
classification look-up (via concordance to SITC2), and trade elasticity look-up
(via concordance to HS0 or SITC3 codes).")
    (license license:gpl2)))

(define-public r-conconpiwifun
  (package
    (name "r-conconpiwifun")
    (version "0.4.6.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConConPiWiFun" version))
       (sha256
        (base32 "1ziy646lbx297kia797xjxa8hyl826x1hiighyjslvnlvrhapx08"))))
    (properties `((upstream-name . "ConConPiWiFun")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://cran.r-project.org/package=ConConPiWiFun")
    (synopsis
     "Optimisation with Continuous Convex Piecewise (Linear and Quadratic) Functions")
    (description
     "Continuous convex piecewise linear (ccpl) resp.  quadratic (ccpq) functions can
be implemented with sorted breakpoints and slopes.  This includes functions that
are ccpl (resp.  ccpq) on a convex set (i.e.  an interval or a point) and
infinite out of the domain.  These functions can be very useful for a large
class of optimisation problems.  Efficient manipulation (such as log(N)
insertion) of such data structure is obtained with map standard template library
of C++ (that hides balanced trees).  This package is a wrapper on such a class
based on Rcpp modules.")
    (license license:gpl2+)))

(define-public r-conconianaerobicthresholdtest
  (package
    (name "r-conconianaerobicthresholdtest")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ConconiAnaerobicThresholdTest" version))
       (sha256
        (base32 "0lx1pz40l4qc755lxxvrvkjv6297q61m5vqdix8pw9j4h0wzyxll"))))
    (properties `((upstream-name . "ConconiAnaerobicThresholdTest")))
    (build-system r-build-system)
    (propagated-inputs (list r-tracker r-sizer r-ggplot2 r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/waldronlab/ConconiAnaerobicThresholdTest")
    (synopsis "Conconi Estimate of Anaerobic Threshold from a TCX File")
    (description
     "Analyzes data from a Conconi et al. (1996) <doi:10.1055/s-2007-972887> treadmill
fitness test where speed is augmented by a constant amount every set number of
seconds to estimate the anaerobic (lactate) threshold speed and heart rate.  It
reads a TCX file, allows optional removal observations from before and after the
actual test, fits a change-point linear model where the change-point is the
estimate of the lactate threshold, and plots the data points and fit model.
Details of administering the fitness test are provided in the package vignette.
Functions work by default for Garmin Connect TCX exports but may require
additional data preparation for heart rate, time, and speed data from other
sources.")
    (license license:gpl3+)))

(define-public r-concom
  (package
    (name "r-concom")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "concom" version))
       (sha256
        (base32 "1rqb04kv4ygx1rpnj4dqa3jnx3iy9a3c9d8x3bci969zd9lk7kzb"))))
    (properties `((upstream-name . "concom")))
    (build-system r-build-system)
    (propagated-inputs (list r-rvcg r-rgl r-rcpp r-english r-bh))
    (home-page "https://github.com/stla/concom")
    (synopsis "Connected Components of an Undirected Graph")
    (description
     "This package provides a function for fast computation of the connected
components of an undirected graph (though not faster than the components()
function of the igraph package) from the edges or the adjacency matrix of the
graph.  Based on this one, a function to compute the connected components of a
triangle rgl mesh is also provided.")
    (license license:gpl3)))

(define-public r-conclust
  (package
    (name "r-conclust")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "conclust" version))
       (sha256
        (base32 "1k9y1mniy7s51dmm5ia693k72s2vxk5bznxxf74s7mx9n3mg2i8r"))))
    (properties `((upstream-name . "conclust")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=conclust")
    (synopsis "Pairwise Constraints Clustering")
    (description
     "There are 4 main functions in this package: ckmeans(), lcvqe(), mpckm() and
ccls().  They take an unlabeled dataset and two lists of must-link and
cannot-link constraints as input and produce a clustering as output.")
    (license license:gpl3)))

(define-public r-concaveman
  (package
    (name "r-concaveman")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "concaveman" version))
       (sha256
        (base32 "0b3fx3y60ibb73pqx5591jq1n86242qajfxbz3vzz6rxxspddlcz"))))
    (properties `((upstream-name . "concaveman")))
    (build-system r-build-system)
    (inputs (list proj.4 geos gdal))
    (propagated-inputs (list r-v8 r-sf r-magrittr r-jsonlite r-dplyr))
    (home-page "https://joelgombin.github.io/concaveman/")
    (synopsis "Very Fast 2D Concave Hull Algorithm")
    (description
     "The concaveman function ports the concaveman
(<https://github.com/mapbox/concaveman>) library from mapbox'.  It computes the
concave polygon(s) for one or several set of points.")
    (license license:gpl3)))

(define-public r-concatipede
  (package
    (name "r-concatipede")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "concatipede" version))
       (sha256
        (base32 "1cmc0pcy9di1bxzj4kgbnvv1avd7xd6jzk43kni7fc5fkcq2jj3x"))))
    (properties `((upstream-name . "concatipede")))
    (build-system r-build-system)
    (propagated-inputs (list r-writexl
                             r-tibble
                             r-stringr
                             r-stringdist
                             r-readxl
                             r-qualv
                             r-magrittr
                             r-igraph
                             r-dplyr
                             r-ape))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://github.com/tardipede/concatipede")
    (synopsis "Easy Concatenation of Fasta Sequences")
    (description
     "Concatenation of multiple sequence alignments based on a correspondence table
that can be edited in Excel <doi:10.5281/zenodo.5130603>.")
    (license license:expat)))

(define-public r-concatenate
  (package
    (name "r-concatenate")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "concatenate" version))
       (sha256
        (base32 "1kvsw7vwa3hn97ff7r6z21h5ajs74azwv2dk4pzgyaasnbp778hw"))))
    (properties `((upstream-name . "concatenate")))
    (build-system r-build-system)
    (home-page "https://github.com/jamesdunham/concatenate")
    (synopsis "Human-Friendly Text from Unknown Strings")
    (description
     "Simple functions for joining strings.  Construct human-friendly messages whose
elements aren't known in advance, like in stop, warning, or message, from clean
code.")
    (license (license:fsdg-compatible "GPL (>= 3.2)"))))

(define-public r-conake
  (package
    (name "r-conake")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Conake" version))
       (sha256
        (base32 "00c07wlsrzf6cwpaxmd7c78cxiwc3jfslxm6sxpbpr6b8270hz5m"))))
    (properties `((upstream-name . "Conake")))
    (build-system r-build-system)
    (home-page "www.r-project.org")
    (synopsis "Continuous Associated Kernel Estimation")
    (description
     "Continuous smoothing of probability density function on a compact or
semi-infinite support is performed using four continuous associated kernels:
extended beta, gamma, lognormal and reciprocal inverse Gaussian.  The
cross-validation technique is also implemented for bandwidth selection.")
    (license license:gpl2+)))

(define-public r-con2lki
  (package
    (name "r-con2lki")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "con2lki" version))
       (sha256
        (base32 "005bk3y7il94h7zlkdjlibm1zm9yplbbzlybdjxmckh67sr6d03x"))))
    (properties `((upstream-name . "con2lki")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=con2lki")
    (synopsis "Calculate the Dutch Air Quality Index (LKI)")
    (description
     "Calculates the dutch air quality index (LKI).  This index was created on the
basis of scientific studies of the health effects of air pollution.  From these
studies it can be deduced at what concentrations a certain percentage of the
population can be affected.  For more information see:
<https://www.rivm.nl/bibliotheek/rapporten/2014-0050.pdf>.")
    (license license:expat)))

(define-public r-con2aqi
  (package
    (name "r-con2aqi")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "con2aqi" version))
       (sha256
        (base32 "1gdd1y6xg26fz199hvryzsnp16qbsz13chqqxyxnkgrai1l72mhf"))))
    (properties `((upstream-name . "con2aqi")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=con2aqi")
    (synopsis "Calculate the AQI from Pollutant Concentration")
    (description
     "To calculate the AQI (Air Quality Index) from pollutant concentration data.  O3,
PM2.5, PM10, CO, SO2, and NO2 are available currently.  The method can be
referenced at Environmental Protection Agency, United States as follows: EPA
(2016)
<https://www3.epa.gov/airnow/aqi-technical-assistance-document-may2016.pdf>.")
    (license license:gpl3)))

(define-public r-comtradr
  (package
    (name "r-comtradr")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comtradr" version))
       (sha256
        (base32 "1ljqw9i32p06yq16sbww1la7gnfgbajbs8l5hqbhxqgxk1qfxr0a"))))
    (properties `((upstream-name . "comtradr")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-rlang
                             r-readr
                             r-rappdirs
                             r-purrr
                             r-poorman
                             r-memoise
                             r-lubridate
                             r-lifecycle
                             r-httr2
                             r-fs
                             r-cli
                             r-cachem
                             r-askpass))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/comtradr/")
    (synopsis "Interface with the United Nations Comtrade API")
    (description
     "Interface with and extract data from the United Nations Comtrade API
<https://comtradeplus.un.org/>.  Comtrade provides country level shipping data
for a variety of commodities, these functions allow for easy API query and data
returned as a tidy data frame.")
    (license license:gpl3)))

(define-public r-comstab
  (package
    (name "r-comstab")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comstab" version))
       (sha256
        (base32 "0rzgsc4jd65m7wrpf68p83cvngqk2z3dn7src8m47ampmwk131iq"))))
    (properties `((upstream-name . "comstab")))
    (build-system r-build-system)
    (propagated-inputs (list r-ternary))
    (home-page "https://github.com/jsegrestin/comstab")
    (synopsis
     "Partitioning the Drivers of Stability of Ecological Communities")
    (description
     "This package contains the basic functions to apply the unified framework for
partitioning the drivers of stability of ecological communities.  Segrestin et
al. (2024) <doi:10.1111/geb.13828>.")
    (license license:gpl3)))

(define-public r-comsimitv
  (package
    (name "r-comsimitv")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comsimitv" version))
       (sha256
        (base32 "0g1b14bx0dgy7y24gxlj0r2sgiild14cvr1zmf37df7g3bswn112"))))
    (properties `((upstream-name . "comsimitv")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan r-mass))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=comsimitv")
    (synopsis "Flexible Framework for Simulating Community Assembly")
    (description
     "Flexible framework for trait-based simulation of community assembly, where
components could be replaced by user-defined function and that allows variation
of traits within species.")
    (license license:gpl2)))

(define-public r-comriskmodel
  (package
    (name "r-comriskmodel")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ComRiskModel" version))
       (sha256
        (base32 "0jpsmcpi7s0y4dff3k10daimb4gfq7r5sf1w8n51q21zfgf3mn4d"))))
    (properties `((upstream-name . "ComRiskModel")))
    (build-system r-build-system)
    (propagated-inputs (list r-adequacymodel))
    (home-page "https://cran.r-project.org/package=ComRiskModel")
    (synopsis "Fitting of Complementary Risk Models")
    (description
     "Evaluates the probability density function (PDF), cumulative distribution
function (CDF), quantile function (QF), random numbers and maximum likelihood
estimates (MLEs) of well-known complementary binomial-G, complementary negative
binomial-G and complementary geometric-G families of distributions taking
baseline models such as exponential, extended exponential, Weibull, extended
Weibull, Fisk, Lomax, Burr-XII and Burr-X. The functions also allow computing
the goodness-of-fit measures namely the Akaike-information-criterion (AIC), the
Bayesian-information-criterion (BIC), the minimum value of the negative
log-likelihood (-2L) function, Anderson-Darling (A) test, Cramer-Von-Mises (W)
test, Kolmogorov-Smirnov test, P-value and convergence status.  Moreover, some
commonly used data sets from the fields of actuarial, reliability, and medical
science are also provided.  Related works include: a) Tahir, M. H., & Cordeiro,
G. M. (2016).  Compounding of distributions: a survey and new generalized
classes.  Journal of Statistical Distributions and Applications, 3, 1-35.
<doi:10.1186/s40488-016-0052-1>.")
    (license license:gpl2+)))

(define-public r-comradesm
  (package
    (name "r-comradesm")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ComradesM" version))
       (sha256
        (base32 "0z1fxmsbswd6cnv4r557g55a8lsiwwv13v6i5kw8yayg9xh43knx"))))
    (properties `((upstream-name . "ComradesM")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ComradesM")
    (synopsis "The Comrades Marathon 1921 to 2019")
    (description
     "Datasets related to the Comrades Marathon used in the book Antony Unwin (2024,
ISBN:978-0367674007) \"Getting (more out of) Graphics\".  The main dataset
contains the times of every runner that finished in the time limit for each year
the race was run.")
    (license license:gpl2+)))

(define-public r-compute-es
  (package
    (name "r-compute-es")
    (version "0.2-5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "compute.es" version))
       (sha256
        (base32 "00133s3l3g70xrfnxgxhvbjr8izvaj9h0c73iaiyjmlgj84x69m8"))))
    (properties `((upstream-name . "compute.es")))
    (build-system r-build-system)
    (home-page "http://acdelre.com")
    (synopsis "Compute Effect Sizes")
    (description
     "Several functions are available for calculating the most widely used effect
sizes (ES), along with their variances, confidence intervals and p-values.  The
output includes ES's of d (mean difference), g (unbiased estimate of d), r
(correlation coefficient), z (Fisher's z), and OR (odds ratio and log odds
ratio).  In addition, NNT (number needed to treat), U3, CLES (Common Language
Effect Size) and Cliff's Delta are computed.  This package uses recommended
formulas as described in The Handbook of Research Synthesis and Meta-Analysis
(Cooper, Hedges, & Valentine, 2009).")
    (license license:gpl2)))

(define-public r-comprehenr
  (package
    (name "r-comprehenr")
    (version "0.6.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comprehenr" version))
       (sha256
        (base32 "1wlc06swm45nxg9hgik3wj832sr074i3p0j5kxm0i2r74klfy22w"))))
    (properties `((upstream-name . "comprehenr")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/gdemin/comprehenr")
    (synopsis "List Comprehensions")
    (description
     "This package provides Python'-style list comprehensions.  List comprehension
expressions use usual loops (for(), while() and repeat()) and usual if() as list
producers.  In many cases it gives more concise notation than standard \"*apply +
filter\" strategy.")
    (license license:gpl2)))

(define-public r-compr
  (package
    (name "r-compr")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CompR" version))
       (sha256
        (base32 "1k4q0yanvhdh3ksia7d42lxky19yci5vxhmi6h716g9sxzfsjk6b"))))
    (properties `((upstream-name . "CompR")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=CompR")
    (synopsis "Paired Comparison Data Analysis")
    (description
     "Different tools for describing and analysing paired comparison data are
presented.  Main methods are estimation of products scores according Bradley
Terry Luce model.  A segmentation of the individual could be conducted on the
basis of a mixture distribution approach.  The number of classes can be tested
by the use of Monte Carlo simulations.  This package deals also with
multi-criteria paired comparison data.")
    (license license:gpl2)))

(define-public r-comppareto
  (package
    (name "r-comppareto")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CompPareto" version))
       (sha256
        (base32 "1g2cas8pld75wjsvs73knpxyjlaggq5vrzb63hcv3bi29wcwjlzz"))))
    (properties `((upstream-name . "CompPareto")))
    (build-system r-build-system)
    (propagated-inputs (list r-actuar))
    (home-page "https://cran.r-project.org/package=CompPareto")
    (synopsis "Discrete Composite Distributions with Pareto Tails")
    (description
     "This package contains the probability density function, cumulative distribution
function, quantile function, and random number generator for composite and
discrete composite distributions with Pareto tails.  The detailed description of
the methods and the applications of the methods can be found in Bowen Liu,
Malwane M.A. Ananda (2023) <@code{arXiv:2309.16443>}.")
    (license license:gpl3)))

(define-public r-compoundevents
  (package
    (name "r-compoundevents")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CompoundEvents" version))
       (sha256
        (base32 "184dqy6dw6mrw1xpim335fmfnv0a8gmn2siqb4d5fa2rn5vghmcn"))))
    (properties `((upstream-name . "CompoundEvents")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CompoundEvents")
    (synopsis "Statistical Modeling of Compound Events")
    (description
     "This package provides tools for extracting occurrences, assessing potential
driving factors, predicting occurrences, and quantifying impacts of compound
events in hydrology and climatology.  Please see Hao Zengchao et al. (2019)
<doi:10.1088/1748-9326/ab4df5>.")
    (license license:gpl3)))

(define-public r-compound-cox
  (package
    (name "r-compound-cox")
    (version "3.31")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "compound.Cox" version))
       (sha256
        (base32 "0ynv2mpsph40dpkkf6fxw3kvk9x41wdfrk6332ghvfm7xn1aa97h"))))
    (properties `((upstream-name . "compound.Cox")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-numderiv r-mass))
    (home-page "https://cran.r-project.org/package=compound.Cox")
    (synopsis
     "Univariate Feature Selection and Compound Covariate for Predicting Survival, Including Copula-Based Analyses for Dependent Censoring")
    (description
     "Univariate feature selection and compound covariate methods under the Cox model
with high-dimensional features (e.g., gene expressions).  Available are survival
data for non-small-cell lung cancer patients with gene expressions (Chen et al
2007 New Engl J Med) <DOI:10.1056/NEJMoa060096>, statistical methods in Emura et
al (2012 P@code{LoS} ONE) <DOI:10.1371/journal.pone.0047627>, Emura & Chen (2016
Stat Methods Med Res) <DOI:10.1177/0962280214533378>, and Emura et al
(2019)<DOI:10.1016/j.cmpb.2018.10.020>.  Algorithms for generating correlated
gene expressions are also available.  Estimation of survival functions via
copula-graphic (CG) estimators is also implemented, which is useful for
sensitivity analyses under dependent censoring (Yeh et al 2023 Biomedicines)
<DOI:10.3390/biomedicines11030797> and factorial survival analyses (Emura et al
2024 Stat Methods Med Res) <DOI:10.1177/09622802231215805>.")
    (license license:gpl2)))

(define-public r-compositionalrf
  (package
    (name "r-compositionalrf")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CompositionalRF" version))
       (sha256
        (base32 "0brm03d9ypdc9k1klwmwb818gj7b1jr2z3968gs1qnnd8r8sr0bn"))))
    (properties `((upstream-name . "CompositionalRF")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfast r-multivariaterandomforest r-foreach
                             r-doparallel r-compositional))
    (home-page "https://cran.r-project.org/package=CompositionalRF")
    (synopsis "Multivariate Random Forest with Compositional Responses")
    (description
     "Non linear regression with compositional responses and Euclidean predictors is
performed.  The compositional data are first transformed using the additive
log-ratio transformation, and then the multivariate random forest of Rahman R.,
Otridge J. and Pal R. (2017), <doi:10.1093/bioinformatics/btw765>, is applied.")
    (license license:gpl2+)))

(define-public r-compositionalml
  (package
    (name "r-compositionalml")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CompositionalML" version))
       (sha256
        (base32 "1gnr8iqgwx461gm0ff1gvi6j8rw19a1lhz560hcq7sgymzp66l5r"))))
    (properties `((upstream-name . "CompositionalML")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfast2
                             r-rfast
                             r-ranger
                             r-foreach
                             r-e1071
                             r-doparallel
                             r-compositional
                             r-boruta))
    (home-page "https://cran.r-project.org/package=CompositionalML")
    (synopsis "Machine Learning with Compositional Data")
    (description
     "Machine learning algorithms for predictor variables that are compositional data
and the response variable is either continuous or categorical.  Specifically,
the Boruta variable selection algorithm, random forest, support vector machines
and projection pursuit regression are included.  Relevant papers include:
Tsagris M.T., Preston S. and Wood A.T.A. (2011). \"A data-based power
transformation for compositional data\".  Fourth International International
Workshop on Compositional Data Analysis. <doi:10.48550/@code{arXiv.1106.1451>}
and Alenazi, A. (2023). \"A review of compositional data analysis and recent
advances\".  Communications in Statistics--Theory and Methods, 52(16):
5535--5567. <doi:10.1080/03610926.2021.2014890>.")
    (license license:gpl2+)))

(define-public r-compositional
  (package
    (name "r-compositional")
    (version "7.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Compositional" version))
       (sha256
        (base32 "0x3q2cb2b6jgzczjxlw619q5id3ysldp8a3qvp937a212nqpvqks"))))
    (properties `((upstream-name . "Compositional")))
    (build-system r-build-system)
    (propagated-inputs (list r-sn
                             r-rnanoflann
                             r-rfast2
                             r-rfast
                             r-regda
                             r-quantreg
                             r-quadprog
                             r-nnet
                             r-mvhtests
                             r-mixture
                             r-minpack-lm
                             r-mda
                             r-matrix
                             r-mass
                             r-glmnet
                             r-foreach
                             r-energy
                             r-emplik
                             r-doparallel
                             r-cluster
                             r-bigstatsr))
    (home-page "https://cran.r-project.org/package=Compositional")
    (synopsis "Compositional Data Analysis")
    (description
     "Regression, classification, contour plots, hypothesis testing and fitting of
distributions for compositional data are some of the functions included.  We
further include functions for percentages (or proportions).  The standard
textbook for such data is John Aitchison's (1986) \"The statistical analysis of
compositional data\".  Relevant papers include: a) Tsagris M.T., Preston S. and
Wood A.T.A. (2011). \"A data-based power transformation for compositional data\".
Fourth International International Workshop on Compositional Data Analysis.
<doi:10.48550/@code{arXiv.1106.1451>} b) Tsagris M. (2014). \"The k-NN algorithm
for compositional data: a revised approach with and without zero values
present\".  Journal of Data Science, 12(3): 519--534.
<doi:10.6339/JDS.201407_12(3).0008>.  c) Tsagris M. (2015). \"A novel, divergence
based, regression for compositional data\".  Proceedings of the 28th Panhellenic
Statistics Conference, 15-18 April 2015, Athens, Greece, 430--444.
<doi:10.48550/@code{arXiv.1511.07600>}.  d) Tsagris M. (2015). \"Regression
analysis with compositional data containing zero values\".  Chilean Journal of
Statistics, 6(2): 47--57.
<https://soche.cl/chjs/volumes/06/02/Tsagris(2015).pdf>.  e) Tsagris M., Preston
S. and Wood A.T.A. (2016). \"Improved supervised classification for compositional
data using the alpha-transformation\".  Journal of Classification, 33(2):
243--261. <doi:10.1007/s00357-016-9207-5>.  f) Tsagris M., Preston S. and Wood
A.T.A. (2017). \"Nonparametric hypothesis testing for equality of means on the
simplex\".  Journal of Statistical Computation and Simulation, 87(2): 406--422.
<doi:10.1080/00949655.2016.1216554>.  g) Tsagris M. and Stewart C. (2018). \"A
Dirichlet regression model for compositional data with zeros\".  Lobachevskii
Journal of Mathematics, 39(3): 398--412. <doi:10.1134/S1995080218030198>.  h)
Alenazi A. (2019). \"Regression for compositional data with compositional data as
predictor variables with or without zero values\".  Journal of Data Science,
17(1): 219--238. <doi:10.6339/JDS.201901_17(1).0010>.  i) Tsagris M. and Stewart
C. (2020). \"A folded model for compositional data analysis\".  Australian and New
Zealand Journal of Statistics, 62(2): 249--277. <doi:10.1111/anzs.12289>.  j)
Alenazi A. (2021).  Alenazi, A. (2023). \"A review of compositional data analysis
and recent advances\".  Communications in Statistics--Theory and Methods, 52(16):
5535--5567. <doi:10.1080/03610926.2021.2014890>.  k) Alenazi A.A. (2022).
\"f-divergence regression models for compositional data\".  Pakistan Journal of
Statistics and Operation Research, 18(4): 867--882.
<doi:10.18187/pjsor.v18i4.3969>.  l) Tsagris M. and Stewart C. (2022). \"A Review
of Flexible Transformations for Modeling Compositional Data\".  In Advances and
Innovations in Statistics and Data Science, pp.  225--234.
<doi:10.1007/978-3-031-08329-7_10>.  m) Tsagris M., Alenazi A. and Stewart C.
(2023). \"Flexible non-parametric regression models for compositional response
data with zeros\".  Statistics and Computing, 33(106).
<doi:10.1007/s11222-023-10277-5>.  n) Tsagris.  M. (2024). \"Constrained least
squares simplicial-simplicial regression\".
<doi:10.48550/@code{arXiv.2403.19835>}.")
    (license license:gpl2+)))

(define-public r-compositereliabilityinnesteddesigns
  (package
    (name "r-compositereliabilityinnesteddesigns")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "compositeReliabilityInNestedDesigns" version))
       (sha256
        (base32 "13936214rr398758sw3l534fr4qr8b83bm4ygjbvfj9k33df2xby"))))
    (properties `((upstream-name . "compositeReliabilityInNestedDesigns")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rsolnp
                             r-reshape2
                             r-psych
                             r-plyr
                             r-magrittr
                             r-lme4
                             r-ggplot2
                             r-dplyr))
    (home-page
     "https://github.com/jmoonen/compositeReliabilityInNestedDesigns")
    (synopsis
     "Optimizing the Composite Reliability in Multivariate Nested Designs")
    (description
     "The reliability of assessment tools is a crucial aspect of monitoring student
performance in various educational settings.  It ensures that the assessment
outcomes accurately reflect a student's true level of performance.  However,
when assessments are combined, determining composite reliability can be
challenging, especially for naturalistic and unbalanced datasets in nested
design as is often the case for Workplace-Based Assessments.  This package is
designed to estimate composite reliability in nested designs using multivariate
generalizability theory and enhance the analysis of assessment data.  The
package allows for the inclusion of weight per assessment type and produces
extensive G- and D-study results with graphical interpretations, and options to
find the set of weights that maximizes the composite reliability or minimizes
the standard error of measurement (SEM).")
    (license license:gpl3+)))

(define-public r-compositereliability
  (package
    (name "r-compositereliability")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CompositeReliability" version))
       (sha256
        (base32 "04qpwqrz1x1hdjfin77fb4kywv9sspzdq7kn4f7jxaaz3ykhrhkc"))))
    (properties `((upstream-name . "CompositeReliability")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rsolnp
                             r-reshape2
                             r-psych
                             r-plyr
                             r-magrittr
                             r-lme4
                             r-ggplot2
                             r-dplyr))
    (home-page "https://github.com/jmoonen/CompositeReliability")
    (synopsis
     "Determine the Composite Reliability of a Naturalistic, Unbalanced Dataset")
    (description
     "The reliability of assessment tools is a crucial aspect of monitoring student
performance in various educational settings.  It ensures that the assessment
outcomes accurately reflect a student's true level of performance.  However,
when assessments are combined, determining composite reliability can be
challenging, especially for naturalistic and unbalanced datasets.  This package
provides an easy-to-use solution for calculating composite reliability for
different assessment types.  It allows for the inclusion of weight per
assessment type and produces extensive G- and D-study results with graphical
interpretations.  Overall, our approach enhances the reliability of composite
assessments, making it suitable for various education contexts.")
    (license license:gpl3+)))

(define-public r-compoissonreg
  (package
    (name "r-compoissonreg")
    (version "0.8.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "COMPoissonReg" version))
       (sha256
        (base32 "0a03v9b3mv214y2ky94z8y363x6b97a68kvypvan56m0mg0zzq3d"))))
    (properties `((upstream-name . "COMPoissonReg")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-numderiv))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/lotze/COMPoissonReg")
    (synopsis "Conway-Maxwell Poisson (COM-Poisson) Regression")
    (description
     "Fit Conway-Maxwell Poisson (COM-Poisson or CMP) regression models to count data
(Sellers & Shmueli, 2010) <doi:10.1214/09-AOAS306>.  The package provides
functions for model estimation, dispersion testing, and diagnostics.
Zero-inflated CMP regression (Sellers & Raim, 2016)
<doi:10.1016/j.csda.2016.01.007> is also supported.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-compmodels
  (package
    (name "r-compmodels")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CompModels" version))
       (sha256
        (base32 "1373m324zq7f3wffb25ypjidvsxki0p64iv4qy8i887g4f8inq6q"))))
    (properties `((upstream-name . "CompModels")))
    (build-system r-build-system)
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=CompModels")
    (synopsis "Pseudo Computer Models for Optimization")
    (description
     "This package provides a suite of computer model test functions that can be used
to test and evaluate algorithms for Bayesian (also known as sequential)
optimization.  Some of the functions have known functional forms, however, most
are intended to serve as black-box functions where evaluation requires running
computer code that reveals little about the functional forms of the objective
and/or constraints.  The primary goal of the package is to provide users
(especially those who do not have access to real computer models) a source of
reproducible and shareable examples that can be used for benchmarking
algorithms.  The package is a living repository, and so more functions will be
added over time.  For function suggestions, please do contact the author of the
package.")
    (license license:gpl2)))

(define-public r-compmix
  (package
    (name "r-compmix")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CompMix" version))
       (sha256
        (base32 "1b7vmkyqh8m2p72wr469anwqwghiw6m9f1p8q3mr6l1pgx7nqhsn"))))
    (properties `((upstream-name . "CompMix")))
    (build-system r-build-system)
    (propagated-inputs (list r-superlearner
                             r-randomforest
                             r-qgcomp
                             r-proc
                             r-mvtnorm
                             r-matrix
                             r-higlasso
                             r-hiernet
                             r-gwqs
                             r-glmnet
                             r-gglasso
                             r-devtools
                             r-bkmr))
    (home-page "https://cran.r-project.org/package=CompMix")
    (synopsis
     "Comprehensive Toolkit for Environmental Mixtures Analysis ('CompMix')")
    (description
     "Quantitative characterization of the health impacts associated with exposure to
chemical mixtures has received considerable attention in current environmental
and epidemiological studies. @code{CompMix} package allows practitioners to
estimate the health impacts from exposure to chemical mixtures data through
various statistical approaches, including Lasso, Elastic net, Bayeisan kernel
machine regression (BKMR), @code{hierNet}, Quantile g-computation, Weighted
quantile sum (WQS) and Random forest.  Hao W, Cathey A, Aung M, Boss J, Meeker
J, Mukherjee B. (2024) \"Statistical methods for chemical mixtures: a
practitioners guide\". <DOI:10.1101/2024.03.03.24303677>.")
    (license license:gpl3)))

(define-public r-complmrob
  (package
    (name "r-complmrob")
    (version "0.7.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "complmrob" version))
       (sha256
        (base32 "0dvkc5y53041agkjz3rl898hkq686pxzr6flf2qx1g3jbza3pk1y"))))
    (properties `((upstream-name . "complmrob")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales r-robustbase r-ggplot2 r-boot))
    (home-page "https://github.com/dakep/complmrob")
    (synopsis "Robust Linear Regression with Compositional Data as Covariates")
    (description
     "Robust regression methods for compositional data.  The distribution of the
estimates can be approximated with various bootstrap methods.  These bootstrap
methods are available for the compositional as well as for standard robust
regression estimates.  This allows for direct comparison between them.")
    (license license:gpl2+)))

(define-public r-complexnet
  (package
    (name "r-complexnet")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "complexNet" version))
       (sha256
        (base32 "199zxqsbasd1j598srpb10y8mjw2l4plra1121i9sdsf40bvd7aw"))))
    (properties `((upstream-name . "complexNet")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://marcosmolla.github.io/complexNet/")
    (synopsis "Complex Network Generation")
    (description
     "Providing a set of functions to easily generate and iterate complex networks.
The functions can be used to generate realistic networks with a wide range of
different clustering, density, and average path length.  For more information
consult research articles by Amiyaal Ilany and Erol Akcay (2016)
<doi:10.1093/icb/icw068> and Ilany and Erol Akcay (2016) <doi:10.1101/026120>,
which have inspired many methods in this package.")
    (license license:gpl3)))

(define-public r-complexlm
  (package
    (name "r-complexlm")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "complexlm" version))
       (sha256
        (base32 "0ykshrqia09pklkwhvjc8mfn005yq5wxfpjsbimg8gp38xch3wvn"))))
    (properties `((upstream-name . "complexlm")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma r-mathjaxr r-mass))
    (home-page "https://github.com/QuantumOfMoose/complexlm")
    (synopsis "Linear Fitting for Complex Valued Data")
    (description
     "This package provides tools for linear fitting with complex variables.  Includes
ordinary least-squares (zlm()) and robust M-estimation (rzlm()), and complex
methods for oft used generics.  Originally adapted from the rlm() functions of
MASS and the lm() functions of stats'.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-complexity
  (package
    (name "r-complexity")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "complexity" version))
       (sha256
        (base32 "0y1rlz456mny4d0kr8rx26qg5frr3zxsbzm1cc76h475vad4ns28"))))
    (properties `((upstream-name . "complexity")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-combinat))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=complexity")
    (synopsis
     "Calculate the Proportion of Permutations in Line with an Informative Hypothesis")
    (description
     "Allows for the easy computation of complexity: the proportion of the parameter
space in line with the hypothesis by chance.  The package comes with a Shiny
application in which the calculations can be conducted as well.")
    (license license:gpl2+)))

(define-public r-complex
  (package
    (name "r-complex")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "complex" version))
       (sha256
        (base32 "1f1xyvapswfsd7gbw8279m1pdjrry68hkci69d9h3gwav2v3fi4l"))))
    (properties `((upstream-name . "complex")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo
                             r-rcpp
                             r-pracma
                             r-nloptr
                             r-mvtnorm
                             r-legion
                             r-greybox))
    (home-page "https://github.com/config-i1/complex")
    (synopsis "Time Series Analysis and Forecasting Using Complex Variables")
    (description
     "Set of function implementing the instruments for complex-valued modelling,
including time series analysis and forecasting.  This is based on the monograph
by Svetunkov Sergey and Svetunkov Ivan \"Complex-valued Econometrics with
Examples in R\" which is in press by Springer (expected to be published in 2024).")
    (license license:lgpl2.1)))

(define-public r-completejourney
  (package
    (name "r-completejourney")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "completejourney" version))
       (sha256
        (base32 "0ysbpmd7rglz3diy2cpcgvmmcnysradb4ddiwix7kbhzrhvhrdrs"))))
    (properties `((upstream-name . "completejourney")))
    (build-system r-build-system)
    (propagated-inputs (list r-zeallot
                             r-tibble
                             r-stringr
                             r-progress
                             r-dplyr
                             r-curl))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/bradleyboehmke/completejourney")
    (synopsis "Retail Shopping Data")
    (description
     "Retail shopping transactions for 2,469 households over one year.  Originates
from the 84.51Â° Complete Journey 2.0 source files <https://www.8451.com/area51>
which also includes useful metadata on products, coupons, campaigns, and
promotions.")
    (license license:cc0)))

(define-public r-compindpca
  (package
    (name "r-compindpca")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "compindPCA" version))
       (sha256
        (base32 "1v7fppbb1pswd1d1bw0szmmjc51smnmal5psd98ms5cfm7yv597g"))))
    (properties `((upstream-name . "compindPCA")))
    (build-system r-build-system)
    (propagated-inputs (list r-factoextra))
    (home-page "https://cran.r-project.org/package=compindPCA")
    (synopsis
     "Computation of Relative Weights of Variables and Composite Index Values Based on PCA")
    (description
     "It helps in development of a principal component analysis based composite index
by assigning weights to variables and combining the weighted variables.  For
method details see Sendhil, R., Jha, A., Kumar, A. and Singh, S. (2018).
<doi:10.1016/j.ecolind.2018.02.053>, and Wu, T. (2021).
<doi:10.1016/j.ecolind.2021.108006>.")
    (license license:gpl3)))

(define-public r-compindexr
  (package
    (name "r-compindexr")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "compindexR" version))
       (sha256
        (base32 "1glc1y6wa1g7zxj1xwj0fgcfsy118xhd637gi8zsz7l9vxj614cp"))))
    (properties `((upstream-name . "compindexR")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma r-nlcoptim r-dplyr r-car))
    (home-page "https://github.com/olgnaydn/compindexR")
    (synopsis "Calculates Composite Index")
    (description
     "It uses the first-order sensitivity index to measure whether the weights
assigned by the creator of the composite indicator match the actual importance
of the variables.  Moreover, the variance inflation factor is used to reduce the
set of correlated variables.  In the case of a discrepancy between the
importance and the assigned weight, the script determines weights that allow
adjustment of the weights to the intended impact of variables.  If the optimised
weights are unable to reflect the desired importance, the highly correlated
variables are reduced, taking into account variance inflation factor.  The final
outcome of the script is the calculated value of the composite indicator based
on optimal weights and a reduced set of variables, and the linear ordering of
the analysed objects.")
    (license license:gpl3+)))

(define-public r-compind
  (package
    (name "r-compind")
    (version "3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Compind" version))
       (sha256
        (base32 "0k45gazca94dscqhy05p68k755al4gd1gilz5svq5h6cv5fijhxk"))))
    (properties `((upstream-name . "Compind")))
    (build-system r-build-system)
    (propagated-inputs (list r-spdep
                             r-sp
                             r-smaa
                             r-rcompadre
                             r-psych
                             r-np
                             r-nonparaeff
                             r-mass
                             r-lpsolve
                             r-hmisc
                             r-gwmodel
                             r-gparotation
                             r-factominer
                             r-boot
                             r-benchmarking))
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=Compind")
    (synopsis "Composite Indicators Functions")
    (description
     "This package provides a collection of functions to calculate Composite
Indicators methods, focusing, in particular, on the normalisation and
weighting-aggregation steps, as described in OECD Handbook on constructing
composite indicators: methodology and user guide
<https://www.oecd-ilibrary.org/economics/handbook-on-constructing-composite-indicators-methodology-and-user-guide_9789264043466-en>,
Vidoli and Fusco and Mazziotta <doi:10.1007/s11205-014-0710-y>, Mazziotta and
Pareto (2016) <doi:10.1007/s11205-015-0998-2>, Van Puyenbroeck and Rogge
<doi:10.1016/j.ejor.2016.07.038> and other authors.")
    (license license:gpl3)))

(define-public r-comphclust
  (package
    (name "r-comphclust")
    (version "1.0-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "compHclust" version))
       (sha256
        (base32 "0agay7rn5mrw07imz4l547b7m9pfcg3rhz4krfxrvg1q2z2kryvj"))))
    (properties `((upstream-name . "compHclust")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=compHclust")
    (synopsis "Complementary Hierarchical Clustering")
    (description
     "This package performs the complementary hierarchical clustering procedure and
returns X (the expected residual matrix) and a vector of the relative gene
importances.")
    (license license:gpl2+)))

(define-public r-compgr
  (package
    (name "r-compgr")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CompGR" version))
       (sha256
        (base32 "0ck4kmb4h2i7qgikmy7i0cwhf14nh71pdf4mnss4ahxac4xsh2rr"))))
    (properties `((upstream-name . "CompGR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CompGR")
    (synopsis "Complete Annual Growth Rate Generator")
    (description
     "It is designed to streamline the process of calculating complete annual growth
rates with user-friendly functions and robust algorithms.  It enables
researchers and analysts to effortlessly generate precise growth rate estimates
for their data.  For method details see, Sharma, M.K.(2013)
<https://www.indianjournals.com/ijor.aspx?target=ijor:jfl&volume=26&issue=1and2&article=018>.
 It offers a comprehensive suite of functions and customisable parameters.
Equipped to handle varying complexities in data structures.  It empowers users
to uncover insightful growth dynamics and make informed decisions.")
    (license license:gpl2+)))

(define-public r-compexpdes
  (package
    (name "r-compexpdes")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CompExpDes" version))
       (sha256
        (base32 "0asr1ghsdqnxp7bvzypx3zyr0i1gcx1c0g973zz9gizpvym6q5j8"))))
    (properties `((upstream-name . "CompExpDes")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CompExpDes")
    (synopsis "Computer Experiment Designs")
    (description
     "In computer experiments space-filling designs are having great impact.  Most
popularly used space-filling designs are Uniform designs (UDs), Latin hypercube
designs (LHDs) etc.  For further references one can see Mckay (1979)
<DOI:10.1080/00401706.1979.10489755> and Fang (1980)
<https://cir.nii.ac.jp/crid/1570291225616774784>.  In this package, we have
provided algorithms for generate efficient LHDs and UDs.  Here, generated LHDs
are efficient as they possess lower value of Maxpro measure, Phi_p value and
Maximum Absolute Correlation (MAC) value based on the weightage given to each
criterion.  On the other hand, the produced UDs are having good space-filling
property as they always attain the lower bound of Discrete Discrepancy measure.
Further, some useful functions added in this package for adding more value to
this package.")
    (license license:gpl2+)))

(define-public r-competitiontoolbox
  (package
    (name "r-competitiontoolbox")
    (version "0.7.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "competitiontoolbox" version))
       (sha256
        (base32 "0s8n62hssx0qkznf0x6gw9yzlngiqgjw34k9wyhlh5iiwq4fyc3x"))))
    (properties `((upstream-name . "competitiontoolbox")))
    (build-system r-build-system)
    (propagated-inputs (list r-trade r-shiny r-rhandsontable r-ggplot2
                             r-antitrust))
    (home-page "https://github.com/luciu5/competitiontoolbox")
    (synopsis "Graphical User Interface for Antitrust and Trade Practitioners")
    (description
     "This package provides a graphical user interface for simulating the effects of
mergers, tariffs, and quotas under an assortment of different economic models.
The interface is powered by the Shiny web application framework from RStudio'.")
    (license license:cc0)))

(define-public r-comperes
  (package
    (name "r-comperes")
    (version "0.2.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comperes" version))
       (sha256
        (base32 "1qcrm0mw90gkx0dcka2bsszrmcbl46lrbgp5i58xbws9s5i54lff"))))
    (properties `((upstream-name . "comperes")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-tibble r-rlang r-magrittr r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/echasnovski/comperes")
    (synopsis "Manage Competition Results")
    (description
     "This package provides tools for storing and managing competition results.
Competition is understood as a set of games in which players gain some abstract
scores.  There are two ways for storing results: in long (one row per
game-player) and wide (one row per game with fixed amount of players) formats.
This package provides functions for creation and conversion between them.  Also
there are functions for computing their summary and Head-to-Head values for
players.  They leverage grammar of data manipulation from dplyr'.")
    (license license:expat)))

(define-public r-comperank
  (package
    (name "r-comperank")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comperank" version))
       (sha256
        (base32 "0wz46rkpx1cjjng3i03pms2x27cik9wbx7al5r289ym3664zb83m"))))
    (properties `((upstream-name . "comperank")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-rlang r-rcpp r-dplyr r-comperes))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/echasnovski/comperank")
    (synopsis "Ranking Methods for Competition Results")
    (description
     "Compute ranking and rating based on competition results.  Methods of different
nature are implemented: with fixed Head-to-Head structure, with variable
Head-to-Head structure and with iterative nature.  All algorithms are taken from
the book Whoâs #1?: The science of rating and ranking by Amy N. Langville and
Carl D. Meyer (2012, ISBN:978-0-691-15422-0).")
    (license license:expat)))

(define-public r-compdist
  (package
    (name "r-compdist")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CompDist" version))
       (sha256
        (base32 "02c18ksk6clv674yh79bzg3mh9hymzhal51j6g0rnvqd5ra8g66c"))))
    (properties `((upstream-name . "CompDist")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam
                             r-rmutil
                             r-pearsonds
                             r-numderiv
                             r-fextremes
                             r-actuar))
    (home-page "https://cran.r-project.org/package=CompDist")
    (synopsis "Multisection Composite Distributions")
    (description
     "Computes density function, cumulative distribution function, quantile function
and random numbers for a multisection composite distribution specified by the
user.  Also fits the user specified distribution to a given data set.  More
details of the package can be found in the following paper submitted to the R
journal Wiegand M and Nadarajah S (2017) @code{CompDist}: Multisection composite
distributions.")
    (license license:gpl2+)))

(define-public r-compas
  (package
    (name "r-compas")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "compas" version))
       (sha256
        (base32 "0hhqg2xsifnh1v931mmfij6s5idy9s984hdnrkp9n3f3azgwvcz4"))))
    (properties `((upstream-name . "compas")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppeigen r-rcpp r-bio3d))
    (home-page "https://cran.r-project.org/package=compas")
    (synopsis "Conformational Manipulations of Protein Atomic Structures")
    (description
     "Manipulate and analyze 3-D structural geometry of Protein Data Bank (PDB) files.")
    (license license:gpl3)))

(define-public r-comparisonsurv
  (package
    (name "r-comparisonsurv")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ComparisonSurv" version))
       (sha256
        (base32 "0lidakxb1ab6bpb7sf2arjl1xpym1lzxbh63g0x4c2dm7h0kzkwi"))))
    (properties `((upstream-name . "ComparisonSurv")))
    (build-system r-build-system)
    (propagated-inputs (list r-tshrc r-survrm2 r-survival r-muhaz))
    (home-page "https://cran.r-project.org/package=ComparisonSurv")
    (synopsis "Comparison of Survival Curves Between Two Groups")
    (description
     "Various statistical methods for survival analysis in comparing survival curves
between two groups, including overall hypothesis tests described in Li et al.
(2015) <doi:10.1371/journal.pone.0116774> and Huang et al. (2020)
<doi:10.1080/03610918.2020.1753075>, fixed-point tests in Klein et al. (2007)
<doi:10.1002/sim.2864>, short-term tests, and long-term tests in Logan et al.
(2008) <doi:10.1111/j.1541-0420.2007.00975.x>.  Some commonly used descriptive
statistics and plots are also included.")
    (license license:gpl2)))

(define-public r-comparison
  (package
    (name "r-comparison")
    (version "1.0.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comparison" version))
       (sha256
        (base32 "0q5x1ank48w9zsfxswahjl7v6f46qxj70lvyn2pj7sz78nfpqjj6"))))
    (properties `((upstream-name . "comparison")))
    (build-system r-build-system)
    (propagated-inputs (list r-isotone r-cvglasso))
    (home-page "https://github.com/jmcurran/comparison")
    (synopsis "Multivariate Likelihood Ratio Calculation and Evaluation")
    (description
     "This package provides functions for calculating and evaluating likelihood ratios
from uni/multivariate continuous observations.")
    (license license:gpl2+)))

(define-public r-comparetests
  (package
    (name "r-comparetests")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CompareTests" version))
       (sha256
        (base32 "1z96kh851bpr2szgyjszkpv6m5ma6abz7hrm50fgvfpgxkj7f4yi"))))
    (properties `((upstream-name . "CompareTests")))
    (build-system r-build-system)
    (home-page
     "http://dceg.cancer.gov/about/staff-directory/biographies/A-J/katki-hormuzd")
    (synopsis
     "Correct for Verification Bias in Diagnostic Accuracy & Agreement")
    (description
     "This package provides a standard test is observed on all specimens.  We treat
the second test (or sampled test) as being conducted on only a stratified sample
of specimens.  Verification Bias is this situation when the specimens for doing
the second (sampled) test is not under investigator control.  We treat the total
sample as stratified two-phase sampling and use inverse probability weighting.
We estimate diagnostic accuracy (category-specific classification probabilities;
for binary tests reduces to specificity and sensitivity, and also predictive
values) and agreement statistics (percent agreement, percent agreement by
category, Kappa (unweighted), Kappa (quadratic weighted) and symmetry tests
(reduces to @code{McNemar's} test for binary tests)).  See: Katki HA, Li Y,
Edelstein DW, Castle PE. Estimating the agreement and diagnostic accuracy of two
diagnostic tests when one test is conducted on only a subsample of specimens.
Stat Med.  2012 Feb 28; 31(5) <doi:10.1002/sim.4422>.")
    (license license:gpl3)))

(define-public r-comparer
  (package
    (name "r-comparer")
    (version "0.2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comparer" version))
       (sha256
        (base32 "0jyqnma93z9fihcnpgxm6d6r2dah15ap5ii3l1d3ddbhs1b56y37"))))
    (properties `((upstream-name . "comparer")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmarkdown
                             r-r6
                             r-progress
                             r-plyr
                             r-mixopt
                             r-gaupro))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/CollinErickson/comparer")
    (synopsis "Compare Output and Run Time")
    (description
     "Quickly run experiments to compare the run time and output of code blocks.  The
function mbc() can make fast comparisons of code, and will calculate statistics
comparing the resulting outputs.  It can be used to compare model fits to the
same data or see which function runs faster.  The R6 class ffexp$new() runs a
function using all possible combinations of selected inputs.  This is useful for
comparing the effect of different parameter values.  It can also run in parallel
and automatically save intermediate results, which is very useful for long
computations.")
    (license license:gpl3)))

(define-public r-comparemultiplemodels
  (package
    (name "r-comparemultiplemodels")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CompareMultipleModels" version))
       (sha256
        (base32 "0qzybbxx5kqlrb260c0wh2vhp3ci5wk6853mm01wfyivhvf7sz0h"))))
    (properties `((upstream-name . "CompareMultipleModels")))
    (build-system r-build-system)
    (propagated-inputs (list r-ceemdanml))
    (home-page "https://cran.r-project.org/package=CompareMultipleModels")
    (synopsis "Finding the Best Model Using Eight Metrics Values")
    (description
     "In statistical modeling, multiple models need to be compared based on certain
criteria.  The method described here uses eight metrics from @code{AllMetrics}
package.  âinput_dfâ is the data frame (at least two columns for comparison)
containing metrics values in different rows of a column (which denotes a
particular modelâs performance).  First five metrics are expected to be
minimum and last three metrics are expected to be maximum for a model to be
considered good.  Firstly, every metric value (among first five) is searched in
every columns and minimum values are denoted as âMINâ and other values are
denoted as âNAâ.  Secondly, every metric (among last three) is searched in
every columns and maximum values are denoted as âMAXâ and other values are
denoted as âNAâ.  âoutput_dfâ contains the similar number of rows (which
is 8) and columns (which is number of models to be compared) as of
âinput_dfâ.  Values in âoutput_dfâ are corresponding âNAâ, âMINâ
or âMAXâ.  Finally, the column containing minimum number of âNAâ values
is denoted as the best column.  âmin_NA_colâ gives the name of the best
column (model).  âmin_NA_valuesâ are the corresponding metrics values.
â@code{BestColumn_metricsâ} is the data frame (dimension: 1*8) containing
different metrics of the best column (model).  âbest_column_resultsâ is the
final result (a list) containing all of these output elements.  In special case,
if two columns having equal NA', it will be checked among these two column which
one is having least NA in first five rows and will be inferred as the best.
More details about @code{AllMetrics} can be found in Garai (2023)
<doi:10.13140/RG.2.2.18688.30723>.")
    (license license:gpl3)))

(define-public r-comparemcmcs
  (package
    (name "r-comparemcmcs")
    (version "0.6.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "compareMCMCs" version))
       (sha256
        (base32 "0h55azjbz7lr78y65ypjmqri6g69cwmjwpj50kgk3kw2phla1pqw"))))
    (properties `((upstream-name . "compareMCMCs")))
    (build-system r-build-system)
    (propagated-inputs (list r-xtable
                             r-rlang
                             r-reshape2
                             r-r6
                             r-nimble
                             r-ggplot2
                             r-dplyr
                             r-coda))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/nimble-dev/compareMCMCs")
    (synopsis
     "Compare MCMC Efficiency from 'nimble' and/or Other MCMC Engines")
    (description
     "Manages comparison of MCMC performance metrics from multiple MCMC algorithms.
These may come from different MCMC configurations using the nimble package or
from other packages.  Plug-ins for JAGS via rjags and Stan via rstan are
provided.  It is possible to write plug-ins for other packages.  Performance
metrics are held in an MCMCresult class along with samples and timing data.  It
is easy to apply new performance metrics.  Reports are generated as html pages
with figures comparing sets of runs.  It is possible to configure the html
pages, including providing new figure components.")
    (license (list license:bsd-3 license:gpl2+))))

(define-public r-comparegroups
  (package
    (name "r-comparegroups")
    (version "4.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "compareGroups" version))
       (sha256
        (base32 "1kfnwyi41l11nvmjjays23k8lwc1wzh6q65rmjff2s7sxx994cin"))))
    (properties `((upstream-name . "compareGroups")))
    (build-system r-build-system)
    (propagated-inputs (list r-writexl
                             r-survival
                             r-rmarkdown
                             r-pmcmrplus
                             r-officer
                             r-knitr
                             r-kableextra
                             r-hardyweinberg
                             r-flextable
                             r-chron))
    (native-inputs (list r-knitr))
    (home-page "https://isubirana.github.io/compareGroups/index.html")
    (synopsis "Descriptive Analysis by Groups")
    (description
     "Create data summaries for quality control, extensive reports for exploring data,
as well as publication-ready univariate or bivariate tables in several formats
(plain text, HTML,@code{LaTeX}, PDF, Word or Excel.  Create figures to quickly
visualise the distribution of your data (boxplots, barplots, normality-plots,
etc.).  Display statistics (mean, median, frequencies, incidences, etc.).
Perform the appropriate tests (t-test, Analysis of variance, Kruskal-Wallis,
Fisher, log-rank, ...) depending on the nature of the described variable
(normal, non-normal or qualitative).  Summarize genetic data (Single Nucleotide
Polymorphisms) data displaying Allele Frequencies and performing Hardy-Weinberg
Equilibrium tests among other typical statistics and tests for these kind of
data.")
    (license license:gpl2+)))

(define-public r-comparedf
  (package
    (name "r-comparedf")
    (version "2.3.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "compareDF" version))
       (sha256
        (base32 "1sq30ndlidpmyvpqkzhq5shy52i22p80lcfar3p8dqymndg1bgyl"))))
    (properties `((upstream-name . "compareDF")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-openxlsx
                             r-htmltable
                             r-dplyr
                             r-data-table))
    (home-page "https://cran.r-project.org/package=compareDF")
    (synopsis
     "Do a Git Style Diff of the Rows Between Two Dataframes with Similar Structure")
    (description
     "Compares two dataframes which have the same column structure to show the rows
that have changed.  Also gives a git style diff format to quickly see what has
changed in addition to summary statistics.")
    (license license:expat)))

(define-public r-comparedesign
  (package
    (name "r-comparedesign")
    (version "2.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CompAREdesign" version))
       (sha256
        (base32 "0jdfrn8p13d369gwfkyiydwv6451gvz8qiiij74bj2zjpq7z6kc7"))))
    (properties `((upstream-name . "CompAREdesign")))
    (build-system r-build-system)
    (propagated-inputs (list r-rootsolve r-numderiv r-ggpubr r-ggplot2
                             r-copula))
    (home-page "https://cran.r-project.org/package=CompAREdesign")
    (synopsis
     "Statistical Functions for the Design of Studies with Composite Endpoints")
    (description
     "It has been designed to calculate the required sample size in randomized
clinical trials with composite endpoints.  It also calculates the expected
effect and the probability of observing the composite endpoint, among others.
The methodology can be found in Bofill & GÃ³mez (2019) <doi:10.1002/sim.8092>
and GÃ³mez & Lagakos (2013) <doi:10.1002/sim.5547>.")
    (license license:gpl3)))

(define-public r-comparecausalnetworks
  (package
    (name "r-comparecausalnetworks")
    (version "0.2.6.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CompareCausalNetworks" version))
       (sha256
        (base32 "0r8gdr834jqqwiq9h4yz19gcg92rbdd4fr3fwi083vfjml82f0v0"))))
    (properties `((upstream-name . "CompareCausalNetworks")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-expm r-data-table))
    (home-page "https://github.com/christinaheinze/CompareCausalNetworks")
    (synopsis "Interface to Diverse Estimation Methods of Causal Networks")
    (description
     "Unified interface for the estimation of causal networks, including the methods
@code{backShift} (from package @code{backShift}'), @code{bivariateANM}
(bivariate additive noise model), @code{bivariateCAM} (bivariate causal additive
model), CAM (causal additive model) (from package CAM'; the package is
temporarily unavailable on the CRAN repository; formerly available versions can
be obtained from the archive), @code{hiddenICP} (invariant causal prediction
with hidden variables), ICP (invariant causal prediction) (from package
@code{InvariantCausalPrediction}'), GES (greedy equivalence search), GIES
(greedy interventional equivalence search), LINGAM', PC (PC Algorithm), FCI
(fast causal inference), RFCI (really fast causal inference) (all from package
pcalg') and regression.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-comparec
  (package
    (name "r-comparec")
    (version "1.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "compareC" version))
       (sha256
        (base32 "0r3d03yj5fjzfc6awc16x9420366dcy3nhvibjlrn0m10il714pc"))))
    (properties `((upstream-name . "compareC")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=compareC")
    (synopsis
     "Compare Two Correlated C Indices with Right-Censored Survival Outcome")
    (description
     "Proposed by Harrell, the C index or concordance C, is considered an overall
measure of discrimination in survival analysis between a survival outcome that
is possibly right censored and a predictive-score variable, which can represent
a measured biomarker or a composite-score output from an algorithm that combines
multiple biomarkers.  This package aims to statistically compare two C indices
with right-censored survival outcome, which commonly arise from a paired design
and thus resulting two correlated C indices.")
    (license license:gpl2+)))

(define-public r-comparator
  (package
    (name "r-comparator")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comparator" version))
       (sha256
        (base32 "1mygip50mc3jni1zc6jhjg2mx61sjgdq5w7snqdvv1rycp3fdpb1"))))
    (properties `((upstream-name . "comparator")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-proxy r-clue))
    (home-page "https://github.com/ngmarchant/comparator")
    (synopsis "Comparison Functions for Clustering and Record Linkage")
    (description
     "This package implements functions for comparing strings, sequences and numeric
vectors for clustering and record linkage applications.  Supported comparison
functions include: generalized edit distances for comparing sequences/strings,
Monge-Elkan similarity for fuzzy comparison of token sets, and L-p distances for
comparing numeric vectors.  Where possible, comparison functions are implemented
in C/C++ to ensure good performance.")
    (license license:gpl2+)))

(define-public r-comp2roc
  (package
    (name "r-comp2roc")
    (version "1.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Comp2ROC" version))
       (sha256
        (base32 "06hpbid9z1pzg7k4gqp2zn8l7sm375z32fsn54i27qbl3inp7m2d"))))
    (properties `((upstream-name . "Comp2ROC")))
    (build-system r-build-system)
    (propagated-inputs (list r-rocr r-boot))
    (home-page "https://cran.r-project.org/package=Comp2ROC")
    (synopsis "Compare Two ROC Curves that Intersect")
    (description
     "Comparison of two ROC curves through the methodology proposed by Ana C. Braga.")
    (license license:gpl2)))

(define-public r-comorosmaps
  (package
    (name "r-comorosmaps")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comorosmaps" version))
       (sha256
        (base32 "1rjsgvln5wa7bbh4iqpfvmdqvmx4cgl8mxxkar76rkam9r54hwhv"))))
    (properties `((upstream-name . "comorosmaps")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf r-magrittr r-dplyr))
    (home-page "https://github.com/hhousni/comorosmaps")
    (synopsis "Comoro Islands Maps")
    (description
     "Maps of Comoro Islands.  Layers include the country coastline, each island
coastline and administrative regions boundaries.")
    (license license:expat)))

(define-public r-comorbidpgs
  (package
    (name "r-comorbidpgs")
    (version "0.3.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comorbidPGS" version))
       (sha256
        (base32 "1dy8yfyy88vw2x8mk6n3nx2dbkf17m4ibvbkxhrywralvll0wspa"))))
    (properties `((upstream-name . "comorbidPGS")))
    (build-system r-build-system)
    (propagated-inputs (list r-nnet r-mass r-ggplot2))
    (home-page "https://cran.r-project.org/package=comorbidPGS")
    (synopsis
     "Assessing Predisposition Between Phenotypes using Polygenic Scores")
    (description
     "Using polygenic scores (PGS, or PRS/GRS for binary outcomes), this package
allows to investigate shared predisposition between different conditions, and do
fast association analysis, export plots and views of the PGS distribution using
ggplot2 object.")
    (license license:gpl3+)))

(define-public r-comorbidity
  (package
    (name "r-comorbidity")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comorbidity" version))
       (sha256
        (base32 "1j86631kyh774hs6a4ivmhkbj6kc733vy0pn1sa86yh0s6iqbmdb"))))
    (properties `((upstream-name . "comorbidity")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi r-data-table r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://ellessenne.github.io/comorbidity/")
    (synopsis "Computing Comorbidity Scores")
    (description
     "Computing comorbidity indices and scores such as the weighted Charlson score
(Charlson, 1987 <doi:10.1016/0021-9681(87)90171-8>) and the Elixhauser
comorbidity score (Elixhauser, 1998 <doi:10.1097/00005650-199801000-00004>)
using ICD-9-CM or ICD-10 codes (Quan, 2005
<doi:10.1097/01.mlr.0000182534.19832.83>).  Australian and Swedish modifications
of the Charlson Comorbidity Index are available as well (Sundararajan, 2004
<doi:10.1016/j.jclinepi.2004.03.012> and Ludvigsson, 2021
<doi:10.2147/CLEP.S282475>), together with different weighting algorithms for
both the Charlson and Elixhauser comorbidity scores.")
    (license license:gpl3+)))

(define-public r-communication
  (package
    (name "r-communication")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "communication" version))
       (sha256
        (base32 "08fkllwwcw2llpg5ivxhqghc88qfg1vdy0ciif3xazhhymb8wavb"))))
    (properties `((upstream-name . "communication")))
    (build-system r-build-system)
    (propagated-inputs (list r-wrassp
                             r-useful
                             r-tuner
                             r-signal
                             r-scales
                             r-reshape2
                             r-rcpparmadillo
                             r-rcpp
                             r-rcolorbrewer
                             r-purrr
                             r-plyr
                             r-magrittr
                             r-igraph
                             r-gtools
                             r-gtable
                             r-ggplot2
                             r-ggally
                             r-diagram
                             r-abind))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=communication")
    (synopsis
     "Feature Extraction and Model Estimation for Audio of Human Speech")
    (description
     "This package provides fast, easy feature extraction of human speech and model
estimation with hidden Markov models.  Flexible extraction of phonetic features
and their derivatives, with necessary preprocessing options like feature
standardization.  Communication can estimate supervised and unsupervised hidden
Markov models with these features, with cross validation and corrections for
auto-correlation in features.  Methods developed in Knox and Lucas (2021)
<doi:10.7910/DVN.8BTOHQ>.")
    (license license:gpl2+)))

(define-public r-commonsmath
  (package
    (name "r-commonsmath")
    (version "1.2.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "commonsMath" version))
       (sha256
        (base32 "0qbb7c5xqffq17i636qf9ppanxlmph9wym9bz6n4dhscfniw14q8"))))
    (properties `((upstream-name . "commonsMath")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/dbdahl/commonsMath")
    (synopsis "JAR Files of the Apache Commons Mathematics Library")
    (description
     "Java JAR files for the Apache Commons Mathematics Library for use by users and
other packages.")
    (license (list license:asl2.0
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-commonmean-copula
  (package
    (name "r-commonmean-copula")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CommonMean.Copula" version))
       (sha256
        (base32 "0c4la7sn3aynmj9qcz5d9gn9k3y5b38bjff0mfa5qccdb8rdkdhp"))))
    (properties `((upstream-name . "CommonMean.Copula")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma r-mvtnorm))
    (home-page "https://cran.r-project.org/package=CommonMean.Copula")
    (synopsis "Common Mean Vector under Copula Models")
    (description
     "Estimate bivariate common mean vector under copula models with known
correlation.  In the current version, available copulas are the Clayton, Gumbel,
Frank, Farlie-Gumbel-Morgenstern (FGM), and normal copulas.  See Shih et al.
(2019) <doi:10.1080/02331888.2019.1581782> and Shih et al. (2021) <under review>
for details under the FGM and general copulas, respectively.")
    (license license:gpl2)))

(define-public r-commonjavajars
  (package
    (name "r-commonjavajars")
    (version "1.1-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CommonJavaJars" version))
       (sha256
        (base32 "0yarxzryipv0s9gv28jfdh9igc6lqd71drpq29897gdb98vbz58c"))))
    (properties `((upstream-name . "CommonJavaJars")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (native-inputs (list r-knitr))
    (home-page "http://gsrmtp.r-forge.r-project.org/")
    (synopsis "Useful Libraries for Building a Java Based GUI under R")
    (description
     "Useful libraries for building a Java based GUI under R are provided.")
    (license license:gpl2)))

(define-public r-commondatamodel
  (package
    (name "r-commondatamodel")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CommonDataModel" version))
       (sha256
        (base32 "01q9z1pmji87pk0bcign3p9fj8f5zvx1b2whpxv8mkh01zw28wdm"))))
    (properties `((upstream-name . "CommonDataModel")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-sqlrender
                             r-rmarkdown
                             r-rjava
                             r-readr
                             r-dplyr
                             r-dbi
                             r-databaseconnector))
    (home-page "https://cran.r-project.org/package=CommonDataModel")
    (synopsis "OMOP CDM DDL and Documentation Generator")
    (description
     "Generates the scripts required to create an Observational Medical Outcomes
Partnership (OMOP) Common Data Model (CDM) database and associated documentation
for supported database platforms.  Leverages the @code{SqlRender} package to
convert the Data Definition Language (DDL) script written in parameterized
Structured Query Language (SQL) to the other supported dialects.")
    (license license:asl2.0)))

(define-public r-common
  (package
    (name "r-common")
    (version "1.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "common" version))
       (sha256
        (base32 "1zl34ikbasph6dchvl2dcbrs5wj6jxlyfg8gfnbq7dcmmbjg9l2h"))))
    (properties `((upstream-name . "common")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://common.r-sassy.org")
    (synopsis "Solutions for Common Problems in Base R")
    (description
     "This package contains functions for solving commonly encountered problems while
programming in R. This package is intended to provide a lightweight supplement
to Base R, and will be useful for almost any R user.")
    (license license:cc0)))

(define-public r-commkern
  (package
    (name "r-commkern")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CommKern" version))
       (sha256
        (base32 "1nr1mfc8nigwp8y6f4hiw7irbmyicdk5vjvlcndcywd1lzmlwi4b"))))
    (properties `((upstream-name . "CommKern")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2
                             r-rcolorbrewer
                             r-matrix
                             r-gridextra
                             r-ggplot2
                             r-ggnewscale))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/aljensen89/CommKern")
    (synopsis "Network-Based Communities and Kernel Machine Methods")
    (description
     "Analysis of network community objects with applications to neuroimaging data.
There are two main components to this package.  The first is the hierarchical
multimodal spinglass (HMS) algorithm, which is a novel community detection
algorithm specifically tailored to the unique issues within brain connectivity.
The other is a suite of semiparametric kernel machine methods that allow for
statistical inference to be performed to test for potential associations between
these community structures and an outcome of interest (binary or continuous).")
    (license license:gpl2+)))

(define-public r-commecol
  (package
    (name "r-commecol")
    (version "1.8.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CommEcol" version))
       (sha256
        (base32 "11pzb6m4ywkdrpckqahq1fddhgb9z6148vhaawyawyi7n3p7sggp"))))
    (properties `((upstream-name . "CommEcol")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-rncl
                             r-picante
                             r-gmp
                             r-betapart
                             r-ape
                             r-adespatial))
    (home-page "https://cran.r-project.org/package=CommEcol")
    (synopsis "Community Ecology Analyses")
    (description
     "Autosimilarity curves, standardization of spatial extent, dissimilarity indexes
that overweight rare species, phylogenetic and functional (pairwise and
multisample) dissimilarity indexes and nestedness for phylogenetic, functional
and other diversity metrics.  The methods for phylogenetic and functional
nestedness is described in Melo, Cianciaruso and Almeida-Neto (2014)
<doi:10.1111/2041-210X.12185>.  This should be a complement to available
packages, particularly vegan'.")
    (license license:gpl2)))

(define-public r-commafree
  (package
    (name "r-commafree")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "commafree" version))
       (sha256
        (base32 "0slxxq4jw2abfvg725x1hd7jmrsdc6ckbgzjzin081ll29axrfxg"))))
    (properties `((upstream-name . "commafree")))
    (build-system r-build-system)
    (home-page "https://github.com/t-kalinowski/commafree")
    (synopsis "Call Functions Without Commas Between Arguments")
    (description
     "This package provides the \"comma-free call\" operator: %(%'.  Use it to call a
function without commas between the arguments.  Just replace the ( with %(% in a
function call, supply your arguments as standard R expressions enclosed by { }',
and be free of commas (for that call).")
    (license license:gpl3+)))

(define-public r-comma
  (package
    (name "r-comma")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "COMMA" version))
       (sha256
        (base32 "1yaac6kgx3912l8iac4ybhm9drs7hy5x4wxiyc4w35clkg6r76vc"))))
    (properties `((upstream-name . "COMMA")))
    (build-system r-build-system)
    (propagated-inputs (list r-turboem r-matrix))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=COMMA")
    (synopsis "Correcting Misclassified Mediation Analysis")
    (description
     "Use three methods to estimate parameters from a mediation analysis with a binary
misclassified mediator.  These methods correct for the problem of \"label
switching\" using Youden's J criteria.  A detailed description of the analysis
methods is available in Webb and Wells (2024), \"Effect estimation in the
presence of a misclassified binary mediator\"
<doi:10.48550/@code{arXiv.2407.06970>}.")
    (license license:expat)))

(define-public r-comix
  (package
    (name "r-comix")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "COMIX" version))
       (sha256
        (base32 "0dhc3zb8jkfq8b9vj8m2a9jbd9fc7xxvhz16l8xhz9v5iffgk6hh"))))
    (properties `((upstream-name . "COMIX")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-rlang
                             r-rcppnumerical
                             r-rcppeigen
                             r-rcpparmadillo
                             r-rcpp
                             r-ggplot2
                             r-dplyr
                             r-coda))
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=COMIX")
    (synopsis "Coarsened Mixtures of Hierarchical Skew Kernels")
    (description
     "Bayesian fit of a Dirichlet Process Mixture with hierarchical multivariate skew
normal kernels and coarsened posteriors.  For more information, see Gorsky, Chan
and Ma (2020) <@code{arXiv:2001.06451>}.")
    (license license:cc0)))

(define-public r-comire
  (package
    (name "r-comire")
    (version "0.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoMiRe" version))
       (sha256
        (base32 "0wq1li1snn4c01vw1zqv6s9sqjrmiw04pkkmx2zdy5wg6bzfz363"))))
    (properties `((upstream-name . "CoMiRe")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncnorm
                             r-splines2
                             r-rlang
                             r-rcpparmadillo
                             r-rcpp
                             r-mvtnorm
                             r-kernsmooth
                             r-gtools
                             r-ggplot2))
    (home-page "https://cran.r-project.org/package=CoMiRe")
    (synopsis "Convex Mixture Regression")
    (description
     "Posterior inference under the convex mixture regression (@code{CoMiRe}) models
introduced by Canale, Durante, and Dunson (2018) <doi:10.1111/biom.12917>.")
    (license license:gpl2)))

(define-public r-comics
  (package
    (name "r-comics")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ComICS" version))
       (sha256
        (base32 "0brsb7y1bg23sdpxs4j1y3xdgr1q7iinxnnp17rravw72l991xqa"))))
    (properties `((upstream-name . "ComICS")))
    (build-system r-build-system)
    (propagated-inputs (list r-glmnet))
    (home-page "http://dcq.tau.ac.il/")
    (synopsis "Computational Methods for Immune Cell-Type Subsets")
    (description
     "Provided are Computational methods for Immune Cell-type Subsets, including:(1)
DCQ (Digital Cell Quantifier) to infer global dynamic changes in immune cell
quantities within a complex tissue; and (2) @code{VoCAL} (Variation of Cell-type
Abundance Loci) a deconvolution-based method that utilizes transcriptome data to
infer the quantities of immune-cell types, and then uses these quantitative
traits to uncover the underlying DNA loci.")
    (license license:gpl2)))

(define-public r-comfuncs
  (package
    (name "r-comfuncs")
    (version "0.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comFuncs" version))
       (sha256
        (base32 "0li89pgvvlzv9gkzkvnpwxl04fx5djsg0w80bk2mj45h5ark5s37"))))
    (properties `((upstream-name . "comFuncs")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny))
    (home-page "https://github.com/TuCai/comFuncs")
    (synopsis "Commonly Used Functions for R Shiny Applications")
    (description
     "This package provides a set of common functions to be used for displaying
messages, checking variables, finding absolute paths, starting applications,
etc.  More functions will be added later.")
    (license license:expat)))

(define-public r-comf
  (package
    (name "r-comf")
    (version "0.1.12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comf" version))
       (sha256
        (base32 "1239lj29y2hiqgsf507i535d8adgsmzh2a1b1h896cxlbvpjn3ls"))))
    (properties `((upstream-name . "comf")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape r-plyr r-jsonlite))
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=comf")
    (synopsis "Models and Equations for Human Comfort Research")
    (description
     "Calculation of various common and less common comfort indices such as predicted
mean vote or the two node model.  Converts physical variables such as relative
to absolute humidity and evaluates the performance of comfort indices.")
    (license license:gpl2)))

(define-public r-comets
  (package
    (name "r-comets")
    (version "0.0-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comets" version))
       (sha256
        (base32 "1rkw49b0pxn0vg3ahrk3i2xd61v2px00b8jbws8s40r19ak27a19"))))
    (properties `((upstream-name . "comets")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-ranger r-glmnet r-formula r-coin))
    (home-page "https://github.com/LucasKook/comets")
    (synopsis "Covariance Measure Tests for Conditional Independence")
    (description
     "Covariance measure tests for conditional independence testing against
conditional covariance and nonlinear conditional mean alternatives.  Contains
versions of the generalised covariance measure test (Shah and Peters, 2020,
<doi:10.1214/19-aos1857>) and projected covariance measure test (Lundborg et
al., 2023, <doi:10.48550/@code{arXiv.2211.02039>}).  Applications can be found
in Kook and Lundborg (2024, <doi:10.1093/bib/bbae475>).")
    (license license:gpl3)))

(define-public r-cometr
  (package
    (name "r-cometr")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cometr" version))
       (sha256
        (base32 "022fz7b94xl56ss1773n3g9zwfjm8mqfqds68ngvfq5498npd9z5"))))
    (properties `((upstream-name . "cometr")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-r6
                             r-r-utils
                             r-jsonlite
                             r-httr
                             r-digest
                             r-callr))
    (home-page "https://github.com/comet-ml/cometr")
    (synopsis "'Comet' API for R")
    (description
     "This package provides a convenient R wrapper to the Comet API, which is a cloud
platform allowing you to track, compare, explain and optimize machine learning
experiments and models.  Experiments can be viewed on the Comet online dashboard
at <https://www.comet.com>.")
    (license license:expat)))

(define-public r-cometexacttest
  (package
    (name "r-cometexacttest")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cometExactTest" version))
       (sha256
        (base32 "0ar9axm9cd1wd937xcmsmd7xqilnfyab8gsrpkiqpc3fjh86qyrp"))))
    (properties `((upstream-name . "cometExactTest")))
    (build-system r-build-system)
    (propagated-inputs (list r-dplyr))
    (home-page "http://compbio.cs.brown.edu/projects/comet")
    (synopsis
     "Exact Test from the Combinations of Mutually Exclusive Alterations (CoMEt) Algorithm")
    (description
     "An algorithm for identifying combinations of mutually exclusive alterations in
cancer genomes. @code{CoMEt} represents the mutations in a set M of k genes with
a 2^k dimensional contingency table, and then computes the tail probability of
observing T(M) exclusive alterations using an exact statistical test.")
    (license license:expat)))

(define-public r-comclim
  (package
    (name "r-comclim")
    (version "0.9.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comclim" version))
       (sha256
        (base32 "0dw3s3xbkfn38m7xg49cbn70qj0j4hsxj6m72p1diirrcy2sn07c"))))
    (properties `((upstream-name . "comclim")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=comclim")
    (synopsis "Community Climate Statistics")
    (description
     "Computes community climate statistics for volume and mismatch using species
climate niches either unscaled or scaled relative to a regional species pool.
These statistics can be used to describe biogeographic patterns and infer
community assembly processes.  Includes a vignette outlining usage.")
    (license license:gpl3)))

(define-public r-combo
  (package
    (name "r-combo")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "COMBO" version))
       (sha256
        (base32 "0073cwbggmqgm13nmg8b6lq3gb5qid73nhh0jb0ldmabwn1bw3hk"))))
    (properties `((upstream-name . "COMBO")))
    (build-system r-build-system)
    (inputs (list jags))
    (propagated-inputs (list r-turboem
                             r-tidyr
                             r-samba
                             r-rjags
                             r-matrix
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=COMBO")
    (synopsis
     "Correcting Misclassified Binary Outcomes in Association Studies")
    (description
     "Use frequentist and Bayesian methods to estimate parameters from a binary
outcome misclassification model.  These methods correct for the problem of
\"label switching\" by assuming that the sum of outcome sensitivity and
specificity is at least 1.  A description of the analysis methods is available
in Hochstedler and Wells (2023) <doi:10.48550/@code{arXiv.2303.10215>}.")
    (license license:expat)))

(define-public r-combiter
  (package
    (name "r-combiter")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "combiter" version))
       (sha256
        (base32 "11pcvrpbvkzkjwks2z6ww7s9d5fkh8zl0jw52a5ya3y1wkqcs3n6"))))
    (properties `((upstream-name . "combiter")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-itertools r-iterators))
    (home-page "https://github.com/kota7/combiter")
    (synopsis "Combinatorics Iterators")
    (description
     "This package provides iterators for combinations, permutations, subsets, and
Cartesian product, which allow one to go through all elements without creating a
huge set of all possible values.")
    (license license:expat)))

(define-public r-combiroc
  (package
    (name "r-combiroc")
    (version "0.3.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "combiroc" version))
       (sha256
        (base32 "00wbhsw14v05gy0yhr4b45n53n9sd9m6hyw3wiyv6rpwn1k0jybi"))))
    (properties `((upstream-name . "combiroc")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-proc
                             r-moments
                             r-gtools
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://doi.org/10.1101/2022.01.17.476603")
    (synopsis
     "Selection and Ranking of Omics Biomarkers Combinations Made Easy")
    (description
     "This package provides functions and a workflow to easily and powerfully
calculating specificity, sensitivity and ROC curves of biomarkers combinations.
Allows to rank and select multi-markers signatures as well as to find the best
performing sub-signatures, now also from single-cell RNA-seq datasets.  The
method used was first published as a Shiny app and described in Mazzara et al.
(2017) <doi:10.1038/srep45477> and further described in Bombaci & Rossi (2019)
<doi:10.1007/978-1-4939-9164-8_16>, and widely expanded as a package as
presented in the @code{bioRxiv} pre print Ferrari et al.
<doi:10.1101/2022.01.17.476603>.")
    (license license:expat)))

(define-public r-combins
  (package
    (name "r-combins")
    (version "1.1-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CombinS" version))
       (sha256
        (base32 "06g41zbjl54cbhhs8q7l4bbvszclvbxn3m2dqg800d6ghs9vgl6v"))))
    (properties `((upstream-name . "CombinS")))
    (build-system r-build-system)
    (home-page "'www.sites.google.com/site/mohamedlaibwebpage'")
    (synopsis "Construction Methods of some Series of PBIB Designs")
    (description
     "Series of partially balanced incomplete block designs (PBIB) based on the
combinatory method (S) introduced in (Imane Rezgui et al, 2014)
<doi:10.3844/jmssp.2014.45.48>; and it gives their associated U-type design.")
    (license license:gpl3)))

(define-public r-combinit
  (package
    (name "r-combinit")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "combinIT" version))
       (sha256
        (base32 "1l2ypnrm2qi1z10c2qyyaqqcjgk3mgsh80b3j9zrjwq9zdakrhi5"))))
    (properties `((upstream-name . "combinIT")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-mvtnorm))
    (home-page "https://github.com/haghbinh/combinIT")
    (synopsis "Combined Interaction Test for Unreplicated Two-Way Tables")
    (description
     "There are several non-functional-form-based interaction tests for testing
interaction in unreplicated two-way layouts.  However, no single test can detect
all patterns of possible interaction and the tests are sensitive to a particular
pattern of interaction.  This package combines six non-functional-form-based
interaction tests for testing additivity.  These six tests were proposed by Boik
(1993) <doi:10.1080/02664769300000004>, Piepho (1994), Kharrati-Kopaei and
Sadooghi-Alvandi (2007) <doi:10.1080/03610920701386851>, Franck et al. (2013)
<doi:10.1016/j.csda.2013.05.002>, Malik et al. (2016)
<doi:10.1080/03610918.2013.870196> and Kharrati-Kopaei and Miller (2016)
<doi:10.1080/00949655.2015.1057821>.  The p-values of these six tests are
combined by Bonferroni, Sidak, Jacobi polynomial expansion, and the Gaussian
copula methods to provide researchers with a testing approach which leverages
many existing methods to detect disparate forms of non-additivity.  This package
is based on the following published paper: Shenavari and Kharrati-Kopaei (2018)
\"A Method for Testing Additivity in Unreplicated Two-Way Layouts Based on
Combining Multiple Interaction Tests\".  In addition, several sentences in help
files or descriptions were copied from that paper.")
    (license license:gpl2+)))

(define-public r-combineportfolio
  (package
    (name "r-combineportfolio")
    (version "0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CombinePortfolio" version))
       (sha256
        (base32 "0kj96i2ahq7ax1nx66jac8bbdiiyviwnzr4cr4gn0b8y580rdcwi"))))
    (properties `((upstream-name . "CombinePortfolio")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CombinePortfolio")
    (synopsis
     "Estimation of Optimal Portfolio Weights by Combining Simple Portfolio Strategies")
    (description
     "Estimation of optimal portfolio weights as combination of simple portfolio
strategies, like the tangency, global minimum variance (GMV) or naive (1/N)
portfolio.  It is based on a utility maximizing 8-fund rule.  Popular special
cases like the Kan-Zhou(2007) 2-fund and 3-fund rule or the Tu-Zhou(2011)
estimator are nested.")
    (license license:gpl2+)))

(define-public r-combinedevents
  (package
    (name "r-combinedevents")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "combinedevents" version))
       (sha256
        (base32 "0fwsxn2ziapax1wy9k57n76z3nxqb22vfbp5r3y6xg3aparxdxpz"))))
    (properties `((upstream-name . "combinedevents")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-rlang r-magrittr r-lubridate))
    (home-page "https://katie-frank.github.io/combinedevents/")
    (synopsis "Calculate Scores and Marks for Track and Field Combined Events")
    (description
     "Includes functions to calculate scores and marks for track and field combined
events competitions.  The functions are based on the scoring tables for combined
events set forth by the International Association of Athletics Federation
(2001).")
    (license license:gpl3)))

(define-public r-combinatorics
  (package
    (name "r-combinatorics")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "combinatorics" version))
       (sha256
        (base32 "02v0fz6qw08v4krnaj6ph76d6n2al12c48vl81ajj5hvlnjwldhg"))))
    (properties `((upstream-name . "combinatorics")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=combinatorics")
    (synopsis "Introduction to Some Combinatorial Relations")
    (description
     "Determining the value of Stirling numbers of 1st kind and 2nd kind,references:
BÃ³na,MiklÃ³s(2017,ISBN 9789813148840).")
    (license license:gpl3)))

(define-public r-combinationpvalues
  (package
    (name "r-combinationpvalues")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "combinationpvalues" version))
       (sha256
        (base32 "0n5dhgss8mrxshfixpc10g1p7l06hcn3fbk7l9sp92ap64kalz6c"))))
    (properties `((upstream-name . "combinationpvalues")))
    (build-system r-build-system)
    (propagated-inputs (list r-spatstat-utils r-dplyr r-chi))
    (home-page "https://github.com/StatsGirl/Master2021/tree/main/R")
    (synopsis "Combination of Independent P-Values")
    (description
     "This package provides access to six fundamental statistics that can be used for
the purpose of combination p-values.  All methods used can referenced here:
Heard & Rubin-Delanchy (2017) <@code{arXiv:1707.06897>}.")
    (license license:expat)))

(define-public r-combat-enigma
  (package
    (name "r-combat-enigma")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "combat.enigma" version))
       (sha256
        (base32 "1skrjssp8gfqfi3pjb1aawqwdh066fiz0ssal43jlx1wbkmk65m8"))))
    (properties `((upstream-name . "combat.enigma")))
    (build-system r-build-system)
    (propagated-inputs (list r-nlme r-matrix r-caret r-car))
    (home-page "https://cran.r-project.org/package=combat.enigma")
    (synopsis
     "Fit and Apply ComBat, LMM, or Prescaling Harmonization for ENIGMA and Other Multisite MRI Data")
    (description
     "Fit and apply @code{ComBat}, linear mixed-effects models (LMM), or prescaling to
harmonize magnetic resonance imaging (MRI) data from different sites.  Briefly,
these methods remove differences between sites due to using different scanning
devices, and LMM additionally tests linear hypotheses.  As detailed in the
manual, the original @code{ComBat} function was first modified for the
harmonization of MRI data (Fortin et al. (2017)
<doi:10.1016/j.neuroimage.2017.11.024>) and then modified again to create
separate functions for fitting and applying the harmonization and allow missing
values and constant rows for its use within the Enhancing Neuro Imaging Genetics
through Meta-Analysis (ENIGMA) Consortium (Radua et al. (2020)
<doi:10.1016/j.neuroimage.2017.11.024>); this package includes the latter
version.  LMM calls \"lme\" massively considering specific brain imaging details.
Finally, prescaling is a good option for @code{fMRI}, where different devices
can have varying units of measurement.")
    (license (license:fsdg-compatible "Artistic License 2.0"))))

(define-public r-combat
  (package
    (name "r-combat")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "COMBAT" version))
       (sha256
        (base32 "0m700pl33frdpc9y16y4zyh1ixpardh0r5kmz8a78jrh1acn30id"))))
    (properties `((upstream-name . "COMBAT")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-corpcor))
    (home-page "https://cran.r-project.org/package=COMBAT")
    (synopsis "Combined Association Test for Genes using Summary Statistics")
    (description
     "Genome-wide association studies (GWAS) have been widely used for identifying
common variants associated with complex diseases.  Due to the small effect sizes
of common variants, the power to detect individual risk variants is generally
low.  Complementary to SNP-level analysis, a variety of gene-based association
tests have been proposed.  However, the power of existing gene-based tests is
often dependent on the underlying genetic models, and it is not known a priori
which test is optimal.  Here we proposed COMBined Association Test (COMBAT) to
incorporate strengths from multiple existing gene-based tests, including VEGAS,
GATES and @code{simpleM}.  Compared to individual tests, COMBAT shows higher
overall performance and robustness across a wide range of genetic models.  The
algorithm behind this method is described in Wang et al (2017)
<doi:10.1534/genetics.117.300257>.")
    (license license:gpl2)))

(define-public r-comato
  (package
    (name "r-comato")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comato" version))
       (sha256
        (base32 "0lidwr5vw10655p7q0iqzq3phq5y1i86w3bjdv87cwx3m6333bz6"))))
    (properties `((upstream-name . "comato")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml
                             r-matrix
                             r-lattice
                             r-igraph
                             r-gdata
                             r-clustersim
                             r-cluster))
    (home-page "https://cran.r-project.org/package=comato")
    (synopsis "Analysis of Concept Maps and Concept Landscapes")
    (description
     "This package provides methods for the import/export and automated analysis of
concept maps and concept landscapes (sets of concept maps).")
    (license license:gpl3)))

(define-public r-comat
  (package
    (name "r-comat")
    (version "0.9.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "comat" version))
       (sha256
        (base32 "05kvm4wv5m1mk7lkh69vbzb26xqjxdyvx87r9vx2hmz5wv0vhp7y"))))
    (properties `((upstream-name . "comat")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://jakubnowosad.com/comat/")
    (synopsis "Creates Co-Occurrence Matrices of Spatial Data")
    (description
     "Builds co-occurrence matrices based on spatial raster data.  It includes
creation of weighted co-occurrence matrices (wecoma) and integrated
co-occurrence matrices (incoma; Vadivel et al. (2007)
<doi:10.1016/j.patrec.2007.01.004>).")
    (license license:expat)))

(define-public r-colt
  (package
    (name "r-colt")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colt" version))
       (sha256
        (base32 "028jqvgr14ig8jxp8h2lrf7mainzppgqh6v1479qfv4l9is3bnwy"))))
    (properties `((upstream-name . "colt")))
    (build-system r-build-system)
    (propagated-inputs (list r-crayon))
    (home-page "https://github.com/s-fleck/colt")
    (synopsis "Command-Line Color Themes")
    (description
     "This package provides a collection of command-line color styles based on the
crayon package.  Colt styles are defined in themes that can easily be switched,
to ensure command line output looks nice on dark as well as light consoles.")
    (license license:expat)))

(define-public r-cols4all
  (package
    (name "r-cols4all")
    (version "0.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cols4all" version))
       (sha256
        (base32 "19r7b9ndq80sbzfnksh6869ffbwx5jvlqvccwrijczbls1xhhnlr"))))
    (properties `((upstream-name . "cols4all")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringdist r-spacesxyz r-png r-colorspace
                             r-abind))
    (home-page "https://mtennekes.github.io/cols4all/")
    (synopsis "Colors for all")
    (description
     "Color palettes for all people, including those with color vision deficiency.
Popular color palette series have been organized by type and have been scored on
several properties such as color-blind-friendliness and fairness (i.e.  do
colors stand out equally?).  Own palettes can also be loaded and analysed.
Besides the common palette types (categorical, sequential, and diverging) it
also includes cyclic and bivariate color palettes.  Furthermore, a color for
missing values is assigned to each palette.")
    (license license:gpl3)))

(define-public r-cols
  (package
    (name "r-cols")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cols" version))
       (sha256
        (base32 "00r3dniz5n4mx8cwsyixs1v88pdjx0a460zcq420z5wrav23jbdl"))))
    (properties `((upstream-name . "cols")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfast2 r-rfast r-quadprog))
    (home-page "https://cran.r-project.org/package=cols")
    (synopsis "Constrained Ordinary Least Squares")
    (description
     "Constrained ordinary least squares is performed.  One constraint is that all
beta coefficients (including the constant) cannot be negative.  They can be
either 0 or strictly positive.  Another constraint is that the sum of the beta
coefficients equals a constant.  References: Hansen, B. E. (2022).
Econometrics, Princeton University Press. <ISBN:9780691235899>.")
    (license license:gpl2+)))

(define-public r-colp
  (package
    (name "r-colp")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "COLP" version))
       (sha256
        (base32 "0259s058rn7fyprma5frx7sdjv4qk9hxijpi9xh7qyz5jzzsi660"))))
    (properties `((upstream-name . "COLP")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-combinat))
    (home-page "https://github.com/nySTAT/COLP")
    (synopsis "Causal Discovery for Categorical Data with Label Permutation")
    (description
     "Discover causality for bivariate categorical data.  This package aims to enable
users to discover causality for bivariate observational categorical data.  See
Ni, Y. (2022) <@code{arXiv:2209.08579>} \"Bivariate Causal Discovery for
Categorical Data via Classification with Optimal Label Permutation.  Advances in
Neural Information Processing Systems 35 (in press)\".")
    (license license:expat)))

(define-public r-colourvision
  (package
    (name "r-colourvision")
    (version "2.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colourvision" version))
       (sha256
        (base32 "1abrp6x9wdl5bdbysgziznzmiaik8v4n76b4bgnlk13mwbhfn47h"))))
    (properties `((upstream-name . "colourvision")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=colourvision")
    (synopsis "Colour Vision Models")
    (description
     "Colour vision models, colour spaces and colour thresholds.  Provides flexibility
to build user-defined colour vision models for n number of photoreceptor types.
Also includes Vorobyev & Osorio (1998) Receptor Noise Limited models
<doi:10.1098/rspb.1998.0302>, Chittka (1992) colour hexagon
<doi:10.1007/BF00199331>, and Endler & Mielke (2005) model
<doi:10.1111/j.1095-8312.2005.00540.x>.  Models have been extended to accept any
number of photoreceptor types.")
    (license license:gpl2)))

(define-public r-colourvalues
  (package
    (name "r-colourvalues")
    (version "0.3.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colourvalues" version))
       (sha256
        (base32 "0prrvkj3xi09fbjz9sd12nvqmsm47fkpw9v9kxsrx3wgm1vi49in"))))
    (properties `((upstream-name . "colourvalues")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-bh))
    (home-page "https://symbolixau.github.io/colourvalues/")
    (synopsis "Assigns Colours to Values")
    (description
     "Maps one of the viridis colour palettes, or a user-specified palette to values.
Viridis colour maps are created by StÃ©fan van der Walt and Nathaniel Smith, and
were set as the default palette for the Python Matplotlib library
<https://matplotlib.org/>.  Other palettes available in this library have been
derived from R@code{ColorBrewer}
<https://CRAN.R-project.org/package=R@code{ColorBrewer>} and colorspace
<https://CRAN.R-project.org/package=colorspace> packages.")
    (license license:gpl3)))

(define-public r-colourlovers
  (package
    (name "r-colourlovers")
    (version "0.3.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colourlovers" version))
       (sha256
        (base32 "13fqn6hbqjk3d8krpqb3hmsq06qrbks8a9ia5441hd6m7m8wjjkc"))))
    (properties `((upstream-name . "colourlovers")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml r-png r-jsonlite r-httr))
    (home-page "https://github.com/andrewheiss/colourlovers")
    (synopsis "R Client for the COLOURlovers API")
    (description
     "This package provides access to the COLOURlovers <https://www.colourlovers.com/>
API, which offers color inspiration and color palettes.")
    (license license:gpl2)))

(define-public r-colour
  (package
    (name "r-colour")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colouR" version))
       (sha256
        (base32 "0dchwa6nqikdm7chzavimc5cayhrbrl0hzr8xg8y15nvb8b2vqj6"))))
    (properties `((upstream-name . "colouR")))
    (build-system r-build-system)
    (propagated-inputs (list r-png
                             r-pixmap
                             r-jpeg
                             r-httr
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=colouR")
    (synopsis "Create Colour Palettes from Images")
    (description
     "Can take in images in either .jpg, .jpeg, or .png format and creates a colour
palette of the most frequent colours used in the image.  Also provides some
custom colour palettes.")
    (license license:gpl2+)))

(define-public r-colorspec
  (package
    (name "r-colorspec")
    (version "1.5-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colorSpec" version))
       (sha256
        (base32 "0vqh6nnp6myv46x520hisfz4ggfyhki88d1bggf9kq7p0723w4lk"))))
    (properties `((upstream-name . "colorSpec")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=colorSpec")
    (synopsis "Color Calculations with Emphasis on Spectral Data")
    (description
     "Calculate with spectral properties of light sources, materials, cameras, eyes,
and scanners.  Build complex systems from simpler parts using a spectral product
algebra.  For light sources, compute CCT, CRI, and SSI. For object colors,
compute optimal colors and Logvinenko coordinates.  Work with the standard CIE
illuminants and color matching functions, and read spectra from text files,
including CGATS files.  Estimate a spectrum from its response.  A user guide and
9 vignettes are included.")
    (license license:gpl3+)))

(define-public r-colorsgen
  (package
    (name "r-colorsgen")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colorsGen" version))
       (sha256
        (base32 "0w4qkl4fw7pjfcd2z3nhpkxh8kv3bbq19bi2cg0ivfr83kxa44fj"))))
    (properties `((upstream-name . "colorsGen")))
    (build-system r-build-system)
    (propagated-inputs (list r-colorspace))
    (home-page "https://github.com/stla/colorsGen")
    (synopsis "Generation of Random Colors")
    (description
     "Generation of random colors, possibly with a given hue or a given luminosity.
This is a port of the @code{JavaScript} library @code{randomColor}
<https://randomcolor.lllllllllllllllll.com/>.")
    (license license:cc0)))

(define-public r-colorscience
  (package
    (name "r-colorscience")
    (version "1.0.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colorscience" version))
       (sha256
        (base32 "1m96av3dax3nh7ckd83hrzklxccq878gn808jmkwqzkvnx3y5i13"))))
    (properties `((upstream-name . "colorscience")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp r-pracma r-hmisc))
    (home-page "https://cran.r-project.org/package=colorscience")
    (synopsis "Color Science Methods and Data")
    (description
     "This package provides methods and data for color science - color conversions by
observer, illuminant, and gamma.  Color matching functions and chromaticity
diagrams.  Color indices, color differences, and spectral data
conversion/analysis.  This package is deprecated and will someday be removed;
for reasons and details please see the README file.")
    (license license:gpl3+)))

(define-public r-colors3d
  (package
    (name "r-colors3d")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colors3d" version))
       (sha256
        (base32 "0d78y5v329fhaqhw0a0cgkpiajmqb91vl9809fiwnvl2b4x3j51r"))))
    (properties `((upstream-name . "colors3d")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales r-plyr r-fnn r-combinat))
    (home-page "https://github.com/matthewkling/colors3d")
    (synopsis "Generate 2D and 3D Color Palettes")
    (description
     "Generate multivariate color palettes to represent two-dimensional or
three-dimensional data in graphics (in contrast to standard color palettes that
represent just one variable).  You tell colors3d how to map color space onto
your data, and it gives you a color for each data point.  You can then use these
colors to make plots in base R', ggplot2', or other graphics frameworks.")
    (license license:expat)))

(define-public r-colorrepel
  (package
    (name "r-colorrepel")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colorrepel" version))
       (sha256
        (base32 "0p5zfcmyrs567ddn7jilzbvs2k1qr213ims5m0zx1swylxpvjda7"))))
    (properties `((upstream-name . "colorrepel")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-purrr
                             r-png
                             r-plotly
                             r-matrixstats
                             r-matrix
                             r-knitr
                             r-gtools
                             r-ggrepel
                             r-ggplot2
                             r-ggalt
                             r-dqrng
                             r-dplyr
                             r-distances))
    (home-page "https://github.com/raysinensis/color_repel")
    (synopsis
     "Repel Visually Similar Colors for Colorblind Users in Various Plots")
    (description
     "Iterate and repel visually similar colors away in various ggplot2 plots.  When
many groups are plotted at the same time on multiple axes, for instance stacked
bars or scatter plots, effectively ordering colors becomes difficult.  This tool
iterates through color combinations to find the best solution to maximize visual
distinctness of nearby groups, so plots are more friendly toward colorblind
users.  This is achieved by two distance measurements, distance between groups
within the plot, and CIELAB color space distances between colors as described in
Carter et al., (2018) <doi:10.25039/TR.015.2018>.")
    (license license:expat)))

(define-public r-colorramp2
  (package
    (name "r-colorramp2")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colorRamp2" version))
       (sha256
        (base32 "0b4m30s9rkhb37lf2zr6zgnfvxdj3nhm0jp5b42fxgy2y5qd5q02"))))
    (properties `((upstream-name . "colorRamp2")))
    (build-system r-build-system)
    (propagated-inputs (list r-colorspace))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jokergoo/colorRamp2")
    (synopsis "Generate Color Mapping Functions")
    (description
     "This package provides a color mapping is generated according to the break values
and corresponding colors.  Other colors are generated by interpolating in a
certain color space.  The functions were part of the circlize package
<https://CRAN.R-project.org/package=circlize>.")
    (license license:expat)))

(define-public r-colorr
  (package
    (name "r-colorr")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colorr" version))
       (sha256
        (base32 "1wwrgb9fc9gzxxwxrdrkwwrmhqqllv29wr4q8y1shj9d3nzcpwmh"))))
    (properties `((upstream-name . "colorr")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=colorr")
    (synopsis "Color Palettes for EPL, MLB, NBA, NHL, and NFL Teams")
    (description "Color palettes for EPL, MLB, NBA, NHL, and NFL teams.")
    (license license:expat)))

(define-public r-colorplane
  (package
    (name "r-colorplane")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colorplane" version))
       (sha256
        (base32 "00jicdyrw6pl2x83qf9x22is21rmi011zziy3hvjw2vqvclxb38i"))))
    (properties `((upstream-name . "colorplane")))
    (build-system r-build-system)
    (propagated-inputs (list r-assertthat))
    (home-page "https://cran.r-project.org/package=colorplane")
    (synopsis
     "Basic S4 Classes and Methods for Mapping Between Numeric Values and Colors")
    (description
     "This package provides a simple set of classes and methods for mapping between
scalar intensity values and colors.  There is also support for layering maps on
top of one another using alpha composition.")
    (license license:expat)))

(define-public r-colorpatch
  (package
    (name "r-colorpatch")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colorpatch" version))
       (sha256
        (base32 "18p9hgccp37pbdf437xffkv6z500896v08fsw2jm8zcl9ladygaf"))))
    (properties `((upstream-name . "colorpatch")))
    (build-system r-build-system)
    (propagated-inputs (list r-tsp r-gridextra r-ggplot2 r-colorspace))
    (native-inputs (list r-knitr))
    (home-page "http://sysbio.uni-ulm.de/?Software:colorpatch")
    (synopsis "Optimized Rendering of Fold Changes and Confidence Values")
    (description
     "Shows color patches for encoding fold changes (e.g. log ratios) together with
confidence values within a single diagram.  This is especially useful for
rendering gene expression data as well as other types of differential
experiments.  In addition to different rendering methods (ggplot extensions)
functionality for perceptually optimizing color palettes are provided.
Furthermore the package provides extension methods of the colorspace color-class
in order to simplify the work with palettes (a.o.  length, as.list, and append
are supported).")
    (license license:artistic2.0)))

(define-public r-colornamer
  (package
    (name "r-colornamer")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ColorNameR" version))
       (sha256
        (base32 "0gqyph3f6mhwg6zwc5bgfglpmg152a4kd2wrmp9jn18wvg8wd03g"))))
    (properties `((upstream-name . "ColorNameR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-purrr r-magrittr r-dplyr))
    (home-page "https://github.com/msanchez-beeckman/ColorNameR")
    (synopsis "Give Colors a Name")
    (description
     "This package provides a tool for transforming coordinates in a color space to
common color names using data from the Royal Horticultural Society and the
International Union for the Protection of New Varieties of Plants.")
    (license license:expat)))

(define-public r-colormap
  (package
    (name "r-colormap")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colormap" version))
       (sha256
        (base32 "0032ji9n8pivl70jppq989fgg781wil8zag7pfl1hs9xrpin8asy"))))
    (properties `((upstream-name . "colormap")))
    (build-system r-build-system)
    (propagated-inputs (list r-v8 r-stringr r-ggplot2))
    (home-page "https://github.com/bhaskarvk/colormap")
    (synopsis "Color Palettes using Colormaps Node Module")
    (description
     "Allows to generate colors from palettes defined in the colormap module of
Node.js'. (see <https://github.com/bpostlethwaite/colormap> for more
information).  In total it provides 44 distinct palettes made from sequential
and/or diverging colors.  In addition to the pre defined palettes you can also
specify your own set of colors.  There are also scale functions that can be used
with ggplot2'.")
    (license license:expat)))

(define-public r-colorizer
  (package
    (name "r-colorizer")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colorizer" version))
       (sha256
        (base32 "1c0rgjxzjwkaxdnkmcgn9f0mmcxna724cq60q79hzjindbl4r6bk"))))
    (properties `((upstream-name . "colorizer")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-purrr
                             r-magrittr
                             r-magick
                             r-httr
                             r-dplyr))
    (home-page "https://github.com/zumbov2/colorizer")
    (synopsis
     "Colorize Old Images Using the 'DeOldify' Image Colorization API")
    (description
     "Call the @code{DeOldify} <https://github.com/jantic/@code{DeOldify>} image
colorization API on
@code{DeepAI'<https://deepai.org/machine-learning-model/colorizer>} to colorize
black and white images.")
    (license license:expat)))

(define-public r-colorist
  (package
    (name "r-colorist")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colorist" version))
       (sha256
        (base32 "0sv3gg1cqgvadb16f5v7fc002cq0sdk6g1409adymxlxrn2bn6rd"))))
    (properties `((upstream-name . "colorist")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-scales
                             r-rlang
                             r-raster
                             r-magrittr
                             r-ggplot2
                             r-colorspace))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mstrimas/colorist")
    (synopsis "Coloring Wildlife Distributions in Space-Time")
    (description
     "Color and visualize wildlife distributions in space-time using raster data.  In
addition to enabling display of sequential change in distributions through the
use of small multiples, colorist provides functions for extracting several
features of interest from a sequence of distributions and for visualizing those
features using HCL (hue-chroma-luminance) color palettes.  Resulting maps allow
for \"fair\" visual comparison of intensity values (e.g., occurrence, abundance,
or density) across space and time and can be used to address questions about
where, when, and how consistently a species, group, or individual is likely to
be found.")
    (license license:gpl3)))

(define-public r-colorhcplot
  (package
    (name "r-colorhcplot")
    (version "1.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colorhcplot" version))
       (sha256
        (base32 "009pyyb30kwshldd7v7zfy5rxys6i0dhlc5w8ail61acbg4rlrmz"))))
    (properties `((upstream-name . "colorhcplot")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=colorhcplot")
    (synopsis "Colorful Hierarchical Clustering Dendrograms")
    (description
     "Build dendrograms with sample groups highlighted by different colors.  Visualize
results of hierarchical clustering analyses as dendrograms whose leaves and
labels are colored according to sample grouping.  Assess whether data point
grouping aligns to naturally occurring clusters.")
    (license license:gpl2)))

(define-public r-colorfindr
  (package
    (name "r-colorfindr")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colorfindr" version))
       (sha256
        (base32 "175h476dzq1f2x25vdd268xj4ja4lv8fhfj9vld85waqi0sq515g"))))
    (properties `((upstream-name . "colorfindr")))
    (build-system r-build-system)
    (propagated-inputs (list r-treemap
                             r-tiff
                             r-tibble
                             r-stringr
                             r-rsvg
                             r-purrr
                             r-png
                             r-plotwidgets
                             r-plotly
                             r-pixmap
                             r-magrittr
                             r-jpeg
                             r-dplyr
                             r-bmp))
    (home-page "https://cran.r-project.org/package=colorfindr")
    (synopsis
     "Extract Colors from Windows BMP, JPEG, PNG, TIFF, and SVG Format Images")
    (description
     "Extracts colors from various image types, returns customized reports and plots
treemaps and 3D scatterplots of image compositions.  Color palettes can also be
created.")
    (license license:gpl2+)))

(define-public r-colorednoise
  (package
    (name "r-colorednoise")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colorednoise" version))
       (sha256
        (base32 "1wyqliwy64hxbhhij8m5f9s4ranjpqc3qzlkr9m37c9z70lgjril"))))
    (properties `((upstream-name . "colorednoise")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-purrr r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=colorednoise")
    (synopsis "Simulate Temporally Autocorrelated Populations")
    (description
     "Temporally autocorrelated populations are correlated in their vital rates
(growth, death, etc.) from year to year.  It is very common for populations,
whether they be bacteria, plants, or humans, to be temporally autocorrelated.
This poses a challenge for stochastic population modeling, because a temporally
correlated population will behave differently from an uncorrelated one.  This
package provides tools for simulating populations with white noise (no temporal
autocorrelation), red noise (positive temporal autocorrelation), and blue noise
(negative temporal autocorrelation).  The algebraic formulation for
autocorrelated noise comes from Ruokolainen et al. (2009)
<doi:10.1016/j.tree.2009.04.009>.  Models for unstructured populations and for
structured populations (matrix models) are available.")
    (license license:gpl3)))

(define-public r-colordistance
  (package
    (name "r-colordistance")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colordistance" version))
       (sha256
        (base32 "14j63anmf4j1lmcd7nyr9k7alhycdkrr5yiar262j8wha68f245n"))))
    (properties `((upstream-name . "colordistance")))
    (build-system r-build-system)
    (propagated-inputs (list r-spatstat-geom
                             r-scatterplot3d
                             r-scales
                             r-qpdf
                             r-png
                             r-plotly
                             r-mgcv
                             r-magrittr
                             r-jpeg
                             r-gplots
                             r-emdist
                             r-clue
                             r-ape
                             r-abind))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=colordistance")
    (synopsis "Distance Metrics for Image Color Similarity")
    (description
     "Loads and displays images, selectively masks specified background colors, bins
pixels by color using either data-dependent or automatically generated color
bins, quantitatively measures color similarity among images using one of several
distance metrics for comparing pixel color clusters, and clusters images by
object color similarity.  Uses CIELAB, RGB, or HSV color spaces.  Originally
written for use with organism coloration (reef fish color diversity, butterfly
mimicry, etc), but easily applicable for any image set.")
    (license license:gpl3)))

(define-public r-colordf
  (package
    (name "r-colordf")
    (version "0.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colorDF" version))
       (sha256
        (base32 "0sw455xwnsp4sp37h4c5gz5l5jnwc6ng1rfxfh97ps2gjykmyvdj"))))
    (properties `((upstream-name . "colorDF")))
    (build-system r-build-system)
    (propagated-inputs (list r-purrr r-crayon))
    (native-inputs (list r-knitr))
    (home-page "https://january3.github.io/colorDF/")
    (synopsis "Colorful Data Frames in R Terminal")
    (description
     "Colorful Data Frames in the terminal.  The new class does change the behaviour
of any of the objects, but adds a style definition and a print method.  Using
ANSI escape codes, it colors the terminal output of data frames.  Some column
types (such as p-values and identifiers) are automatically recognized.")
    (license license:gpl3)))

(define-public r-colorblindness
  (package
    (name "r-colorblindness")
    (version "0.1.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colorBlindness" version))
       (sha256
        (base32 "1gzjxvfsj9g07jkcmw04wwzl4rwy16prj4zvsa1mw2zavqindp8h"))))
    (properties `((upstream-name . "colorBlindness")))
    (build-system r-build-system)
    (propagated-inputs (list r-gtable r-gridgraphics r-ggplot2 r-cowplot
                             r-colorspace))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=colorBlindness")
    (synopsis "Safe Color Set for Color Blindness")
    (description
     "Provide the safe color set for color blindness, the simulator of protanopia,
deuteranopia.  The color sets are collected from: Wong, B. (2011)
<doi:10.1038/nmeth.1618>, and <http://mkweb.bcgsc.ca/biovis2012/>.  The
simulations of the appearance of the colors to color-deficient viewers were
based on algorithms in Vienot, F., Brettel, H. and Mollon, J.D. (1999)
<doi:10.1002/(SICI)1520-6378(199908)24:4%3C243::AID-COL5%3E3.0.CO;2-3>.  The
@code{cvdPlot}() function to generate ggplot grobs of simulations were modified
from <https://github.com/clauswilke/colorblindr>.")
    (license license:gpl2+)))

(define-public r-colorblindcheck
  (package
    (name "r-colorblindcheck")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colorblindcheck" version))
       (sha256
        (base32 "1vy4ls5fmzy1bx2garhkvy2f4wqwjy2ph9b3jlzdl5f2lpx2mwq2"))))
    (properties `((upstream-name . "colorblindcheck")))
    (build-system r-build-system)
    (propagated-inputs (list r-spacesxyz r-colorspace))
    (native-inputs (list r-knitr))
    (home-page "https://jakubnowosad.com/colorblindcheck/")
    (synopsis "Check Color Palettes for Problems with Color Vision Deficiency")
    (description
     "Compare color palettes with simulations of color vision deficiencies -
deuteranopia, protanopia, and tritanopia.  It includes calculation of distances
between colors, and creating summaries of differences between a color palette
and simulations of color vision deficiencies.  This work was inspired by the
blog post at <http://www.vis4.net/blog/2018/02/automate-colorblind-checking/>.")
    (license license:expat)))

(define-public r-colopendata
  (package
    (name "r-colopendata")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ColOpenData" version))
       (sha256
        (base32 "10nb1mgxxxwbbq9s39dml89q8rk6xnfanklcrvqcphgafm91sf8d"))))
    (properties `((upstream-name . "ColOpenData")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringdist
                             r-sf
                             r-rlang
                             r-magrittr
                             r-dplyr
                             r-config
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/epiverse-trace/ColOpenData")
    (synopsis "Download Colombian Demographic, Climate and Geospatial Data")
    (description
     "Downloads wrangled Colombian socioeconomic, geospatial,population and climate
data from DANE <https://www.dane.gov.co/> (National Administrative Department of
Statistics) and IDEAM <https://ideam.gov.co> (Institute of Hydrology,
Meteorology and Environmental Studies).  It solves the problem of Colombian data
being issued in different web pages and sources by using functions that allow
the user to select the desired database and download it without having to do the
exhausting acquisition process.")
    (license license:expat)))

(define-public r-colocr
  (package
    (name "r-colocr")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colocr" version))
       (sha256
        (base32 "0ijykza6fdmwbr5zbyfjf382anrxh0lb9hlallyawfi6z076fv7j"))))
    (properties `((upstream-name . "colocr")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-scales r-magrittr r-magick r-imager))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/colocr")
    (synopsis
     "Conduct Co-Localization Analysis of Fluorescence Microscopy Images")
    (description
     "Automate the co-localization analysis of fluorescence microscopy images.
Selecting regions of interest, extract pixel intensities from the image channels
and calculate different co-localization statistics.  The methods implemented in
this package are based on Dunn et al. (2011) <doi:10.1152/ajpcell.00462.2010>.")
    (license license:gpl3)))

(define-public r-colocproptest
  (package
    (name "r-colocproptest")
    (version "0.9.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colocPropTest" version))
       (sha256
        (base32 "1nz5x1j2xagy6sx85m6cvzhvzj59byircl35ammj860vkp050rm9"))))
    (properties `((upstream-name . "colocPropTest")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-data-table r-coloc r-car))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=colocPropTest")
    (synopsis "Proportional Testing for Colocalisation Analysis")
    (description
     "Colocalisation analysis tests whether two traits share a causal genetic variant
in a specified genomic region.  Proportional testing for colocalisation has been
previously proposed [Wallace (2013) <doi:10.1002/gepi.21765>], but is
reimplemented here to overcome barriers to its adoption.  Its use is
complementary to the fine- mapping based colocalisation method in the coloc
package, and may be used in particular to identify false \"H3\" conclusions in
coloc'.")
    (license license:gpl3+)))

(define-public r-colocalized
  (package
    (name "r-colocalized")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colocalized" version))
       (sha256
        (base32 "1q98wfqk0p9p92jgjf8liamz6grzwy6h57k7681fm07wfnyr268g"))))
    (properties `((upstream-name . "colocalized")))
    (build-system r-build-system)
    (propagated-inputs (list r-purrr r-foreach r-doparallel))
    (home-page "https://cran.r-project.org/package=colocalized")
    (synopsis "Clusters of Colocalized Sequences")
    (description
     "Also abbreviates to \"CCSeq\".  Finds clusters of colocalized sequences in .bed
annotation files up to a specified cut-off distance.  Two sequences are
colocalized if they are within the cut-off distance of each other, and clusters
are sets of sequences where each sequence is colocalized to at least one other
sequence in the cluster.  For a set of .bed annotation tables provided in a list
along with a cut-off distance, the program will output a file containing the
locations of each cluster.  Annotated .bed files are from the pwmscan
application at <https://ccg.epfl.ch/pwmtools/pwmscan.php>.  Personal machines
might crash or take excessively long depending on the number of annotated
sequences in each file and whether chromsearch() or gensearch() is used.")
    (license license:expat)))

(define-public r-colocalization
  (package
    (name "r-colocalization")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colocalization" version))
       (sha256
        (base32 "0jrrh9nxjl3261rp1fnjfnydpxwpi7v0d20kzd0xc6awf52gydbb"))))
    (properties `((upstream-name . "colocalization")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2))
    (home-page "https://cran.r-project.org/package=colocalization")
    (synopsis "Normalized Spatial Intensity Correlation")
    (description
     "Calculate the colocalization index, NS@code{InC}, in two different ways as
described in the paper (Liu et al., 2019.  Manuscript submitted for
publication.) for multiple-species spatial data which contain the precise
locations and membership of each spatial point.  The two main functions are
nsinc.d() and nsinc.z().  They provide the Pearsonâs correlation coefficients
of signal proportions in different memberships within a concerned proximity of
every signal (or every base signal if single direction colocalization is
considered) across all (base) signals using two different ways of normalization.
 The proximity sizes could be an individual value or a range of values, where
the default ranges of values are different for the two functions.")
    (license license:gpl3)))

(define-public r-coloc
  (package
    (name "r-coloc")
    (version "5.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coloc" version))
       (sha256
        (base32 "0l318ad8sn151fjibgfvy082ar29f8c6x3qlmmhal2fq2fbbv795"))))
    (properties `((upstream-name . "coloc")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis r-susier r-ggplot2 r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/chr1swallace/coloc")
    (synopsis "Colocalisation Tests of Two Genetic Traits")
    (description
     "This package performs the colocalisation tests described in Giambartolomei et al
(2013) <doi:10.1371/journal.pgen.1004383>, Wallace (2020)
<doi:10.1371/journal.pgen.1008720>, Wallace (2021)
<doi:10.1371/journal.pgen.1009440>.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-colmozzie
  (package
    (name "r-colmozzie")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colmozzie" version))
       (sha256
        (base32 "0sn7dqg7rnddnmdb10c6scws6kgi1lz4lw8nc698x63z431ah1p8"))))
    (properties `((upstream-name . "colmozzie")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=colmozzie")
    (synopsis "Dengue Cases and Climate Variables in Colombo Sri Lanka")
    (description
     "Weekly notified dengue cases and climate variables in Colombo district Sri Lanka
from 2008/ week-52 to 2014/ week-21.")
    (license license:cc0)))

(define-public r-collutils
  (package
    (name "r-collutils")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "collUtils" version))
       (sha256
        (base32 "0gbk3lrb2lwq2ixrpcngng6qz6axjb4iyqy5606x1zmjm71c060p"))))
    (properties `((upstream-name . "collUtils")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (propagated-inputs (list r-rjava r-rcpp))
    (home-page "https://bitbucket.org/kindlychung/collutils")
    (synopsis "Auxiliary Package for Package 'CollapsABEL'")
    (description
     "This package provides some low level functions for processing PLINK input and
output files.")
    (license license:gpl3)))

(define-public r-collpcm
  (package
    (name "r-collpcm")
    (version "1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "collpcm" version))
       (sha256
        (base32 "170pi66zw3h0yz8d34bg9n4qxkdn941xxi818g0vnkilvqyhjnib"))))
    (properties `((upstream-name . "collpcm")))
    (build-system r-build-system)
    (propagated-inputs (list r-network r-latentnet r-gtools))
    (home-page "https://cran.r-project.org/package=collpcm")
    (synopsis "Collapsed Latent Position Cluster Model for Social Networks")
    (description
     "Markov chain Monte Carlo based inference routines for collapsed latent position
cluster models or social networks, which includes searches over the model space
(number of clusters in the latent position cluster model).  The label switching
algorithm used is that of Nobile and Fearnside (2007)
<doi:10.1007/s11222-006-9014-7> which relies on the algorithm of Carpaneto and
Toth (1980) <doi:10.1145/355873.355883>.")
    (license license:gpl3)))

(define-public r-collocinfer
  (package
    (name "r-collocinfer")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CollocInfer" version))
       (sha256
        (base32 "1iwf5g2y7i0j8dc19hdhya4m6g47jj968glnclj7a2yaq2yx37cj"))))
    (properties `((upstream-name . "CollocInfer")))
    (build-system r-build-system)
    (propagated-inputs (list r-spam r-matrix r-mass r-fda r-desolve))
    (home-page "http://www.bscb.cornell.edu/~hooker")
    (synopsis "Collocation Inference for Dynamic Systems")
    (description
     "These functions implement collocation-inference for continuous-time and
discrete-time stochastic processes.  They provide model-based smoothing,
gradient-matching, generalized profiling and forwards prediction error methods.")
    (license license:gpl2+)))

(define-public r-collinear
  (package
    (name "r-collinear")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "collinear" version))
       (sha256
        (base32 "1vflihmpbqhfl9y8a2s5pnj4pjdj9m20mk80lm6lvff1pjwj2sbp"))))
    (properties `((upstream-name . "collinear")))
    (build-system r-build-system)
    (propagated-inputs (list r-dplyr))
    (home-page "https://blasbenito.github.io/collinear/")
    (synopsis "Seamless Multicollinearity Management")
    (description
     "System for seamless management of multicollinearity in data frames with numeric
and/or categorical variables for statistical analysis and machine learning
modeling.  The package combines bivariate correlation (Pearson, Spearman, and
Cramer's V) with variance inflation factor analysis, target encoding to
transform categorical variables into numeric (Micci-Barreca, D. 2001
<DOI:10.1145/507533.507538>), and a flexible feature prioritization method, to
deliver a comprehensive multicollinearity management tool covering a wide range
of use cases.")
    (license license:expat)))

(define-public r-collin
  (package
    (name "r-collin")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "collin" version))
       (sha256
        (base32 "0dh3k9rh1ykrd5nvp5nh4q7zvv835hx8ydpyml88d90ksy8za90p"))))
    (properties `((upstream-name . "collin")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam r-nlme r-mgcv r-mass r-dlnm))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=collin")
    (synopsis
     "Visualization the Effects of Collinearity in Distributed Lag Models and Other Linear Models")
    (description
     "Tool to assessing whether the results of a study could be influenced by
collinearity.  Simulations under a given hypothesized truth regarding effects of
an exposure on the outcome are used and the resulting curves of lagged effects
are visualized.  A user's manual is provided, which includes detailed examples
(e.g. a cohort study looking for windows of vulnerability to air pollution, a
time series study examining the linear association of air pollution with
hospital admissions, and a time series study examining the non-linear
association between temperature and mortality).  The methods are described in
Basagana and Barrera-Gomez (2021) <doi:10.1093/ije/dyab179>.")
    (license license:gpl3)))

(define-public r-collidr
  (package
    (name "r-collidr")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "collidr" version))
       (sha256
        (base32 "18ki8mwf5ihbgfbhdbbk9ljs44js3rqgl1g6g3ch6dynz61sr6hn"))))
    (properties `((upstream-name . "collidr")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-jsonlite r-dplyr))
    (home-page "https://github.com/collidrpackage/collidr")
    (synopsis
     "Check for Namespace Collisions Across Packages and Functions on CRAN")
    (description
     "Check for namespace collisions between a string input (your function or package
name) and half a million packages and functions on CRAN.")
    (license license:expat)))

(define-public r-collegescorecard
  (package
    (name "r-collegescorecard")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "collegeScorecard" version))
       (sha256
        (base32 "06v8r8ldlx1n4wp5mhzizh92pyysj7zjvcn6vrh5n4w28f719i8q"))))
    (properties `((upstream-name . "collegeScorecard")))
    (build-system r-build-system)
    (home-page "https://github.com/gadenbuie/scorecard-db")
    (synopsis "US College Scorecard Data")
    (description
     "This package provides a tidied subset of the US College Scorecard dataset,
containing institutional characteristics, enrollment, student aid, costs, and
student outcomes at institutions of higher education in the United States.")
    (license license:cc0)))

(define-public r-collatz
  (package
    (name "r-collatz")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "collatz" version))
       (sha256
        (base32 "02dvivahpq3zyiyhx7w36bs3dw1p2r3g167sjf3k173q7rr77p0m"))))
    (properties `((upstream-name . "collatz")))
    (build-system r-build-system)
    (propagated-inputs (list r-gmp))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Skenvy/Collatz")
    (synopsis "Functions Related to the Collatz/Syracuse/3n+1 Problem")
    (description
     "This package provides the basic functionality to interact with the Collatz
conjecture.  The parameterisation uses the same (P,a,b) notation as Conway's
generalisations.  Besides the function and reverse function, there is also
functionality to retrieve the hailstone sequence, the \"stopping time\"/\"total
stopping time\", or tree-graph.  The only restriction placed on parameters is
that both P and a can't be 0.  For further reading, see
<https://en.wikipedia.org/wiki/Collatz_conjecture>.")
    (license license:asl2.0)))

(define-public r-collateral
  (package
    (name "r-collateral")
    (version "0.5.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "collateral" version))
       (sha256
        (base32 "1wnzgpayjsqnqry0cdmkijyjkkjhbc8hxwlkx7aj9qwaiz7wiibr"))))
    (properties `((upstream-name . "collateral")))
    (build-system r-build-system)
    (propagated-inputs (list r-purrr r-pillar r-crayon))
    (native-inputs (list r-knitr))
    (home-page "https://collateral.jamesgoldie.dev")
    (synopsis "Quickly Evaluate Captured Side Effects")
    (description
     "Map functions while capturing results, errors, warnings, messages and other
output tidily, then filter and summarise data frames or lists on the basis of
those side effects.")
    (license license:expat)))

(define-public r-collapselevels
  (package
    (name "r-collapselevels")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CollapseLevels" version))
       (sha256
        (base32 "1d2grxh95893j260igh4yh2z3rm3zymlpadqyp6w3na91birazb4"))))
    (properties `((upstream-name . "CollapseLevels")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-lazyeval r-ggplot2 r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CollapseLevels")
    (synopsis "Collapses Levels, Computes Information Value and WoE")
    (description
     "This package contains functions to help in selecting and exploring features ( or
variables ) in binary classification problems.  Provides functions to compute
and display information value and weight of evidence (@code{WoE}) of the
variables , and to convert numeric variables to categorical variables by
binning.  Functions are also provided to determine which levels ( or categories
) of a categorical variable can be collapsed (or combined ) based on their
response rates.  The functions provided only work for binary classification
problems.")
    (license license:gpl2)))

(define-public r-colf
  (package
    (name "r-colf")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "colf" version))
       (sha256
        (base32 "1av82yrp6csw7700ymipd02j73cmzn0apv7ykachjw09nzk86kvj"))))
    (properties `((upstream-name . "colf")))
    (build-system r-build-system)
    (propagated-inputs (list r-nlsr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/LyzandeR/colf")
    (synopsis "Constrained Optimization on Linear Function")
    (description
     "This package performs least squares constrained optimization on a linear
objective function.  It contains a number of algorithms to choose from and
offers a formula syntax similar to lm().")
    (license license:expat)))

(define-public r-cold
  (package
    (name "r-cold")
    (version "2.0-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cold" version))
       (sha256
        (base32 "1y2l1v7s1v3m4nhlnl72n075h53vm93vxmfn4b6269n690wl9s6d"))))
    (properties `((upstream-name . "cold")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-cubature))
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=cold")
    (synopsis "Count Longitudinal Data")
    (description
     "This package performs regression analysis for longitudinal count data, allowing
for serial dependence among observations from a given individual and two
dimensional random effects on the linear predictor.  Estimation is via
maximization of the exact likelihood of a suitably defined model.  Missing
values and unbalanced data are allowed.  Details can be found in the
accompanying scientific papers: Goncalves & Cabral (2021, Journal of Statistical
Software, <doi:10.18637/jss.v099.i03>) and Goncalves et al. (2007, Computational
Statistics & Data Analysis, <doi:10.1016/j.csda.2007.03.002>).")
    (license license:gpl2+)))

(define-public r-cointreg
  (package
    (name "r-cointreg")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cointReg" version))
       (sha256
        (base32 "0n4s809avhlrmrjdqzc2s752m7x96c4432gnjd4qv77r2nns7dw4"))))
    (properties `((upstream-name . "cointReg")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrixstats r-mass r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/aschersleben/cointReg")
    (synopsis
     "Parameter Estimation and Inference in a Cointegrating Regression")
    (description
     "Cointegration methods are widely used in empirical macroeconomics and empirical
finance.  It is well known that in a cointegrating regression the ordinary least
squares (OLS) estimator of the parameters is super-consistent, i.e.  converges
at rate equal to the sample size T. When the regressors are endogenous, the
limiting distribution of the OLS estimator is contaminated by so-called second
order bias terms, see e.g. Phillips and Hansen (1990) <DOI:10.2307/2297545>.
The presence of these bias terms renders inference difficult.  Consequently,
several modifications to OLS that lead to zero mean Gaussian mixture limiting
distributions have been proposed, which in turn make standard asymptotic
inference feasible.  These methods include the fully modified OLS (FM-OLS)
approach of Phillips and Hansen (1990) <DOI:10.2307/2297545>, the dynamic OLS
(D-OLS) approach of Phillips and Loretan (1991) <DOI:10.2307/2298004>, Saikkonen
(1991) <DOI:10.1017/S0266466600004217> and Stock and Watson (1993)
<DOI:10.2307/2951763> and the new estimation approach called integrated modified
OLS (IM-OLS) of Vogelsang and Wagner (2014) <DOI:10.1016/j.jeconom.2013.10.015>.
 The latter is based on an augmented partial sum (integration) transformation of
the regression model.  IM-OLS is similar in spirit to the FM- and D-OLS
approaches, with the key difference that it does not require estimation of long
run variance matrices and avoids the need to choose tuning parameters (kernels,
bandwidths, lags).  However, inference does require that a long run variance be
scaled out.  This package provides functions for the parameter estimation and
inference with all three modified OLS approaches.  That includes the automatic
bandwidth selection approaches of Andrews (1991) <DOI:10.2307/2938229> and of
Newey and West (1994) <DOI:10.2307/2297912> as well as the calculation of the
long run variance.")
    (license license:gpl3)))

(define-public r-cointmonitor
  (package
    (name "r-cointmonitor")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cointmonitoR" version))
       (sha256
        (base32 "0rsacvib9prgb199m5ndi0zlgfsvf1giqc5s41wp0yvxdxjdq5lw"))))
    (properties `((upstream-name . "cointmonitoR")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrixstats r-cointreg))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/aschersleben/cointmonitoR")
    (synopsis
     "Consistent Monitoring of Stationarity and Cointegrating Relationships")
    (description
     "We propose a consistent monitoring procedure to detect a structural change from
a cointegrating relationship to a spurious relationship.  The procedure is based
on residuals from modified least squares estimation, using either Fully
Modified, Dynamic or Integrated Modified OLS. It is inspired by Chu et al.
(1996) <DOI:10.2307/2171955> in that it is based on parameter estimation on a
pre-break \"calibration\" period only, rather than being based on sequential
estimation over the full sample.  See the discussion paper
<DOI:10.2139/ssrn.2624657> for further information.  This package provides the
monitoring procedures for both the cointegration and the stationarity case
(while the latter is just a special case of the former one) as well as printing
and plotting methods for a clear presentation of the results.")
    (license license:gpl3)))

(define-public r-coinr
  (package
    (name "r-coinr")
    (version "1.1.14")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "COINr" version))
       (sha256
        (base32 "1fk2ha2g02f720kxxbxf2fkg2xyg81y3p181zy0yj8f4mjxp0w1s"))))
    (properties `((upstream-name . "COINr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-readxl r-openxlsx r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://bluefoxr.github.io/COINr/")
    (synopsis "Composite Indicator Construction and Analysis")
    (description
     "This package provides a comprehensive high-level package, for composite
indicator construction and analysis.  It is a \"development environment\" for
composite indicators and scoreboards, which includes utilities for construction
(indicator selection, denomination, imputation, data treatment, normalisation,
weighting and aggregation) and analysis (multivariate analysis, correlation
plotting, short cuts for principal component analysis, global sensitivity
analysis, and more).  A composite indicator is completely encapsulated inside a
single hierarchical list called a \"coin\".  This allows a fast and efficient work
flow, as well as making quick copies, testing methodological variations and
making comparisons.  It also includes many plotting options, both statistical
(scatter plots, distribution plots) as well as for presenting results.")
    (license license:expat)))

(define-public r-coinprofile
  (package
    (name "r-coinprofile")
    (version "0.1.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Coinprofile" version))
       (sha256
        (base32 "1bcip62gm34cx5m8a1mx9px2rhgvdmsgnn6q9q40k8p5hw4cx9g0"))))
    (properties `((upstream-name . "Coinprofile")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-rdpack
                             r-plyr
                             r-ggplot2
                             r-exactranktests
                             r-coin))
    (home-page "https://github.com/WilmerMartinezR/Coinprofile")
    (synopsis "Coincident Profile")
    (description
     "Builds the coincident profile proposed by Martinez, W and Nieto, Fabio H and
Poncela, P (2016) <doi:10.1016/j.spl.2015.11.008>.  This methodology studies the
relationship between a couple of time series based on the the set of turning
points of each time series.  The coincident profile establishes if two time
series are coincident, or one of them leads the second.")
    (license license:gpl2)))

(define-public r-coinmarketcapr
  (package
    (name "r-coinmarketcapr")
    (version "0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coinmarketcapr" version))
       (sha256
        (base32 "1h95fm32w03gxjka71n41lxkinfwpal4dl6hmhfdph8wywn7y50j"))))
    (properties `((upstream-name . "coinmarketcapr")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite
                             r-ggplot2
                             r-data-table
                             r-curl
                             r-crayon
                             r-cli))
    (home-page "https://github.com/amrrs/coinmarketcapr")
    (synopsis "Get 'Cryptocurrencies' Market Cap Prices from Coin Market Cap")
    (description
     "Extract and monitor price and market cap of Cryptocurrencies from Coin Market
Cap <https://coinmarketcap.com/api/>.")
    (license license:expat)))

(define-public r-coimp
  (package
    (name "r-coimp")
    (version "2.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoImp" version))
       (sha256
        (base32 "1hn6nf37z90pwhixfwjj5r9avv03k6bsc099j3d4j8g3wc40mlx4"))))
    (properties `((upstream-name . "CoImp")))
    (build-system r-build-system)
    (propagated-inputs (list r-nnet r-locfit r-gtools r-copula r-cluster))
    (home-page "https://cran.r-project.org/package=CoImp")
    (synopsis "Parametric and Non-Parametric Copula-Based Imputation Methods")
    (description
     "Copula-based imputation methods: parametric and non-parametric algorithms for
missing multivariate data through conditional copulas.")
    (license license:gpl2+)))

(define-public r-coil
  (package
    (name "r-coil")
    (version "1.2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coil" version))
       (sha256
        (base32 "1jkhci42r3kx554dvpbdnyfzml0l9csxa5fm1ds13c6ny6z54c06"))))
    (properties `((upstream-name . "coil")))
    (build-system r-build-system)
    (propagated-inputs (list r-seqinr r-aphid r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=coil")
    (synopsis "Contextualization and Evaluation of COI-5P Barcode Data")
    (description
     "Designed for the cleaning, contextualization and assessment of cytochrome c
oxidase I DNA barcode data (COI-5P, or the five prime portion of COI).  It
contains functions for placing COI-5P barcode sequences into a common reading
frame, translating DNA sequences to amino acids and for assessing the likelihood
that a given barcode sequence includes an insertion or deletion error.  The
error assessment relies on the comparison of input sequences against nucleotide
and amino acid profile hidden Markov models (PHMMs) (for details see Durbin et
al.  1998, ISBN: 9780521629713) trained on a taxonomically diverse set of
reference sequences.  The functions are provided as a complete pipeline and are
also available individually for efficient and targeted analysis of barcode data.")
    (license license:gpl3)))

(define-public r-cohorttools
  (package
    (name "r-cohorttools")
    (version "0.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cohorttools" version))
       (sha256
        (base32 "17gz4887vhkk0qr5mcv0vcfaxiws1pk1fdd4y8wqbl57ikn5i9vs"))))
    (properties `((upstream-name . "cohorttools")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-rsvg
                             r-mgcv
                             r-ggplot2
                             r-epi
                             r-diagrammersvg
                             r-diagrammer
                             r-cmprsk))
    (home-page "https://cran.r-project.org/package=cohorttools")
    (synopsis "Cohort Data Analyses")
    (description
     "This package provides functions to make lifetables and to calculate hazard
function estimate using Poisson regression model with splines.  Includes
function to draw simple flowchart of cohort study.  Function @code{boxesLx}()
makes boxes of transition rates between states.  It utilizes Epi package Lexis
data.")
    (license license:gpl2)))

(define-public r-cohortsymmetry
  (package
    (name "r-cohortsymmetry")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CohortSymmetry" version))
       (sha256
        (base32 "15rmz8r3q52mmmr7h639az3ayiylxwiqny5kl6ksdlg4pb0hiw9q"))))
    (properties `((upstream-name . "CohortSymmetry")))
    (build-system r-build-system)
    (propagated-inputs (list r-visomopresults
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-patientprofiles
                             r-omopgenerics
                             r-omock
                             r-magrittr
                             r-here
                             r-gt
                             r-ggplot2
                             r-flextable
                             r-duckdb
                             r-drugutilisation
                             r-dplyr
                             r-codelistgenerator
                             r-cdmconnector))
    (native-inputs (list r-knitr))
    (home-page "https://oxford-pharmacoepi.github.io/CohortSymmetry/")
    (synopsis
     "Sequence Symmetry Analysis Using the Observational Medical Outcomes Partnership Common Data Model")
    (description
     "Calculating crude sequence ratio, adjusted sequence ratio and confidence
intervals using data mapped to the Observational Medical Outcomes Partnership
Common Data Model.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-cohortsurvival
  (package
    (name "r-cohortsurvival")
    (version "0.5.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CohortSurvival" version))
       (sha256
        (base32 "02p0n7nhwa50z3w3q20nx2pp6sdkbyqwmk7ix7s2cc8i7qxxhlfl"))))
    (properties `((upstream-name . "CohortSurvival")))
    (build-system r-build-system)
    (propagated-inputs (list r-visomopresults
                             r-tidyr
                             r-tibble
                             r-survival
                             r-stringr
                             r-scales
                             r-rlang
                             r-purrr
                             r-patientprofiles
                             r-omopgenerics
                             r-magrittr
                             r-lubridate
                             r-dplyr
                             r-dbplyr
                             r-dbi
                             r-cli
                             r-checkmate
                             r-cdmconnector
                             r-broom))
    (native-inputs (list r-knitr))
    (home-page "https://darwin-eu-dev.github.io/CohortSurvival/")
    (synopsis "Estimate Survival from Common Data Model Cohorts")
    (description
     "Estimate survival using data mapped to the Observational Medical Outcomes
Partnership common data model.  Survival can be estimated based on user-defined
study cohorts.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-cohorts
  (package
    (name "r-cohorts")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cohorts" version))
       (sha256
        (base32 "0g3xllmk5n4s2w10a2460v735bsc2xnkxgcr9zkvl8sz8rczrs2n"))))
    (properties `((upstream-name . "cohorts")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-tidyr
                             r-tibble
                             r-magrittr
                             r-dtplyr
                             r-dplyr
                             r-data-table))
    (home-page "https://github.com/PeerChristensen/cohorts")
    (synopsis "Cohort Analysis Made Easy")
    (description
     "This package provides functions to simplify the process of preparing event and
transaction for cohort analysis.")
    (license license:expat)))

(define-public r-cohortplat
  (package
    (name "r-cohortplat")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CohortPlat" version))
       (sha256
        (base32 "01jvi7k3lvx684c4cwn3xrpwjsksk7gjvs3db64ji7chc4lkajv4"))))
    (properties `((upstream-name . "CohortPlat")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-tidyr
                             r-purrr
                             r-plotly
                             r-openxlsx
                             r-ggplot2
                             r-foreach
                             r-forcats
                             r-epitools
                             r-dplyr
                             r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CohortPlat")
    (synopsis
     "Simulation of Cohort Platform Trials for Combination Treatments")
    (description
     "This package provides a collection of functions dedicated to simulating
staggered entry platform trials whereby the treatment under investigation is a
combination of two active compounds.  In order to obtain approval for this
combination therapy, superiority of the combination over the two active
compounds and superiority of the two active compounds over placebo need to be
demonstrated.  A more detailed description of the design can be found in Meyer
et al. <DOI:10.1002/pst.2194> and a manual in Meyer et al.
<@code{arXiv:2202.02182>}.")
    (license license:expat)))

(define-public r-cohortgenerator
  (package
    (name "r-cohortgenerator")
    (version "0.11.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CohortGenerator" version))
       (sha256
        (base32 "02fsdwswdpgv0cf2naqj9p0fv8qxvcsani68dl05hcnsj7qrhgs6"))))
    (properties `((upstream-name . "CohortGenerator")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringi
                             r-sqlrender
                             r-rlang
                             r-rjsonio
                             r-resultmodelmanager
                             r-readr
                             r-r6
                             r-parallellogger
                             r-lubridate
                             r-jsonlite
                             r-dplyr
                             r-digest
                             r-databaseconnector
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://ohdsi.github.io/CohortGenerator/")
    (synopsis "Cohort Generation for the OMOP Common Data Model")
    (description
     "Generate cohorts and subsets using an Observational Medical Outcomes Partnership
(OMOP) Common Data Model (CDM) Database.  Cohorts are defined using CIRCE
(<https://github.com/ohdsi/circe-be>) or SQL compatible with @code{SqlRender}
(<https://github.com/OHDSI/@code{SqlRender>}).")
    (license (license:fsdg-compatible "Apache License"))))

(define-public r-cohortexplorer
  (package
    (name "r-cohortexplorer")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CohortExplorer" version))
       (sha256
        (base32 "1jskxg72g7n5n3zg2kmkhykcrbf30q0h919273n6lm6nw0pzn44d"))))
    (properties `((upstream-name . "CohortExplorer")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-parallellogger
                             r-lifecycle
                             r-dplyr
                             r-databaseconnector
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://ohdsi.github.io/CohortExplorer/")
    (synopsis "Explorer of Profiles of Patients in a Cohort")
    (description
     "This software tool is designed to extract data from a randomized subset of
individuals within a cohort and make it available for exploration in a shiny
application environment.  It retrieves date-stamped, event-level records from
one or more data sources that represent patient data in the Observational
Medical Outcomes Partnership (OMOP) data model format.  This tool features a
user-friendly interface that enables users to efficiently explore the extracted
profiles, thereby facilitating applications, such as reviewing structured
profiles.")
    (license (license:fsdg-compatible "Apache License"))))

(define-public r-cohortconstructor
  (package
    (name "r-cohortconstructor")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CohortConstructor" version))
       (sha256
        (base32 "0sh9i7bv64zdqjzdb3hh3kkixahw465j30ryg79gvlsyrj2h41as"))))
    (properties `((upstream-name . "CohortConstructor")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rlang
                             r-purrr
                             r-patientprofiles
                             r-omopgenerics
                             r-magrittr
                             r-glue
                             r-dplyr
                             r-dbplyr
                             r-cli
                             r-checkmate
                             r-cdmconnector))
    (native-inputs (list r-knitr))
    (home-page "https://ohdsi.github.io/CohortConstructor/")
    (synopsis "Build and Manipulate Study Cohorts Using a Common Data Model")
    (description
     "Create and manipulate study cohorts in data mapped to the Observational Medical
Outcomes Partnership Common Data Model.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-cohortcharacteristics
  (package
    (name "r-cohortcharacteristics")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CohortCharacteristics" version))
       (sha256
        (base32 "017yflwvfnsvkm03m5p31hx1f4wmws14nab1n493ingmhmxaqbfs"))))
    (properties `((upstream-name . "CohortCharacteristics")))
    (build-system r-build-system)
    (propagated-inputs (list r-visomopresults
                             r-tidyr
                             r-stringr
                             r-snakecase
                             r-rlang
                             r-purrr
                             r-patientprofiles
                             r-omopgenerics
                             r-lifecycle
                             r-dplyr
                             r-cli
                             r-cdmconnector))
    (native-inputs (list r-knitr))
    (home-page "https://darwin-eu-dev.github.io/CohortCharacteristics/")
    (synopsis
     "Summarise and Visualise Characteristics of Patients in the OMOP CDM")
    (description
     "Summarise and visualise the characteristics of patients in data mapped to the
Observational Medical Outcomes Partnership (OMOP) common data model (CDM).")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-cohortbuilder
  (package
    (name "r-cohortbuilder")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cohortBuilder" version))
       (sha256
        (base32 "0rwqi9sh69j1bx116q41gby7j0lrh81j232xlp003vs4i7pwwx4k"))))
    (properties `((upstream-name . "cohortBuilder")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-rlang
                             r-r6
                             r-purrr
                             r-magrittr
                             r-jsonlite
                             r-glue
                             r-ggplot2
                             r-formatr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/r-world-devs/cohortBuilder/")
    (synopsis "Data Source Agnostic Filtering Tools")
    (description
     "Common API for filtering data stored in different data models.  Provides
multiple filter types and reproducible R code.  Works standalone or with
@code{shinyCohortBuilder} as the GUI for interactive Shiny apps.")
    (license license:expat)))

(define-public r-cohortalgebra
  (package
    (name "r-cohortalgebra")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CohortAlgebra" version))
       (sha256
        (base32 "05sn073sfmngjbq2g198nckxw2zwk2jj69xf3pddlrka05v3a1b9"))))
    (properties `((upstream-name . "CohortAlgebra")))
    (build-system r-build-system)
    (propagated-inputs (list r-sqlrender
                             r-rlang
                             r-lifecycle
                             r-dplyr
                             r-databaseconnector
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/OHDSI/CohortAlgebra")
    (synopsis
     "Use of Interval Algebra to Create New Cohort(s) from Existing Cohorts")
    (description
     "This software tool is designed to generate new cohorts utilizing data from
previously instantiated cohorts.  It employs interval algebra operators such as
UNION, INTERSECT, and MINUS to manipulate the data within the instantiated
cohorts and create new cohorts.")
    (license (license:fsdg-compatible "Apache License"))))

(define-public r-cohensdplibrary
  (package
    (name "r-cohensdplibrary")
    (version "0.5.11")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CohensdpLibrary" version))
       (sha256
        (base32 "16zsjc6n05ffk35qrdslgvzdva9cwq7by1vsjr3y35zv4wcvnxd8"))))
    (properties `((upstream-name . "CohensdpLibrary")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack))
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=CohensdpLibrary")
    (synopsis "Cohen's D_p Computation with Confidence Intervals")
    (description
     "Computing Cohen's d_p in any experimental designs (between-subject,
within-subject, and single-group design).  Cousineau (2022)
<https://github.com/dcousin3/@code{CohensdpLibrary>}; Cohen (1969, ISBN:
0-8058-0283-5).")
    (license license:gpl3)))

(define-public r-cognitor
  (package
    (name "r-cognitor")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cognitoR" version))
       (sha256
        (base32 "1ik2cdw1vigiplsrxy2mbv3l2w9wlzw6xkgrdm4l3pg9x6hhcx6s"))))
    (properties `((upstream-name . "cognitoR")))
    (build-system r-build-system)
    (propagated-inputs (list r-shinyjs
                             r-shiny
                             r-paws
                             r-jsonlite
                             r-httr
                             r-dplyr
                             r-config
                             r-base64enc))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cognitoR")
    (synopsis "Authentication for 'Shiny' Apps with 'Amazon Cognito'")
    (description
     "This package provides authentication for Shiny applications using Amazon Cognito
( <https://aws.amazon.com/es/cognito/>).")
    (license license:gpl3)))

(define-public r-cogmapr
  (package
    (name "r-cogmapr")
    (version "0.9.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cogmapr" version))
       (sha256
        (base32 "0aqlk6248m3pad0fwarvxvxfn4qfazhdbdplg8haw3aj165szq43"))))
    (properties `((upstream-name . "cogmapr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rgraphviz
                             r-magrittr
                             r-graph
                             r-ggplot2
                             r-dplyr))
    (home-page "https://frdvnw.gitlab.io/cogmapr/")
    (synopsis "Cognitive Mapping Tools Based on Coding of Textual Sources")
    (description
     "This package provides functions for building cognitive maps based on qualitative
data.  Inputs are textual sources (articles, transcription of qualitative
interviews of agents,...).  These sources have been coded using relations and
are linked to (i) a table describing the variables (or concepts) used for the
coding and (ii) a table describing the sources (typology of agents, ...).  Main
outputs are Individual Cognitive Maps (ICM), Social Cognitive Maps (all sources
or group of sources) and a list of quotes linked to relations.  This package is
linked to the work done during the @code{PhD} of Frederic M. Vanwindekens (CRA-W
/ UCL) hold the 13 of May 2014 at University of Louvain in collaboration with
the Walloon Agricultural Research Centre (project MIMOSA, MOERMAN fund).")
    (license license:gpl3)))

(define-public r-coglasso
  (package
    (name "r-coglasso")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coglasso" version))
       (sha256
        (base32 "0z4qdncmznprv16973jlj29vxxlkaqy6ari65fswn6ics2sz3xrr"))))
    (properties `((upstream-name . "coglasso")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppeigen r-rcpp r-matrix))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/DrQuestion/coglasso")
    (synopsis
     "Collaborative Graphical Lasso - Multi-Omics Network Reconstruction")
    (description
     "Reconstruct networks from multi-omics data sets with the collaborative graphical
lasso (coglasso) algorithm described in Albanese, A., Kohlen, W., and Behrouzi,
P. (2024) <@code{arXiv:2403.18602>}.  Build multiple networks using the
coglasso() function, select the best one with stars_coglasso().")
    (license license:gpl2+)))

(define-public r-coga
  (package
    (name "r-coga")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coga" version))
       (sha256
        (base32 "0h4qps0k973ia2aw19smlh84p34nnwdrfgk9nm4pgcs3qx3pn102"))))
    (properties `((upstream-name . "coga")))
    (build-system r-build-system)
    (inputs (list gsl))
    (propagated-inputs (list r-rcppgsl r-rcpp r-cubature))
    (native-inputs (list r-r-rsp))
    (home-page "https://github.com/ChaoranHu/coga")
    (synopsis "Convolution of Gamma Distributions")
    (description
     "Evaluation for density and distribution function of convolution of gamma
distributions in R. Two related exact methods and one approximate method are
implemented with efficient algorithm and C++ code.  A quick guide for choosing
correct method and usage of this package is given in package vignette.  For the
detail of methods used in this package, we refer the user to
Mathai(1982)<doi:10.1007/BF02481056>,
Moschopoulos(1984)<doi:10.1007/BF02481123>,
Barnabani(2017)<doi:10.1080/03610918.2014.963612>, Hu et
al.(2020)<doi:10.1007/s00180-019-00924-9>.")
    (license license:gpl3+)))

(define-public r-cofra
  (package
    (name "r-cofra")
    (version "0.1002")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoFRA" version))
       (sha256
        (base32 "0ldf84dxaanww3qkf64mz5gv3yv2rjp9m6dy64xckds66vw6x0m3"))))
    (properties `((upstream-name . "CoFRA")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-gplots))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CoFRA")
    (synopsis "Complete Functional Regulation Analysis")
    (description
     "Calculates complete functional regulation analysis and visualize the results in
a single heatmap.  The provided example data is for biological data but the
methodology can be used for large data sets to compare quantitative entities
that can be grouped.  For example, a store might divide entities into cloth,
food, car products etc and want to see how sales changes in the groups after
some event.  The theoretical background for the calculations are provided in New
insights into functional regulation in MS-based drug profiling, Ana Sofia
Carvalho, Henrik Molina & Rune Matthiesen, Scientific Reports
<doi:10.1038/srep18826>.")
    (license (list license:gpl2
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-cofid
  (package
    (name "r-cofid")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cofid" version))
       (sha256
        (base32 "0nmfs34339immz9vc79jvwvpx9fpp0qp4zvsm3i8c5v0la603xxz"))))
    (properties `((upstream-name . "cofid")))
    (build-system r-build-system)
    (home-page "<https://alrobles.github.io/cofid/>")
    (synopsis "Copepod Fish Interaction Database")
    (description
     "This package provides a curated list of copepod-fish ecological interaction
records.  It contains the taxonomy of the copepod and the fish and the
publication from which the information was obtained.  This database contains
only marine and brackish water fish species.  It excludes fish species that
inhabit only freshwater.")
    (license license:gpl3+)))

(define-public r-coffee
  (package
    (name "r-coffee")
    (version "0.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coffee" version))
       (sha256
        (base32 "1i5jical8rvv7v5mbni619z664c290wniqca82gymqvvdx0c67av"))))
    (properties `((upstream-name . "coffee")))
    (build-system r-build-system)
    (propagated-inputs (list r-rintcal r-rice r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Maarten14C/coffee")
    (synopsis "Chronological Ordering for Fossils and Environmental Events")
    (description
     "While individual calibrated radiocarbon dates can span several centuries,
combining multiple dates together with any chronological constraints can make a
chronology much more robust and precise.  This package uses Bayesian methods to
enforce the chronological ordering of radiocarbon and other dates, for example
for trees with multiple radiocarbon dates spaced at exactly known intervals
(e.g., 10 annual rings).  For methods see Christen 2003 <doi:10.11141/ia.13.2>.
Another example is sites where the relative chronological position of the dates
is taken into account - the ages of dates further down a site must be older than
those of dates further up (Buck, Kenworthy, Litton and Smith 1991
<doi:10.1017/S0003598X00080534>; Nicholls and Jones 2001
<doi:10.1111/1467-9876.00250>).  The paper accompanying this R package is Blaauw
et al.  2024 <doi:10.1017/RDC.2024.56>.")
    (license license:gpl2+)))

(define-public r-cofeaturer
  (package
    (name "r-cofeaturer")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cofeatureR" version))
       (sha256
        (base32 "1awfrlnbpw9ivfvaahznx6dx5jp8ln0154vh2pznp520q59h1mbs"))))
    (properties `((upstream-name . "cofeatureR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-lazyeval r-ggplot2 r-dplyr))
    (home-page "https://github.com/tinyheero/cofeatureR")
    (synopsis "Generate Cofeature Matrices")
    (description
     "Generate cofeature (feature by sample) matrices.  The package utilizes
ggplot2::geom_tile() to generate the matrix allowing for easy additions from the
base matrix.")
    (license license:gpl3)))

(define-public r-cofad
  (package
    (name "r-cofad")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cofad" version))
       (sha256
        (base32 "00m32r1rbc5f2b7viks68ff3sv7p4qvc1i8qag0z75l2jxi839f0"))))
    (properties `((upstream-name . "cofad")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-shinyjs
                             r-shinydashboard
                             r-shiny
                             r-rlang
                             r-rhandsontable
                             r-readr
                             r-magrittr
                             r-hmisc
                             r-dplyr))
    (home-page "https://github.com/johannes-titz/cofad")
    (synopsis "Contrast Analyses for Factorial Designs")
    (description
     "Contrast analysis for factorial designs provides an alternative to the
traditional ANOVA approach, offering the distinct advantage of testing targeted
hypotheses.  The foundation of this package is primarily rooted in the works of
Rosenthal, Rosnow, and Rubin (2000, ISBN: 978-0521659802) as well as Sedlmeier
and Renkewitz (2018, ISBN: 978-3868943214).")
    (license license:lgpl3+)))

(define-public r-coenoflex
  (package
    (name "r-coenoflex")
    (version "2.2-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coenoflex" version))
       (sha256
        (base32 "06f75spl4wkbgicm0bksnid2lb1gkvi05915wn5y4km45d82fkkr"))))
    (properties `((upstream-name . "coenoflex")))
    (build-system r-build-system)
    (propagated-inputs (list r-mgcv))
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=coenoflex")
    (synopsis "Gradient-Based Coenospace Vegetation Simulator")
    (description
     "Simulates the composition of samples of vegetation according to gradient-based
vegetation theory.  Features a flexible algorithm incorporating competition and
complex multi-gradient interaction.")
    (license license:gpl2+)))

(define-public r-coenocliner
  (package
    (name "r-coenocliner")
    (version "0.2-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coenocliner" version))
       (sha256
        (base32 "07hik9y84nj1l83spcp1hq9lj960zsg3v0i8rk0xfv25grrakp85"))))
    (properties `((upstream-name . "coenocliner")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/gavinsimpson/coenocliner/")
    (synopsis "Coenocline Simulation")
    (description
     "Simulate species occurrence and abundances (counts) along gradients.")
    (license license:gpl2)))

(define-public r-coefplot
  (package
    (name "r-coefplot")
    (version "1.2.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coefplot" version))
       (sha256
        (base32 "0qxa57sm5hncmd4mxab1c7hk34n2s5fsn51ck6ik2ciynhgcqxvn"))))
    (properties `((upstream-name . "coefplot")))
    (build-system r-build-system)
    (propagated-inputs (list r-useful
                             r-tibble
                             r-reshape2
                             r-purrr
                             r-plyr
                             r-plotly
                             r-magrittr
                             r-ggplot2
                             r-dygraphs
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=coefplot")
    (synopsis "Plots Coefficients from Fitted Models")
    (description
     "Plots the coefficients from model objects.  This very quickly shows the user the
point estimates and confidence intervals for fitted models.")
    (license license:bsd-3)))

(define-public r-coefficientalpha
  (package
    (name "r-coefficientalpha")
    (version "0.7.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coefficientalpha" version))
       (sha256
        (base32 "0br0drapx4bw96zphnmcdwj8mw7gp0c9xm39gjmnqrvc3ycz5gh1"))))
    (properties `((upstream-name . "coefficientalpha")))
    (build-system r-build-system)
    (propagated-inputs (list r-rsem r-lavaan))
    (home-page "https://cran.r-project.org/package=coefficientalpha")
    (synopsis
     "Robust Coefficient Alpha and Omega with Missing and Non-Normal Data")
    (description
     "Cronbach's alpha and @code{McDonald's} omega are widely used reliability or
internal consistency measures in social, behavioral and education sciences.
Alpha is reported in nearly every study that involves measuring a construct
through multiple test items.  The package coefficientalpha calculates
coefficient alpha and coefficient omega with missing data and non-normal data.
Robust standard errors and confidence intervals are also provided.  A test is
also available to test the tau-equivalent and homogeneous assumptions.  Since
Version 0.5, the bootstrap confidence intervals were added.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-coefa
  (package
    (name "r-coefa")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coefa" version))
       (sha256
        (base32 "0ra9w4mpxwvi5byys45sw1yydf28hvhgp81928ipdra277flhcp9"))))
    (properties `((upstream-name . "coefa")))
    (build-system r-build-system)
    (propagated-inputs (list r-purrr r-psych r-openxlsx))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=coefa")
    (synopsis
     "Meta Analysis of Factor Analysis Based on CO-Occurrence Matrices")
    (description
     "Provide a series of functions to conduct a meta analysis of factor analysis
based on co-occurrence matrices.  The tool can be used to solve the factor
structure (i.e.  inner structure of a construct, or scale) debate in several
disciplines, such as psychology, psychiatry, management, education so on.
References: Shafer (2005) <doi:10.1037/1040-3590.17.3.324>; Shafer (2006)
<doi:10.1002/jclp.20213>; Loeber and Schmaling (1985) <doi:10.1007/BF00910652>.")
    (license license:gpl3+)))

(define-public r-codyn
  (package
    (name "r-codyn")
    (version "2.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codyn" version))
       (sha256
        (base32 "1iqlh3ydnqi7s2b3fa2zgb05j763qgxriys4piawwmgrdrvd3d9q"))))
    (properties `((upstream-name . "codyn")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan r-permute r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/NCEAS/codyn/")
    (synopsis "Community Dynamics Metrics")
    (description
     "Univariate and multivariate temporal and spatial diversity indices, rank
abundance curves, and community stability measures.  The functions implement
measures that are either explicitly temporal and include the option to calculate
them over multiple replicates, or spatial and include the option to calculate
them over multiple time points.  Functions fall into five categories: static
diversity indices, temporal diversity indices, spatial diversity indices, rank
abundance curves, and community stability measures.  The diversity indices are
temporal and spatial analogs to traditional diversity indices.  Specifically,
the package includes functions to calculate community richness, evenness and
diversity at a given point in space and time.  In addition, it contains
functions to calculate species turnover, mean rank shifts, and lags in community
similarity between two time points.  Details of the methods are available in
Hallett et al. (2016) <doi:10.1111/2041-210X.12569> and Avolio et al. (2019)
<doi:10.1002/ecs2.2881>.")
    (license license:asl2.0)))

(define-public r-codingmatrices
  (package
    (name "r-codingmatrices")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codingMatrices" version))
       (sha256
        (base32 "0554jbwy2hzdqy4vf4y26jniw8pp8j7a7ybq9s7120zfkxihccag"))))
    (properties `((upstream-name . "codingMatrices")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-fractional))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=codingMatrices")
    (synopsis "Alternative Factor Coding Matrices for Linear Model Formulae")
    (description
     "This package provides a collection of coding functions as alternatives to the
standard functions in the stats package, which have names starting with contr.'.
 Their main advantage is that they provide a consistent method for defining
marginal effects in factorial models.  In a simple one-way ANOVA model the
intercept term is always the simple average of the class means.")
    (license license:gpl2+)))

(define-public r-codina
  (package
    (name "r-codina")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoDiNA" version))
       (sha256
        (base32 "1zjj86z8ica9j0x2nfyq9y6nyp54w07dwskcsg7z6kqibrkfvaq9"))))
    (properties `((upstream-name . "CoDiNA")))
    (build-system r-build-system)
    (propagated-inputs (list r-visnetwork
                             r-reshape2
                             r-plyr
                             r-magrittr
                             r-igraph
                             r-data-table))
    (home-page "https://cran.r-project.org/package=CoDiNA")
    (synopsis "Co-Expression Differential Network Analysis")
    (description
     "Categorize links and nodes from multiple networks in 3 categories: Common links
(alpha) specific links (gamma), and different links (beta).  Also categorizes
the links into sub-categories and groups.  The package includes a visualization
tool for the networks.  More information about the methodology can be found at:
Gysi et.  al., 2018 <@code{arXiv:1802.00828>}.")
    (license license:gpl2)))

(define-public r-codified
  (package
    (name "r-codified")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codified" version))
       (sha256
        (base32 "0a5k0zqw1dxa3v1hzh3s43zlpyzpgxnbq2rhz8kq0g8lxqlki3pc"))))
    (properties `((upstream-name . "codified")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-rlang
                             r-knitr
                             r-kableextra
                             r-dplyr
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://ouhscbbmc.github.io/codified/")
    (synopsis "Produce Standard/Formalized Demographics Tables")
    (description
     "Augment clinical data with metadata to create output used in conventional
publications and reports.")
    (license license:expat)))

(define-public r-codez
  (package
    (name "r-codez")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codez" version))
       (sha256
        (base32 "1a25k7y59fflzkk95s5b9hr0nw69lnw3vlwv7sy8zj0w0b1n08ic"))))
    (properties `((upstream-name . "codez")))
    (build-system r-build-system)
    (propagated-inputs (list r-tictoc
                             r-tensorflow
                             r-scales
                             r-readr
                             r-purrr
                             r-philentropy
                             r-narray
                             r-moments
                             r-modeest
                             r-lubridate
                             r-keras
                             r-imputets
                             r-greybox
                             r-ggplot2
                             r-fastdummies
                             r-fancova
                             r-entropy
                             r-abind))
    (home-page "https://rpubs.com/giancarlo_vercellino/codez")
    (synopsis
     "Seq2Seq Encoder-Decoder Model for Time-Feature Analysis Based on Tensorflow")
    (description
     "Proposes Seq2seq Time-Feature Analysis using an Encoder-Decoder to project into
latent space and a Forward Network to predict the next sequence.")
    (license license:gpl3)))

(define-public r-codexcopd
  (package
    (name "r-codexcopd")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codexcopd" version))
       (sha256
        (base32 "0pkl29fybflnj42xj8agyw6s3xif9vr5690vlkv5n3dxs8ji582h"))))
    (properties `((upstream-name . "codexcopd")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=codexcopd")
    (synopsis
     "The CODEX (Comorbidity, Obstruction, Dyspnea, and Previous Severe Exacerbations) Index: Short and Medium-Term Prognosis in Patients Hospitalized for Chronic Obstructive Pulmonary Disease (COPD) Exacerbations")
    (description
     "Predicts 3 to 12 months prognosis in Chronic Obstructive Pulmonary Disease
(COPD) patients hospitalized for severe exacerbations, as described in Almagro
et al. (2014) <doi:10.1378/chest.13-1328>.")
    (license license:gpl3)))

(define-public r-codewhere
  (package
    (name "r-codewhere")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codewhere" version))
       (sha256
        (base32 "19biqcmjjly29vh5zn0ak6gz40857xb799fz344xz1vxwv420mp2"))))
    (properties `((upstream-name . "codewhere")))
    (build-system r-build-system)
    (propagated-inputs (list r-httr))
    (home-page "https://thisisnic.github.io/codewhere/")
    (synopsis "Find the Location of an R Package's Code")
    (description
     "Find the location of the code for an R package based on the package's name or
string representation.  Checks on CRAN based on information in the URL field or
@code{BioConductor} and @code{GitHub} based on constructing a URL, and verifies
all paths via testing for a successful response.  This can be useful when
automating static code analysis based on a list of package names, and similar
tasks.")
    (license license:expat)))

(define-public r-coder
  (package
    (name "r-coder")
    (version "0.13.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coder" version))
       (sha256
        (base32 "11vdw6aa977y05vlvqcm636j2c2kgii3w8dv4f2wk9c6l8hjhbg4"))))
    (properties `((upstream-name . "coder")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-generics r-decoder r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/coder/")
    (synopsis
     "Deterministic Categorization of Items Based on External Code Data")
    (description
     "Fast categorization of items based on external code data identified by regular
expressions.  A typical use case considers patient with medically coded data,
such as codes from the International Classification of Diseases ('ICD') or the
Anatomic Therapeutic Chemical ('ATC') classification system.  Functions of the
package relies on a triad of objects: (1) case data with unit id:s and possible
dates of interest; (2) external code data for corresponding units in (1) and
with optional dates of interest and; (3) a classification scheme ('classcodes
object) with regular expressions to identify and categorize relevant codes from
(2).  It is easy to introduce new classification schemes ('classcodes objects)
or to use default schemes included in the package.  Use cases includes patient
categorization based on comorbidity indices such as Charlson', Elixhauser',
@code{RxRisk} V', or the comorbidity-polypharmacy score (CPS), as well as
adverse events after hip and knee replacement surgery.")
    (license license:gpl2)))

(define-public r-codep
  (package
    (name "r-codep")
    (version "1.2-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codep" version))
       (sha256
        (base32 "04i31h2qf5yvh593vr1fdi9yymldby7g2mmz6vc0ww2rlhwq6bzd"))))
    (properties `((upstream-name . "codep")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=codep")
    (synopsis "Multiscale Codependence Analysis")
    (description
     "Computation of Multiscale Codependence Analysis and spatial eigenvector maps.")
    (license license:gpl3)))

(define-public r-codename
  (package
    (name "r-codename")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codename" version))
       (sha256
        (base32 "1466zby3yiggvqiwynyvirifi30y9lwms0a4mx73c8x9wfy36px0"))))
    (properties `((upstream-name . "codename")))
    (build-system r-build-system)
    (home-page "https://github.com/svmiller/codename")
    (synopsis
     "Generation of Code Names for Organizations, People, Projects, and Whatever Else")
    (description
     "This creates code names that a user can consider for their organizations, their
projects, themselves, people in their organizations or projects, or whatever
else.  The user can also supply a numeric seed (and even a character seed) for
maximum reproducibility.  Use is simple and the code names produced come in
various types too, contingent on what the user may be desiring as a code name or
nickname.")
    (license license:gpl2)))

(define-public r-codemetar
  (package
    (name "r-codemetar")
    (version "0.3.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codemetar" version))
       (sha256
        (base32 "0py4qn9148xlc1ldlifpm7vd7l9dih4f7yiadvmz57b3y2vr0b02"))))
    (properties `((upstream-name . "codemetar")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-urltools
                             r-sessioninfo
                             r-remotes
                             r-purrr
                             r-pingr
                             r-memoise
                             r-magrittr
                             r-jsonlite
                             r-gh
                             r-gert
                             r-desc
                             r-crul
                             r-commonmark
                             r-codemeta
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ropensci/codemetar")
    (synopsis "Generate 'CodeMeta' Metadata for R Packages")
    (description
     "The Codemeta Project defines a JSON-LD format for describing software metadata,
as detailed at <https://codemeta.github.io>.  This package provides utilities to
generate, parse, and modify codemeta.json files automatically for R packages, as
well as tools and examples for working with codemeta.json JSON-LD more
generally.")
    (license license:gpl3)))

(define-public r-codemeta
  (package
    (name "r-codemeta")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codemeta" version))
       (sha256
        (base32 "0pcip5ycgkva5pg20fcc3vsb09dv4j57yqvbf5x8bdsxa5vpg11a"))))
    (properties `((upstream-name . "codemeta")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-desc))
    (home-page "https://github.com/cboettig/codemeta")
    (synopsis "Smaller 'codemetar' Package")
    (description
     "The Codemeta Project defines a JSON-LD format for describing software metadata,
as detailed at <https://codemeta.github.io>.  This package provides core
utilities to generate this metadata with a minimum of dependencies.")
    (license license:gpl3)))

(define-public r-codelistgenerator
  (package
    (name "r-codelistgenerator")
    (version "3.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CodelistGenerator" version))
       (sha256
        (base32 "08hlz46s90qv8nj55a1z3rn0x6xpa7fsf2i22n4vyj7n21vxh43g"))))
    (properties `((upstream-name . "CodelistGenerator")))
    (build-system r-build-system)
    (propagated-inputs (list r-visomopresults
                             r-vctrs
                             r-tidyselect
                             r-tidyr
                             r-stringr
                             r-rlang
                             r-rjsonio
                             r-purrr
                             r-patientprofiles
                             r-omopgenerics
                             r-magrittr
                             r-lubridate
                             r-lifecycle
                             r-glue
                             r-dplyr
                             r-dbi
                             r-cli
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://darwin-eu.github.io/CodelistGenerator/")
    (synopsis "Identify Relevant Clinical Codes and Evaluate Their Use")
    (description
     "Generate a candidate code list for the Observational Medical Outcomes
Partnership (OMOP) common data model based on string matching.  For a given
search strategy, a candidate code list will be returned.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-codecountr
  (package
    (name "r-codecountr")
    (version "0.0.4.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codecountR" version))
       (sha256
        (base32 "1vhmgnhhpf409gy1db4n5hsvgcmbdamp7mzcvn6b85imf6wlk60y"))))
    (properties `((upstream-name . "codecountR")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=codecountR")
    (synopsis "Counting Codes in a Text and Preparing Data for Analysis")
    (description
     "Data analysis often requires coding, especially when data are collected through
interviews, observations, or questionnaires.  As a result, code counting and
data preparation are essential steps in the analysis process.  Analysts may need
to count the codes in a text (tokenization and counting of pre-established
codes) and prepare the data (e.g., min-max normalization, Z-score, robust
scaling, Box-Cox transformation, and non-parametric bootstrap).  For the Box-Cox
transformation (Box & Cox, 1964, <https://www.jstor.org/stable/2984418>), the
optimal Lambda is determined using the log-likelihood method.  Non-parametric
bootstrap involves randomly sampling data with replacement.  Two random number
generators are also integrated: a Lehmer congruential generator for uniform
distribution and a Box-Muller generator for normal distribution.  Package for
educational purposes.")
    (license license:gpl3)))

(define-public r-codecollection
  (package
    (name "r-codecollection")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codeCollection" version))
       (sha256
        (base32 "1isw4h0cr6knxn4h00wpv0rzqhgrnidrs9ybppn2i5jds24awc3k"))))
    (properties `((upstream-name . "codeCollection")))
    (build-system r-build-system)
    (propagated-inputs (list r-epi))
    (home-page "https://cran.r-project.org/package=codeCollection")
    (synopsis "Collection of Codes with Labels")
    (description
     "Includes several classifications such as International Statistical
Classification of Diseases and Related Health Problems 10th Revision (ICD10),
Anatomical Therapeutic Chemical (ATC) Classification, The International
Classification of Diseases for Oncology (ICD-O-3), and International
Classification of Primary Care (ICPC).  Includes function that adds descriptive
label to code value.  Depending on classification following languages are
available: English, Finnish, Swedish, and Latin.")
    (license license:gpl2)))

(define-public r-codebreaker
  (package
    (name "r-codebreaker")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codebreaker" version))
       (sha256
        (base32 "1k2l2gpcnlg77sb05zyg64w1nzvwn3j7jv5wwsyyjrlkr60kpval"))))
    (properties `((upstream-name . "codebreaker")))
    (build-system r-build-system)
    (propagated-inputs (list r-cli r-beepr))
    (home-page "https://github.com/rolkra/codebreaker")
    (synopsis "Retro Logic Game")
    (description
     "Logic game in the style of the early 1980s home computers that can be played in
the R console.  This game is inspired by Mastermind, a game that became popular
in the 1970s.  Can you break the code?")
    (license license:gpl3)))

(define-public r-codebookr
  (package
    (name "r-codebookr")
    (version "0.1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codebookr" version))
       (sha256
        (base32 "1y5daii4qms0sj0mqa0lrxfqagxbmd7wc94j8h33szmip7ivqp6v"))))
    (properties `((upstream-name . "codebookr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-purrr
                             r-officer
                             r-haven
                             r-flextable
                             r-dplyr))
    (home-page "https://github.com/brad-cannell/codebookr")
    (synopsis "Create Codebooks from Data Frames")
    (description
     "Quickly and easily create codebooks (i.e.  data dictionaries) directly from a
data frame.")
    (license license:expat)))

(define-public r-codebook
  (package
    (name "r-codebook")
    (version "0.9.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codebook" version))
       (sha256
        (base32 "1jh5qm2qzsvs9pzb67c3z0v5shdzhmqklzp7a9zq9izr9385ilmy"))))
    (properties `((upstream-name . "codebook")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-skimr
                             r-rmdpartials
                             r-rlang
                             r-purrr
                             r-likert
                             r-labelled
                             r-labeling
                             r-knitr
                             r-jsonlite
                             r-htmltools
                             r-haven
                             r-glue
                             r-ggplot2
                             r-future
                             r-forcats
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://rubenarslan.github.io/codebook/")
    (synopsis
     "Automatic Codebooks from Metadata Encoded in Dataset Attributes")
    (description
     "Easily automate the following tasks to describe data frames: Summarise the
distributions, and labelled missings of variables graphically and using
descriptive statistics.  For surveys, compute and summarise reliabilities
(internal consistencies, retest, multilevel) for psychological scales.  Combine
this information with metadata (such as item labels and labelled values) that is
derived from R attributes.  To do so, the package relies on rmarkdown partials,
so you can generate HTML, PDF, and Word documents.  Codebooks are also available
as tables (CSV, Excel, etc.) and in JSON-LD, so that search engines can find
your data and index the metadata.  The metadata are also available at your
fingertips via RStudio Addins.")
    (license license:expat)))

(define-public r-code
  (package
    (name "r-code")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cOde" version))
       (sha256
        (base32 "1h3bp97lqd1jvgnablhxdncmvbf5qwphqbs7xy3r31vpamslz77i"))))
    (properties `((upstream-name . "cOde")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cOde")
    (synopsis "Automated C Code Generation for 'deSolve', 'bvpSolve'")
    (description
     "Generates all necessary C functions allowing the user to work with the
compiled-code interface of ode() and bvptwp().  The implementation supports
\"forcings\" and \"events\".  Also provides functions to symbolically compute
Jacobians, sensitivity equations and adjoint sensitivities being the basis for
sensitivity analysis.")
    (license license:gpl2+)))

(define-public r-codatags
  (package
    (name "r-codatags")
    (version "1.43")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CodataGS" version))
       (sha256
        (base32 "1bjn6s1f5jn64gwrvjz5kvwfkbqrqhavib6dj9k37rb5nzqkwhp6"))))
    (properties `((upstream-name . "CodataGS")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix))
    (home-page "https://cran.r-project.org/package=CodataGS")
    (synopsis "Genomic Prediction Using SNP Codata")
    (description
     "Computes genomic breeding values using external information on the markers.  The
package fits a linear mixed model with heteroscedastic random effects, where the
random effect variance is fitted using a linear predictor and a log link.  The
method is described in Mouresan, Selle and Ronnegard (2019)
<doi:10.1101/636746>.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-codaredistlm
  (package
    (name "r-codaredistlm")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codaredistlm" version))
       (sha256
        (base32 "1i046kxf71yvgqychj6a3lqrdsgcfhgz1i02mm91ih5nrg2613rg"))))
    (properties `((upstream-name . "codaredistlm")))
    (build-system r-build-system)
    (propagated-inputs (list r-knitr r-ggplot2 r-compositions r-broom))
    (home-page "https://github.com/tystan/codaredistlm")
    (synopsis
     "Compositional Data Linear Models with Composition Redistribution")
    (description
     "Provided data containing an outcome variable, compositional variables and
additional covariates (optional); linearly regress the outcome variable on an
isometric log ratio (ilr) transformation of the linearly dependent compositional
variables.  The package provides predictions (with confidence intervals) in the
change (delta) in the outcome/response variable based on the multiple linear
regression model and evenly spaced reallocations of the compositional values.
The compositional data analysis approach implemented is outlined in Dumuid et
al. (2017a) <doi:10.1177/0962280217710835> and Dumuid et al. (2017b)
<doi:10.1177/0962280217737805>.")
    (license license:gpl2)))

(define-public r-codalm
  (package
    (name "r-codalm")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codalm" version))
       (sha256
        (base32 "09q7i96wga55xl8wwkb4i2sisn97wd21zqpmasykpi1aamzysqki"))))
    (properties `((upstream-name . "codalm")))
    (build-system r-build-system)
    (propagated-inputs (list r-squarem r-future-apply r-future))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jfiksel/codalm")
    (synopsis
     "Transformation-Free Linear Regression for Compositional Outcomes and Predictors")
    (description
     "This package implements the expectation-maximization (EM) algorithm as described
in Fiksel et al. (2021) <doi:10.1111/biom.13465> for transformation-free linear
regression for compositional outcomes and predictors.")
    (license license:gpl2)))

(define-public r-codaimpact
  (package
    (name "r-codaimpact")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoDaImpact" version))
       (sha256
        (base32 "0hc76s7k3i8mjq0q0yg9fn6vv7xd7w2j1hym23rkpn6gxjl522jx"))))
    (properties `((upstream-name . "CoDaImpact")))
    (build-system r-build-system)
    (propagated-inputs (list r-compositions))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/LukeCe/CoDaImpact")
    (synopsis "Interpreting CoDa Regression Models")
    (description
     "This package provides methods for interpreting @code{CoDa} (Compositional Data)
regression models along the lines of \"Pairwise share ratio interpretations of
compositional regression models\" (Dargel and Thomas-Agnan 2024)
<doi:10.1016/j.csda.2024.107945>.  The new methods include variation scenarios,
elasticities, elasticity differences and share ratio elasticities.  These tools
are independent of log-ratio transformations and allow an interpretation in the
original space of shares. @code{CoDaImpact} is designed to be used with the
compositions package and its ecosystem.")
    (license license:gpl3+)))

(define-public r-codacore
  (package
    (name "r-codacore")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "codacore" version))
       (sha256
        (base32 "047klw705a4x0b93xvwd6839j30gg9jl1dgwdnkcqjiwn9jx8fb3"))))
    (properties `((upstream-name . "codacore")))
    (build-system r-build-system)
    (inputs (list tensorflow))
    (propagated-inputs (list r-tensorflow r-r6 r-proc r-keras r-gtools))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=codacore")
    (synopsis "Learning Sparse Log-Ratios for Compositional Data")
    (description
     "In the context of high-throughput genetic data, @code{CoDaCoRe} identifies a set
of sparse biomarkers that are predictive of a response variable of interest
(Gordon-Rodriguez et al., 2021) <doi:10.1093/bioinformatics/btab645>.  More
generally, @code{CoDaCoRe} can be applied to any regression problem where the
independent variable is Compositional (@code{CoDa}), to derive a set of
scale-invariant log-ratios (ILR or SLR) that are maximally associated to a
dependent variable.")
    (license license:expat)))

(define-public r-coda4microbiome
  (package
    (name "r-coda4microbiome")
    (version "0.2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coda4microbiome" version))
       (sha256
        (base32 "1gslvlhnps5ibrcgm6b487ii9z4blk92mnp26z4xb7m23l7349c1"))))
    (properties `((upstream-name . "coda4microbiome")))
    (build-system r-build-system)
    (propagated-inputs (list r-survminer
                             r-survival
                             r-proc
                             r-plyr
                             r-glmnet
                             r-ggpubr
                             r-ggplot2
                             r-corrplot
                             r-complexheatmap
                             r-circlize))
    (home-page "https://malucalle.github.io/coda4microbiome/")
    (synopsis "Compositional Data Analysis for Microbiome Studies")
    (description
     "This package provides functions for microbiome data analysis that take into
account its compositional nature.  Performs variable selection through penalized
regression for both, cross-sectional and longitudinal studies, and for binary
and continuous outcomes.")
    (license license:expat)))

(define-public r-coda-base
  (package
    (name "r-coda-base")
    (version "0.5.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coda.base" version))
       (sha256
        (base32 "1jjg0akvi9srdwnk1xibf7lr8vp776xy8ai71g7y15vrbmzyqkfb"))))
    (properties `((upstream-name . "coda.base")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-matrix))
    (native-inputs (list r-knitr))
    (home-page "https://mcomas.net/coda.base/")
    (synopsis "Basic Set of Functions for Compositional Data Analysis")
    (description
     "This package provides a minimum set of functions to perform compositional data
analysis using the log-ratio approach introduced by John Aitchison (1982).  Main
functions have been implemented in c++ for better performance.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-cocron
  (package
    (name "r-cocron")
    (version "1.0-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cocron" version))
       (sha256
        (base32 "0dl14y9v9kndy5gzhhbhq3f31ja724y1hra40givy6bij7h2cj30"))))
    (properties `((upstream-name . "cocron")))
    (build-system r-build-system)
    (home-page "http://comparingcronbachalphas.org")
    (synopsis "Statistical Comparisons of Two or more Alpha Coefficients")
    (description
     "Statistical tests for the comparison between two or more alpha coefficients
based on either dependent or independent groups of individuals.  A web interface
is available at http://comparingcronbachalphas.org.  A plugin for the R GUI and
IDE RKWard is included.  Please install RKWard from https:// rkward.kde.org to
use this feature.  The respective R package rkward cannot be installed directly
from a repository, as it is a part of RKWard.")
    (license license:gpl3+)))

(define-public r-cocotest
  (package
    (name "r-cocotest")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cocotest" version))
       (sha256
        (base32 "0dvdbm4gi7mx0ayjdh75s1vh97fpwnz0qwh5yln6nzppc62qsflj"))))
    (properties `((upstream-name . "cocotest")))
    (build-system r-build-system)
    (propagated-inputs (list r-boot))
    (home-page "https://cran.r-project.org/package=cocotest")
    (synopsis
     "Dependence Condition Test Using Ranked Correlation Coefficients")
    (description
     "This package provides a common misconception is that the Hochberg procedure
comes up with adequate overall type I error control when test statistics are
positively correlated.  However, unless the test statistics follow some standard
distributions, the Hochberg procedure requires a more stringent positive
dependence assumption, beyond mere positive correlation, to ensure valid overall
type I error control.  To fill this gap, we formulate statistical tests grounded
in rank correlation coefficients to validate fulfillment of the positive
dependence through stochastic ordering (PDS) condition.  See Gou, J., Wu, K. and
Chen, O. Y. (2024).  Rank correlation coefficient based tests on positive
dependence through stochastic ordering with application in cancer studies,
Technical Report.")
    (license license:gpl3)))

(define-public r-cocosor
  (package
    (name "r-cocosor")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cocosoR" version))
       (sha256
        (base32 "0aywv3r1kcqiy3bnmvl6djhngzhyvg1f62fldwpz9plxmhphiwdp"))))
    (properties `((upstream-name . "cocosoR")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cocosoR")
    (synopsis "CoCoSo - Combined Compromise Solution Method for MCDA")
    (description
     "This package provides a set of functions to implement the Combined Compromise
Solution (@code{CoCoSo}) Method created by Yazdani, Zarate, Zavadskas and
Turskis (2019) <doi:10.1108/MD-05-2017-0458>.  This method is based on an
integrated simple additive weighting and compromise exponentially weighted
product model.")
    (license license:gpl3+)))

(define-public r-cocorresp
  (package
    (name "r-cocorresp")
    (version "0.4-5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cocorresp" version))
       (sha256
        (base32 "02qzcaf9i55ncr71l9iapzdziqd76s9hljvn819kpvgscdhxdfhn"))))
    (properties `((upstream-name . "cocorresp")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan))
    (native-inputs (list r-knitr))
    (home-page "https://gavinsimpson.github.io/cocorresp/")
    (synopsis "Co-Correspondence Analysis Methods")
    (description
     "Fits predictive and symmetric co-correspondence analysis (@code{CoCA}) models to
relate one data matrix to another data matrix.  More specifically, @code{CoCA}
maximises the weighted covariance between the weighted averaged species scores
of one community and the weighted averaged species scores of another community.
@code{CoCA} attempts to find patterns that are common to both communities.")
    (license license:gpl2)))

(define-public r-cocor
  (package
    (name "r-cocor")
    (version "1.1-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cocor" version))
       (sha256
        (base32 "05hl8nlxzimas36cm5b0k7fbjz69ijif7li8kgnpaxk4zmgvzy18"))))
    (properties `((upstream-name . "cocor")))
    (build-system r-build-system)
    (home-page "http://comparingcorrelations.org")
    (synopsis "Comparing Correlations")
    (description
     "Statistical tests for the comparison between two correlations based on either
independent or dependent groups.  Dependent correlations can either be
overlapping or nonoverlapping.  A web interface is available on the website
<http://comparingcorrelations.org>.  A plugin for the R GUI and IDE RKWard is
included.  Please install RKWard from <https://rkward.kde.org> to use this
feature.  The respective R package rkward cannot be installed directly from a
repository, as it is a part of RKWard.")
    (license license:gpl3+)))

(define-public r-coconut
  (package
    (name "r-coconut")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "COCONUT" version))
       (sha256
        (base32 "1qjrhxn6dkxyimdca3nslaiw3hncfpk1pk4v01mcrnz550z001nz"))))
    (properties `((upstream-name . "COCONUT")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=COCONUT")
    (synopsis "COmbat CO-Normalization Using conTrols (COCONUT)")
    (description
     "Allows for pooled analysis of microarray data by batch-correcting control
samples, and then applying the derived correction parameters to non-control
samples to obtain bias-free, inter-dataset corrected data.")
    (license license:gpl3)))

(define-public r-cocons
  (package
    (name "r-cocons")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cocons" version))
       (sha256
        (base32 "164iw0hs6l2i6z2lbar0m8szshgfg0lq7daax0zl3fyhmxcmzyrw"))))
    (properties `((upstream-name . "cocons")))
    (build-system r-build-system)
    (propagated-inputs (list r-spam
                             r-rcpp
                             r-optimparallel
                             r-knitr
                             r-fields
                             r-bh))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cocons")
    (synopsis
     "Covariate-Based Covariance Functions for Nonstationary Spatial Modeling")
    (description
     "Estimation, prediction, and simulation of nonstationary Gaussian process with
modular covariate-based covariance functions.  Sources of nonstationarity, such
as trend, variance, geometric anisotropy, smoothness, and nugget, can be
considered based on spatial characteristics.  An induced compact-supported
nonstationary covariance function is provided, enabling fast and
memory-efficient computations when handling densely sampled domains.")
    (license license:gpl3+)))

(define-public r-coconots
  (package
    (name "r-coconots")
    (version "1.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coconots" version))
       (sha256
        (base32 "1mymq7rsmawnh6m3m7c39kg8mp829f7kyjnj3hll4jsw6q1sz2fi"))))
    (properties `((upstream-name . "coconots")))
    (build-system r-build-system)
    (propagated-inputs (list r-stanheaders
                             r-rcppparallel
                             r-rcpp
                             r-numderiv
                             r-matrixstats
                             r-juliaconnector
                             r-hmmpa
                             r-ggplot2
                             r-forecast))
    (home-page "https://cran.r-project.org/package=coconots")
    (synopsis "Convolution-Closed Models for Count Time Series")
    (description
     "Useful tools for fitting, validating, and forecasting of practical
convolution-closed time series models for low counts are provided.  Marginal
distributions of the data can be modeled via Poisson and Generalized Poisson
innovations.  Regression effects can be modelled via time varying innovation
rates.  The models are described in Jung and Tremayne (2011)
<doi:10.1111/j.1467-9892.2010.00697.x> and the model assessment tools are
presented in Czado et al. (2009) <doi:10.1111/j.1541-0420.2009.01191.x>,
Gneiting and Raftery (2007) <doi:10.1198/016214506000001437> and, Tsay (1992)
<doi:10.2307/2347612>.")
    (license license:expat)))

(define-public r-coclust
  (package
    (name "r-coclust")
    (version "0.3-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoClust" version))
       (sha256
        (base32 "04xv807785xv9kdspsspx1302ardv8gda06kd590lgawjixai7dh"))))
    (properties `((upstream-name . "CoClust")))
    (build-system r-build-system)
    (propagated-inputs (list r-gtools r-copula))
    (home-page "https://cran.r-project.org/package=CoClust")
    (synopsis "Copula Based Cluster Analysis")
    (description
     "This package provides a copula based clustering algorithm that finds clusters
according to the complex multivariate dependence structure of the data
generating process.  The updated version of the algorithm is described in Di
Lascio, F.M.L. and Giannerini, S. (2016). \"Clustering dependent observations
with copula functions\".  Statistical Papers, p.1-17.
<doi:10.1007/s00362-016-0822-3>.")
    (license license:gpl2+)))

(define-public r-cocktailapp
  (package
    (name "r-cocktailapp")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cocktailApp" version))
       (sha256
        (base32 "134y64z297r6fqiakqa42f15i5sxlaczc9adxrkicq9275kjf2fn"))))
    (properties `((upstream-name . "cocktailApp")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-shinythemes
                             r-shiny
                             r-magrittr
                             r-ggtern
                             r-ggplot2
                             r-forcats
                             r-dt
                             r-dplyr))
    (home-page "https://github.com/shabbychef/cocktailApp")
    (synopsis "'shiny' App to Discover Cocktails")
    (description
     "This package provides a shiny app to discover cocktails.  The app allows one to
search for cocktails by ingredient, filter on rating, and number of ingredients.
 The package also contains data with the ingredients of nearly 26 thousand
cocktails scraped from the web.")
    (license license:lgpl3)))

(define-public r-coca
  (package
    (name "r-coca")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coca" version))
       (sha256
        (base32 "1lh7q3ip1jaz5zj5zcnd5whwpjw6zcrxs6j0j8mnmjsnw2kr4m5n"))))
    (properties `((upstream-name . "coca")))
    (build-system r-build-system)
    (propagated-inputs (list r-sparcl
                             r-rcolorbrewer
                             r-pheatmap
                             r-nnet
                             r-matrix
                             r-glmnet
                             r-fpc
                             r-cluster
                             r-caret))
    (native-inputs (list r-knitr))
    (home-page "http://github.com/acabassi/coca")
    (synopsis "Cluster-of-Clusters Analysis")
    (description
     "This package contains the R functions needed to perform Cluster-Of-Clusters
Analysis (COCA) and Consensus Clustering (CC).  For further details please see
Cabassi and Kirk (2020) <doi:10.1093/bioinformatics/btaa593>.")
    (license license:expat)))

(define-public r-cobiclust
  (package
    (name "r-cobiclust")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cobiclust" version))
       (sha256
        (base32 "04vwf3gawc02czqa3zk5lfklrqivsqlhbvfa2drsysbipy933zny"))))
    (properties `((upstream-name . "cobiclust")))
    (build-system r-build-system)
    (propagated-inputs (list r-testthat r-cluster r-assertthat))
    (home-page "https://github.com/julieaubert/cobiclust")
    (synopsis
     "Biclustering via Latent Block Model Adapted to Overdispersed Count Data")
    (description
     "Implementation of a probabilistic method for biclustering adapted to
overdispersed count data.  It is a Gamma-Poisson Latent Block Model.  It also
implements two selection criteria in order to select the number of biclusters.")
    (license license:gpl3)))

(define-public r-cobalt
  (package
    (name "r-cobalt")
    (version "4.5.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cobalt" version))
       (sha256
        (base32 "1h1fyv2x4wjvwqjxh0hdvh1y355jbkq7n8n6bbnkskd2w5b1jv07"))))
    (properties `((upstream-name . "cobalt")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-gtable
                             r-gridextra
                             r-ggplot2
                             r-crayon
                             r-chk
                             r-backports))
    (native-inputs (list r-knitr))
    (home-page "https://ngreifer.github.io/cobalt/")
    (synopsis "Covariate Balance Tables and Plots")
    (description
     "Generate balance tables and plots for covariates of groups preprocessed through
matching, weighting or subclassification, for example, using propensity scores.
Includes integration with @code{MatchIt}', @code{WeightIt}', @code{MatchThem}',
twang', Matching', optmatch', CBPS', ebal', cem', sbw', and designmatch for
assessing balance on the output of their preprocessing functions.  Users can
also specify data for balance assessment not generated through the above
packages.  Also included are methods for assessing balance in clustered or
multiply imputed data sets or data sets with multi-category, continuous, or
longitudinal treatments.")
    (license license:gpl2+)))

(define-public r-coat
  (package
    (name "r-coat")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coat" version))
       (sha256
        (base32 "01sfssvb20rnjx6vpgyglj96wysr9v00n7fa8mg9l65cgv32dvgc"))))
    (properties `((upstream-name . "coat")))
    (build-system r-build-system)
    (propagated-inputs (list r-partykit r-gridextra r-ggtext r-ggplot2
                             r-ggparty))
    (home-page "https://cran.r-project.org/package=coat")
    (synopsis "Conditional Method Agreement Trees (COAT)")
    (description
     "Agreement of continuously scaled measurements made by two techniques, devices or
methods is usually evaluated by the well-established Bland-Altman analysis or
plot.  Conditional method agreement trees (COAT), proposed by Karapetyan,
Zeileis, Henriksen, and Hapfelmeier (2023)
<doi:10.48550/@code{arXiv.2306.04456>}, embed the Bland-Altman analysis in the
framework of recursive partitioning to explore heterogeneous method agreement in
dependence of covariates.  COAT can also be used to perform a Bland-Altman test
for differences in method agreement.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-coastlinefd
  (package
    (name "r-coastlinefd")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CoastlineFD" version))
       (sha256
        (base32 "1l6igxvp4sz09bbgqjn6kwddi4mciw5ihcmzlg87pqhr1zs2yjbi"))))
    (properties `((upstream-name . "CoastlineFD")))
    (build-system r-build-system)
    (propagated-inputs (list r-writexl
                             r-tidyr
                             r-sfheaders
                             r-sf
                             r-readxl
                             r-progress
                             r-ggplot2
                             r-fields))
    (home-page "https://github.com/redworld123/CoastlineFD")
    (synopsis "Calculation of the Fractal Dimension of a Coastline")
    (description
     "Calculating the fractal dimension of a coastline using the boxes and dividers
methods.")
    (license license:expat)))

(define-public r-coarsedatatools
  (package
    (name "r-coarsedatatools")
    (version "0.6-6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coarseDataTools" version))
       (sha256
        (base32 "1g9hxyp2vdhq1zr18qlf2aqwp9d9hr07k6grmvblj2xrwlzfvc1p"))))
    (properties `((upstream-name . "coarseDataTools")))
    (build-system r-build-system)
    (propagated-inputs (list r-mcmcpack))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=coarseDataTools")
    (synopsis "Analysis of Coarsely Observed Data")
    (description
     "This package provides functions to analyze coarse data.  Specifically, it
contains functions to (1) fit parametric accelerated failure time models to
interval-censored survival time data, and (2) estimate the case-fatality ratio
in scenarios with under-reporting.  This package's development was motivated by
applications to infectious disease: in particular, problems with estimating the
incubation period and the case fatality ratio of a given disease.  Sample data
files are included in the package.  See Reich et al. (2009)
<doi:10.1002/sim.3659>, Reich et al. (2012)
<doi:10.1111/j.1541-0420.2011.01709.x>, and Lessler et al. (2009)
<doi:10.1016/S1473-3099(09)70069-6>.")
    (license license:gpl2+)))

(define-public r-coap
  (package
    (name "r-coap")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "COAP" version))
       (sha256
        (base32 "1772aiy9ywvgb1k9qn41l00qhsmhxkx53mdl16ggcwq0c3gdm8ly"))))
    (properties `((upstream-name . "COAP")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-mass r-irlba))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/feiyoung/COAP")
    (synopsis
     "High-Dimensional Covariate-Augmented Overdispersed Poisson Factor Model")
    (description
     "This package provides a covariate-augmented overdispersed Poisson factor model
is proposed to jointly perform a high-dimensional Poisson factor analysis and
estimate a large coefficient matrix for overdispersed count data.  More details
can be referred to Liu et al. (2024) <doi:10.1093/biomtc/ujae031>.")
    (license license:gpl3)))

(define-public r-coalescentmcmc
  (package
    (name "r-coalescentmcmc")
    (version "0.4-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coalescentMCMC" version))
       (sha256
        (base32 "09abhcp6y98378kf018inhxpkkirch5636nskywn0p6shp2q278x"))))
    (properties `((upstream-name . "coalescentMCMC")))
    (build-system r-build-system)
    (propagated-inputs (list r-phangorn r-matrix r-lattice r-coda r-ape))
    (home-page "https://cran.r-project.org/package=coalescentMCMC")
    (synopsis "MCMC Algorithms for the Coalescent")
    (description
     "Flexible framework for coalescent analyses in R. It includes a main function
running the MCMC algorithm, auxiliary functions for tree rearrangement, and some
functions to compute population genetic parameters.  Extended description can be
found in Paradis (2020) <doi:10.1201/9780429466700>.  For details on the MCMC
algorithm, see Kuhner et al. (1995) <doi:10.1093/genetics/140.4.1421> and
Drummond et al. (2002) <doi:10.1093/genetics/161.3.1307>.")
    (license license:gpl2+)))

(define-public r-coala
  (package
    (name "r-coala")
    (version "0.7.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "coala" version))
       (sha256
        (base32 "1y736gagr1nkyxvsgkn411si6xv6w4sp8m7p20za07y4m71z900i"))))
    (properties `((upstream-name . "coala")))
    (build-system r-build-system)
    (propagated-inputs (list r-scrm
                             r-rehh
                             r-rcpparmadillo
                             r-rcpp
                             r-r6
                             r-digest
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/statgenlmu/coala")
    (synopsis "Framework for Coalescent Simulation")
    (description
     "Coalescent simulators can rapidly simulate biological sequences evolving
according to a given model of evolution.  You can use this package to specify
such models, to conduct the simulations and to calculate additional statistics
from the results (Staab, Metzler, 2016 <doi:10.1093/bioinformatics/btw098>).  It
relies on existing simulators for doing the simulation, and currently supports
the programs ms', msms and scrm'.  It also supports finite-sites mutation models
by combining the simulators with the program seq-gen'.  Coala provides functions
for calculating certain summary statistics, which can also be applied to actual
biological data.  One possibility to import data is through the @code{PopGenome}
package (<https://github.com/pievos101/@code{PopGenome>}).")
    (license license:expat)))

(define-public r-cnvscope
  (package
    (name "r-cnvscope")
    (version "3.7.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CNVScope" version))
       (sha256
        (base32 "03jkivg9jr2dpkf739cba3dsjf56gwvcpq3nqhp42kmmgn50rpiq"))))
    (properties `((upstream-name . "CNVScope")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-shiny
                             r-rtracklayer
                             r-reshape2
                             r-rcurl
                             r-plyr
                             r-openimager
                             r-matrixstats
                             r-matrix
                             r-magrittr
                             r-jointseg
                             r-hmisc
                             r-ggplot2
                             r-genomicinteractions
                             r-foreach
                             r-dplyr
                             r-doparallel
                             r-data-table
                             r-biomart))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jamesdalg/CNVScope/")
    (synopsis
     "Versatile Toolkit for Copy Number Variation Relationship Data Analysis and Visualization")
    (description
     "This package provides the ability to create interaction maps, discover CNV map
domains (edges), gene annotate interactions, and create interactive
visualizations of these CNV interaction maps.")
    (license license:bsd-3)))

(define-public r-cnvrg
  (package
    (name "r-cnvrg")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CNVRG" version))
       (sha256
        (base32 "0xr2c5yc9g8hqw5dy5k2y0pm54sdrrbafsc3cpafpwaf803vdrbk"))))
    (properties `((upstream-name . "CNVRG")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-tibble
                             r-stanheaders
                             r-rstantools
                             r-rstan
                             r-rcppparallel
                             r-rcppeigen
                             r-rcpp
                             r-bh))
    (home-page "https://cran.r-project.org/package=CNVRG")
    (synopsis "Dirichlet Multinomial Modeling of Relative Abundance Data")
    (description
     "This package implements Dirichlet multinomial modeling of relative abundance
data using functionality provided by the Stan software.  The purpose of this
package is to provide a user friendly way to interface with Stan that is
suitable for those new to modeling.  For more regarding the modeling mathematics
and computational techniques we use see our publication in Molecular Ecology
Resources titled Dirichlet multinomial modeling outperforms alternatives for
analysis of ecological count data (Harrison et al.  2020
<doi:10.1111/1755-0998.13128>).")
    (license license:gpl3)))

(define-public r-cnum
  (package
    (name "r-cnum")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cnum" version))
       (sha256
        (base32 "0iphbx5ii4ij0bi9nqdz793i4gk2164jlgz5xn8yzsayjmizhdk2"))))
    (properties `((upstream-name . "cnum")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-rcpp r-bh))
    (home-page "https://github.com/elgarteo/cnum/")
    (synopsis "Chinese Numerals Processing")
    (description
     "Chinese numerals processing in R, such as conversion between Chinese numerals
and Arabic numerals as well as detection and extraction of Chinese numerals in
character objects and string.  This package supports the casual scale naming
system and the respective SI prefix systems used in mainland China and Taiwan:
\"China Statutory Measurement Units\" State Administration for Market Regulation
(2019) <http://gkml.samr.gov.cn/nsjg/jls/201902/t20190225_291134.html> \"Names,
Definitions and Symbols of the Legal Units of Measurement and the Decimal
Multiples and Submultiples\" Ministry of Economic Affairs (2019)
<https://gazette.nat.gov.tw/@code{egFront/detail.do?metaid=108965>}.")
    (license license:expat)))

(define-public r-cnps
  (package
    (name "r-cnps")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CNPS" version))
       (sha256
        (base32 "046jd4nh54qaqm85m74nvgj6x83mf8sd76y4dxydy4ydrk4cvz6p"))))
    (properties `((upstream-name . "CNPS")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CNPS")
    (synopsis "Nonparametric Statistics")
    (description
     "We unify various nonparametric hypothesis testing problems in a framework of
permutation testing, enabling hypothesis testing on multi-sample,
multidimensional data and contingency tables.  Most of the functions available
in the R environment to implement permutation tests are single functions
constructed for specific test problems; to facilitate the use of the package,
the package encapsulates similar tests in a categorized manner, greatly
improving ease of use.  We will all provide functions for self-selected
permutation scoring methods and self-selected p-value calculation methods
(asymptotic, exact, and sampling).  For two-sample tests, we will provide mean
tests and estimate drift sizes; we will provide tests on variance; we will
provide paired-sample tests; we will provide correlation coefficient tests under
three measures.  For multi-sample problems, we will provide both ordinary and
ordered alternative test problems.  For multidimensional data, we will implement
multivariate means (including ordered alternatives) and multivariate pairwise
tests based on four statistics; the components with significant differences are
also calculated.  For contingency tables, we will perform permutation chi-square
test or ordered alternative.")
    (license license:gpl2)))

(define-public r-cnprep
  (package
    (name "r-cnprep")
    (version "2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CNprep" version))
       (sha256
        (base32 "1vfy86b5cczw0va2fkbjv9c99q1gz3sx76yra76x8sz94nhxxq4m"))))
    (properties `((upstream-name . "CNprep")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlecuyer r-mclust))
    (home-page "https://cran.r-project.org/package=CNprep")
    (synopsis
     "Pre-Process DNA Copy Number (CN) Data for Detection of CN Events")
    (description
     "DNA copy number data evaluation using both their initial form (copy number as a
noisy function of genomic position) and their approximation by a
piecewise-constant function (segmentation), for the purpose of identifying
genomic regions where the copy number differs from the norm.")
    (license license:gpl2)))

(define-public r-cnorm
  (package
    (name "r-cnorm")
    (version "3.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cNORM" version))
       (sha256
        (base32 "1wpxn4cvcaip6gs9cs59qb3fns1crfv361mx8fvxdnrsxiqbqac8"))))
    (properties `((upstream-name . "cNORM")))
    (build-system r-build-system)
    (propagated-inputs (list r-leaps r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://www.psychometrica.de/cNorm_en.html")
    (synopsis "Continuous Norming")
    (description
     "This package provides a comprehensive toolkit for generating continuous test
norms in psychometrics and biometrics, and analyzing model fit.  The package
offers both distribution-free modeling using Taylor polynomials and parametric
modeling using the beta-binomial distribution.  Originally developed for
achievement tests, it is applicable to a wide range of mental, physical, or
other test scores dependent on continuous or discrete explanatory variables.
The package provides several advantages: It minimizes deviations from
representativeness in subsamples, interpolates between discrete levels of
explanatory variables, and significantly reduces the required sample size
compared to conventional norming per age group. @code{cNORM} enables graphical
and analytical evaluation of model fit, accommodates a wide range of scales
including those with negative and descending values, and even supports
conventional norming.  It generates norm tables including confidence intervals.
It also includes methods for addressing representativeness issues through
Iterative Proportional Fitting.")
    (license license:agpl3)))

(define-public r-cnmap
  (package
    (name "r-cnmap")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cnmap" version))
       (sha256
        (base32 "17ksinswnj37sj1cdzpxg27rkn8qi4kli48hi1jk8r147d2rykdg"))))
    (properties `((upstream-name . "cnmap")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra r-sf))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/PanfengZhang/cnmap")
    (synopsis "China Map Data from AutoNavi Map")
    (description
     "According to the code or the name of the administrative division at the county
level and above provided by the Ministry of Civil Affairs of the People's
Republic of China in 2022
(<https://www.mca.gov.cn/mzsj/xzqh/2022/202201xzqh.html>), get the map file
online from the website of @code{AutoNavi} Map
(<http://datav.aliyun.com/portal/school/atlas/area_selector>).")
    (license license:gpl3)))

(define-public r-cnlttsa
  (package
    (name "r-cnlttsa")
    (version "0.1-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CNLTtsa" version))
       (sha256
        (base32 "1vy0jjg6s8yvsvkx4pin183y5bnikm5cmjcpa9znz9dj1w6hwr5r"))))
    (properties `((upstream-name . "CNLTtsa")))
    (build-system r-build-system)
    (propagated-inputs (list r-nlt r-fields r-cnltreg r-adlift))
    (home-page "https://cran.r-project.org/package=CNLTtsa")
    (synopsis
     "Complex-Valued Wavelet Lifting for Univariate and Bivariate Time Series Analysis")
    (description
     "Implementations of recent complex-valued wavelet spectral procedures for
analysis of irregularly sampled signals, see Hamilton et al (2018)
<doi:10.1080/00401706.2017.1281846>.")
    (license license:gpl2)))

(define-public r-cnltreg
  (package
    (name "r-cnltreg")
    (version "0.1-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CNLTreg" version))
       (sha256
        (base32 "07yi0ajil1113663v3gp5d3453r4l9qm442jnpydx4ygvjk7m2ha"))))
    (properties `((upstream-name . "CNLTreg")))
    (build-system r-build-system)
    (propagated-inputs (list r-nlt r-misctools r-adlift))
    (home-page "https://cran.r-project.org/package=CNLTreg")
    (synopsis "Complex-Valued Wavelet Lifting for Signal Denoising")
    (description
     "Implementations of recent complex-valued wavelet shrinkage procedures for
smoothing irregularly sampled signals, see Hamilton et al (2018)
<doi:10.1080/00401706.2017.1281846>.")
    (license license:gpl2)))

(define-public r-cnid
  (package
    (name "r-cnid")
    (version "1.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CNID" version))
       (sha256
        (base32 "0lg3lw34jcgpnp311wqpq75vb0985c1x8mvb5x3hcirsy6vlq8v8"))))
    (properties `((upstream-name . "CNID")))
    (build-system r-build-system)
    (home-page "https://gitlab.com/chuxinyuan/cnid")
    (synopsis "Get Basic Information from Chinese ID Number")
    (description
     "The Chinese ID number contains a lot of information, this package helps you get
the date of birth, age, age based on year, gender, region, zodiac, constellation
information from the Chinese ID number.")
    (license license:expat)))

(define-public r-cncagui
  (package
    (name "r-cncagui")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cncaGUI" version))
       (sha256
        (base32 "0wmapwfag2grshmdrpmlinzikrsprcc8a1afq4dfkwr54rb3m6ky"))))
    (properties `((upstream-name . "cncaGUI")))
    (build-system r-build-system)
    (propagated-inputs (list r-tkrplot
                             r-tcltk2
                             r-shapes
                             r-rgl
                             r-plotrix
                             r-mass))
    (home-page "https://cran.r-project.org/package=cncaGUI")
    (synopsis "Canonical Non-Symmetrical Correspondence Analysis in R")
    (description
     "This package provides a GUI with which users can construct and interact with
Canonical Correspondence Analysis and Canonical Non-Symmetrical Correspondence
Analysis and provides inferential results by using Bootstrap Methods.")
    (license license:gpl2+)))

(define-public r-cnbdistr
  (package
    (name "r-cnbdistr")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cnbdistr" version))
       (sha256
        (base32 "05qi41jimslbngjgbwzfda0q25hb28ax79v9yckvrbpgjc8dk990"))))
    (properties `((upstream-name . "cnbdistr")))
    (build-system r-build-system)
    (propagated-inputs (list r-hypergeo))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cnbdistr")
    (synopsis "Conditional Negative Binomial Distribution")
    (description
     "Provided R functions for working with the Conditional Negative Binomial
distribution.")
    (license license:gpl3)))

(define-public r-cnaopt
  (package
    (name "r-cnaopt")
    (version "0.5.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cnaOpt" version))
       (sha256
        (base32 "1ciqh0d88270hizlsks7d05kggaszzl6add2n143z7cswkgfvkyr"))))
    (properties `((upstream-name . "cnaOpt")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-matrixstats r-ggplot2 r-dplyr r-cna))
    (home-page "https://cran.r-project.org/package=cnaOpt")
    (synopsis
     "Optimizing Consistency and Coverage in Configurational Causal Modeling")
    (description
     "This is an add-on to the cna package <https://CRAN.R-project.org/package=cna>
comprising various functions for optimizing consistency and coverage scores of
models of configurational comparative methods as Coincidence Analysis (CNA) and
Qualitative Comparative Analysis (QCA).  The function @code{conCovOpt}()
calculates con-cov optima, @code{selectMax}() selects con-cov maxima among the
con-cov optima, DNFbuild() can be used to build models actually reaching those
optima, and @code{findOutcomes}() identifies those factor values in analyzed
data that can be modeled as outcomes.  For a theoretical introduction to these
functions see Baumgartner and Ambuehl (2021) <doi:10.1177/0049124121995554>.")
    (license license:gpl2+)))

(define-public r-cnaim
  (package
    (name "r-cnaim")
    (version "2.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CNAIM" version))
       (sha256
        (base32 "1bwjglhsv8bd58clzlsa34ag0djyim85p0ilfclx4all1ycrz1k2"))))
    (properties `((upstream-name . "CNAIM")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-r2d3
                             r-plyr
                             r-magrittr
                             r-jsonlite
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://www.cnaim.io/")
    (synopsis "Common Network Asset Indices Methodology (CNAIM)")
    (description
     "Implementation of the CNAIM standard in R. Contains a series of algorithms which
determine the probability of failure, consequences of failure and monetary risk
associated with electricity distribution companies assets such as transformers
and cables.  Results are visualized in an easy-to-understand risk matrix.")
    (license license:expat)))

(define-public r-cna
  (package
    (name "r-cna")
    (version "3.6.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cna" version))
       (sha256
        (base32 "1jjq77a2zzzkzv6sgl7274c8chznwc59cv8gnph3xya2ysmybspq"))))
    (properties `((upstream-name . "cna")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-matrixstats r-matrix r-car))
    (home-page "https://CRAN.R-project.org/package=cna")
    (synopsis "Causal Modeling with Coincidence Analysis")
    (description
     "This package provides comprehensive functionalities for causal modeling with
Coincidence Analysis (CNA), which is a configurational comparative method of
causal data analysis that was first introduced in Baumgartner (2009)
<doi:10.1177/0049124109339369>, and generalized in Baumgartner & Ambuehl (2018)
<doi:10.1017/psrm.2018.45>.  CNA is designed to recover INUS-causation from
data, which is particularly relevant for analyzing processes featuring
conjunctural causation (component causation) and equifinality (alternative
causation).  CNA is currently the only method for INUS-discovery that allows for
multiple effects (outcomes/endogenous factors), meaning it can analyze
common-cause and causal chain structures.")
    (license license:gpl2+)))

(define-public r-cmvnorm
  (package
    (name "r-cmvnorm")
    (version "1.0-7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmvnorm" version))
       (sha256
        (base32 "0zi4adh3gd8nbcnsn9fqiiqi5pc2jx782vw394gi988vyngqr7cq"))))
    (properties `((upstream-name . "cmvnorm")))
    (build-system r-build-system)
    (propagated-inputs (list r-emulator r-elliptic))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/RobinHankin/cmvnorm")
    (synopsis "The Complex Multivariate Gaussian Distribution")
    (description
     "Various utilities for the complex multivariate Gaussian distribution and complex
Gaussian processes.")
    (license license:gpl2)))

(define-public r-cmtest
  (package
    (name "r-cmtest")
    (version "0.1-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmtest" version))
       (sha256
        (base32 "1qff6vx0c9sw4xm7fwhck165snrahlmi91na64f7axad14qmp34d"))))
    (properties `((upstream-name . "cmtest")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack))
    (native-inputs (list r-knitr))
    (home-page "https://www.r-project.org")
    (synopsis "Conditional Moments Test")
    (description
     "Conditional moments test, as proposed by Newey (1985) <doi:10.2307/1911011 > and
Tauchen (1985) <doi:10.1016/0304-4076(85)90149-6>, useful to detect
specification violations for models estimated by maximum likelihood.  Methods
for probit and tobit models are provided.")
    (license license:gpl2+)))

(define-public r-cmstatrext
  (package
    (name "r-cmstatrext")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmstatrExt" version))
       (sha256
        (base32 "06py81q7viz2mh58qn16wvw9xw95vw06cg465qhdrh80j07mygzg"))))
    (properties `((upstream-name . "cmstatrExt")))
    (build-system r-build-system)
    (propagated-inputs (list r-testthat r-rlang r-rcpp r-generics r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/cmstatr/cmstatrExt")
    (synopsis "More Statistical Methods for Composite Material Data")
    (description
     "This package provides a companion package to cmstatr
<https://cran.r-project.org/package=cmstatr>.  cmstatr contains statistical
methods that are published in the Composite Materials Handbook, Volume 1 (2012,
ISBN: 978-0-7680-7811-4), while @code{cmstatrExt} contains statistical methods
that are not included in that handbook.")
    (license license:agpl3)))

(define-public r-cmstatr
  (package
    (name "r-cmstatr")
    (version "0.9.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmstatr" version))
       (sha256
        (base32 "1hi3zyw73jxrl2spfbbfk5xnyg31jqlslz1342p5s45k4ydvqikm"))))
    (properties `((upstream-name . "cmstatr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-rlang
                             r-purrr
                             r-mass
                             r-ksamples
                             r-ggplot2
                             r-generics
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://www.cmstatr.net/")
    (synopsis "Statistical Methods for Composite Material Data")
    (description
     "An implementation of the statistical methods commonly used for advanced
composite materials in aerospace applications.  This package focuses on
calculating basis values (lower tolerance bounds) for material strength
properties, as well as performing the associated diagnostic tests.  This package
provides functions for calculating basis values assuming several different
distributions, as well as providing functions for non-parametric methods of
computing basis values.  Functions are also provided for testing the hypothesis
that there is no difference between strength and modulus data from an alternate
sample and that from a \"qualification\" or \"baseline\" sample.  For a discussion
of these statistical methods and their use, see the Composite Materials
Handbook, Volume 1 (2012, ISBN: 978-0-7680-7811-4).  Additional details about
this package are available in the paper by Kloppenborg (2020,
<doi:10.21105/joss.02265>).")
    (license license:agpl3)))

(define-public r-cmshiny
  (package
    (name "r-cmshiny")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CMShiny" version))
       (sha256
        (base32 "0ciis3930yhn4dmazsg2yp7wi9hdfj5slr032x8qfllxis7m4k0w"))))
    (properties `((upstream-name . "CMShiny")))
    (build-system r-build-system)
    (propagated-inputs (list r-shinymatrix
                             r-shiny
                             r-rmarkdown
                             r-matrix
                             r-epitools
                             r-e1071
                             r-caret))
    (home-page "https://cran.r-project.org/package=CMShiny")
    (synopsis "Interactive Document for Working with Confusion Matrix")
    (description
     "An interactive document on the topic of confusion matrix analysis using
rmarkdown and shiny packages.  Runtime examples are provided in the package
function as well as at
<https://predanalyticssessions1.shinyapps.io/@code{ConfusionMatrixShiny/>}.")
    (license license:gpl2)))

(define-public r-cmsafvis
  (package
    (name "r-cmsafvis")
    (version "1.2.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmsafvis" version))
       (sha256
        (base32 "021dhsa84np86cjbgri0a0z1ymmxs7gr6107c4qq0xyjvh0r427m"))))
    (properties `((upstream-name . "cmsafvis")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp
                             r-sf
                             r-rcolorbrewer
                             r-rastervis
                             r-raster
                             r-progress
                             r-png
                             r-ncdf4
                             r-maps
                             r-mapproj
                             r-gridextra
                             r-fields
                             r-countrycode
                             r-colorspace
                             r-cmsafops
                             r-assertthat))
    (home-page "https://cran.r-project.org/package=cmsafvis")
    (synopsis "Tools to Visualize CM SAF NetCDF Data")
    (description
     "The Satellite Application Facility on Climate Monitoring (CM SAF) is a ground
segment of the European Organization for the Exploitation of Meteorological
Satellites (EUMETSAT) and one of EUMETSATs Satellite Application Facilities.
The CM SAF contributes to the sustainable monitoring of the climate system by
providing essential climate variables related to the energy and water cycle of
the atmosphere (<https://www.cmsaf.eu>).  It is a joint cooperation of eight
National Meteorological and Hydrological Services.  The cmsafvis R-package
provides a collection of R-operators for the analysis and visualization of CM
SAF @code{NetCDF} data.  CM SAF climate data records are provided for free via
(<https://wui.cmsaf.eu/safira>).  Detailed information and test data are
provided on the CM SAF webpage (<http://www.cmsaf.eu/R_toolbox>).")
    (license license:gpl3+)))

(define-public r-cmsafops
  (package
    (name "r-cmsafops")
    (version "1.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmsafops" version))
       (sha256
        (base32 "118msgfysvbg08nvzrx5nmffvszn1cfx91lzd2hkd6la8sivk10h"))))
    (properties `((upstream-name . "cmsafops")))
    (build-system r-build-system)
    (propagated-inputs (list r-trend
                             r-searchtrees
                             r-raster
                             r-rainfarmr
                             r-progress
                             r-ncdf4
                             r-fnn
                             r-fields
                             r-assertthat))
    (home-page "https://www.cmsaf.eu")
    (synopsis "Tools for CM SAF NetCDF Data")
    (description
     "The Satellite Application Facility on Climate Monitoring (CM SAF) is a ground
segment of the European Organization for the Exploitation of Meteorological
Satellites (EUMETSAT) and one of EUMETSATs Satellite Application Facilities.
The CM SAF contributes to the sustainable monitoring of the climate system by
providing essential climate variables related to the energy and water cycle of
the atmosphere (<https://www.cmsaf.eu>).  It is a joint cooperation of eight
National Meteorological and Hydrological Services.  The cmsafops R-package
provides a collection of R-operators for the analysis and manipulation of CM SAF
@code{NetCDF} formatted data.  Other CF conform @code{NetCDF} data with time,
longitude and latitude dimension should be applicable, but there is no guarantee
for an error-free application.  CM SAF climate data records are provided for
free via (<https://wui.cmsaf.eu/safira>).  Detailed information and test data
are provided on the CM SAF webpage (<http://www.cmsaf.eu/R_toolbox>).")
    (license license:gpl3+)))

(define-public r-cmsaf
  (package
    (name "r-cmsaf")
    (version "3.5.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmsaf" version))
       (sha256
        (base32 "19mp8hf34xnw71facrb7xq081x1lclpp84p1pd8n7fy2jmp6r767"))))
    (properties `((upstream-name . "cmsaf")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-shinywidgets
                             r-shinythemes
                             r-shinyjs
                             r-shinyfiles
                             r-shiny
                             r-searchtrees
                             r-raster
                             r-r-utils
                             r-ncdf4
                             r-maps
                             r-fnn
                             r-data-table
                             r-colourpicker
                             r-colorspace
                             r-cmsafvis
                             r-cmsafops))
    (home-page "https://www.cmsaf.eu")
    (synopsis "Toolbox for CM SAF NetCDF Data")
    (description
     "The Satellite Application Facility on Climate Monitoring (CM SAF) is a ground
segment of the European Organization for the Exploitation of Meteorological
Satellites (EUMETSAT) and one of EUMETSATs Satellite Application Facilities.
The CM SAF contributes to the sustainable monitoring of the climate system by
providing essential climate variables related to the energy and water cycle of
the atmosphere (<https://www.cmsaf.eu>).  It is a joint cooperation of eight
National Meteorological and Hydrological Services.  The cmsaf R-package includes
a shiny based interface for an easy application of the cmsafops and cmsafvis
packages - the CM SAF R Toolbox.  The Toolbox offers an easy way to prepare,
manipulate, analyse and visualize CM SAF @code{NetCDF} formatted data.  Other CF
conform @code{NetCDF} data with time, longitude and latitude dimension should be
applicable, but there is no guarantee for an error-free application.  CM SAF
climate data records are provided for free via (<https://wui.cmsaf.eu/safira>).
Detailed information and test data are provided on the CM SAF webpage
(<http://www.cmsaf.eu/R_toolbox>).")
    (license license:gpl3+)))

(define-public r-cms
  (package
    (name "r-cms")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cms" version))
       (sha256
        (base32 "0m3cxvw40nyr1jpdkhg5nbms16hkzj0mrx5nl39x1l42cx2hcjrl"))))
    (properties `((upstream-name . "cms")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-rvest
                             r-rlang
                             r-readr
                             r-magrittr
                             r-dplyr
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/subramv/cms")
    (synopsis "Calculate Medicare Reimbursement")
    (description
     "Uses the CMS application programming interface
<https://dnav.cms.gov/api/healthdata> to provide users databases containing
yearly Medicare reimbursement rates in the United States.  Data can be acquired
for the entire United States or only for specific localities.  Currently,
support is only provided for the Medicare Physician Fee Schedule, but support
will be expanded for other CMS databases in future versions.")
    (license license:gpl3)))

(define-public r-cmrutils
  (package
    (name "r-cmrutils")
    (version "1.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmrutils" version))
       (sha256
        (base32 "0nrq84bkd23lvvg8ls2smkjcnfnydhbcni3n6s8w0579i9xga8dv"))))
    (properties `((upstream-name . "cmrutils")))
    (build-system r-build-system)
    (propagated-inputs (list r-chron))
    (home-page "https://github.com/aparamon/cmrutils")
    (synopsis "Misc Functions of the Center for Mathematical Research")
    (description
     "This package provides a collection of useful helper routines developed by
students of the Center for Mathematical Research, Stankin, Moscow.")
    (license license:gpl3+)))

(define-public r-cmr
  (package
    (name "r-cmr")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmR" version))
       (sha256
        (base32 "1wism1czh94wfjgb1p4y0bvkb2ljkmkr4qkandbdjlgn013kjgv0"))))
    (properties `((upstream-name . "cmR")))
    (build-system r-build-system)
    (propagated-inputs (list r-plotrix r-matrix r-fields))
    (native-inputs (list r-r-rsp r-knitr))
    (home-page "https://bioimaginggroup.github.io/cmr/")
    (synopsis "Analysis of Cardiac Magnetic Resonance Images")
    (description
     "Computes maximum response from Cardiac Magnetic Resonance Images using spatial
and voxel wise spline based Bayesian model.  This is an implementation of the
methods described in Schmid (2011) <doi:10.1109/TMI.2011.2109733> \"Voxel-Based
Adaptive Spatio-Temporal Modelling of Perfusion Cardiovascular MRI\".  IEEE TMI
30(7) p.  1305 - 1313.")
    (license license:gpl3)))

(define-public r-cmpsr
  (package
    (name "r-cmpsr")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmpsR" version))
       (sha256
        (base32 "1qkdv86v0pk9knl97lfz28w8vgn71j7fv9aw8afq8qflfgvda284"))))
    (properties `((upstream-name . "cmpsR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-ggplot2 r-dplyr r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cmpsR")
    (synopsis "R Implementation of Congruent Matching Profile Segments Method")
    (description
     "This is an open-source implementation of the Congruent Matching Profile Segments
(CMPS) method (Chen et al.  2019)<doi:10.1016/j.forsciint.2019.109964>.  In
general, it can be used for objective comparison of striated tool marks, and in
our examples, we specifically use it for bullet signatures comparisons.  The
CMPS score is expected to be large if two signatures are similar.  So it can
also be considered as a feature that measures the similarity of two bullet
signatures.")
    (license license:gpl3)))

(define-public r-cmprskqr
  (package
    (name "r-cmprskqr")
    (version "0.9.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmprskQR" version))
       (sha256
        (base32 "1b3di5fsgglriv00fxydpc4p8lh0xcgi6jc04awq2vmp6s8kvjmw"))))
    (properties `((upstream-name . "cmprskQR")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-quantreg))
    (home-page "https://bitbucket.org/sdlugosz/cmprskqr")
    (synopsis "Analysis of Competing Risks Using Quantile Regressions")
    (description
     "Estimation, testing and regression modeling of subdistribution functions in
competing risks using quantile regressions, as described in Peng and Fine (2009)
<DOI:10.1198/jasa.2009.tm08228>.")
    (license license:gpl2+)))

(define-public r-cmprskcoxmsm
  (package
    (name "r-cmprskcoxmsm")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmprskcoxmsm" version))
       (sha256
        (base32 "1q17nzvqv0c8p2fs34fqszllp6g7kdbsmw4frlxpbjr3gwgd8rlk"))))
    (properties `((upstream-name . "cmprskcoxmsm")))
    (build-system r-build-system)
    (propagated-inputs (list r-twang r-survival r-sandwich r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cmprskcoxmsm")
    (synopsis "Use IPW to Estimate Treatment Effect under Competing Risks")
    (description
     "Uses inverse probability weighting methods to estimate treatment effect under
marginal structure model for the cause-specific hazard of competing risk events.
 Estimates also the cumulative incidence function (i.e.  risk) of the potential
outcomes, and provides inference on risk difference and risk ratio.  Reference:
Kalbfleisch & Prentice (2002)<doi:10.1002/9781118032985>; Hernan et al
(2001)<doi:10.1198/016214501753168154>.")
    (license license:gpl2+)))

(define-public r-cmocean
  (package
    (name "r-cmocean")
    (version "0.3-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmocean" version))
       (sha256
        (base32 "0a4wxakh22rxv9xrmvj0rmky9pbsf4j9dl9fvj9v002flbkw9yv4"))))
    (properties `((upstream-name . "cmocean")))
    (build-system r-build-system)
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://matplotlib.org/cmocean/")
    (synopsis "Beautiful Colour Maps for Oceanography")
    (description
     "Perceptually uniform palettes for commonly used variables in oceanography as
functions taking an integer and producing character vectors of colours.  See
Thyng, K.M., Greene, C.A., Hetland, R.D., Zimmerle, H.M. and S.F. @code{DiMarco}
(2016) <doi:10.5670/oceanog.2016.66> for the guidelines adhered to when creating
the palettes.")
    (license license:expat)))

(define-public r-cmna
  (package
    (name "r-cmna")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmna" version))
       (sha256
        (base32 "161qc7q88ajm3l62bq03lpf35bdii1w1d111085zvs3hrf09iybw"))))
    (properties `((upstream-name . "cmna")))
    (build-system r-build-system)
    (home-page "https://jameshoward.us/cmna/")
    (synopsis "Computational Methods for Numerical Analysis")
    (description
     "This package provides the source and examples for James P. Howard, II,
\"Computational Methods for Numerical Analysis with R,\"
<https://jameshoward.us/cmna/>, a book on numerical methods in R.")
    (license license:bsd-2)))

(define-public r-cmms
  (package
    (name "r-cmms")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CMMs" version))
       (sha256
        (base32 "0wdzyg7kwad8z6kdijbpj8dmhyv17rg027rspv8hxlg8r3l8bd47"))))
    (properties `((upstream-name . "CMMs")))
    (build-system r-build-system)
    (propagated-inputs (list r-survey
                             r-robcompositions
                             r-ggplot2
                             r-forcats
                             r-fastdummies
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=CMMs")
    (synopsis "Compositional Mediation Model")
    (description
     "This package provides a compositional mediation model for continuous outcome and
binary outcomes to deal with mediators that are compositional data.  Lin,
Ziqiang et al. (2022) <doi:10.1016/j.jad.2021.12.019>.")
    (license license:gpl3)))

(define-public r-cmmr
  (package
    (name "r-cmmr")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmmr" version))
       (sha256
        (base32 "1qqwg139an072nm2szyk219id8nvqfrq3vb9z813aszmn9h6a16l"))))
    (properties `((upstream-name . "cmmr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rjsonio r-progress r-httr r-cli))
    (home-page "https://github.com/YaoxiangLi/cmmr")
    (synopsis "CEU Mass Mediator RESTful API")
    (description
     "CEU (CEU San Pablo University) Mass Mediator is an on-line tool for aiding
researchers in performing metabolite annotation.  cmmr (CEU Mass Mediator
RESTful API) allows for programmatic access in R: batch search, batch advanced
search, MS/MS (tandem mass spectrometry) search, etc.  For more information
about the API Endpoint please go to <https://github.com/@code{YaoxiangLi/cmmr>}.")
    (license license:gpl3)))

(define-public r-cmm
  (package
    (name "r-cmm")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmm" version))
       (sha256
        (base32 "1aardzrryg6hs5x01absvnj62qys7qjmnzrbsjh1dqvr4jgvs8ka"))))
    (properties `((upstream-name . "cmm")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cmm")
    (synopsis "Categorical Marginal Models")
    (description
     "Quite extensive package for maximum likelihood estimation and weighted least
squares estimation of categorical marginal models (CMMs; e.g., Bergsma and
Rudas, 2002, <http://www.jstor.org/stable/2700006?; Bergsma, Croon and
Hagenaars, 2009, <DOI:10.1007/b12532>.")
    (license license:gpl2+)))

(define-public r-cmls
  (package
    (name "r-cmls")
    (version "1.0-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CMLS" version))
       (sha256
        (base32 "0vgqdqckkyf0rnxi6hp6xfc1wv2ldz5p8bmc6jq1rgwgz4b66a0p"))))
    (properties `((upstream-name . "CMLS")))
    (build-system r-build-system)
    (propagated-inputs (list r-quadprog))
    (home-page "https://cran.r-project.org/package=CMLS")
    (synopsis "Constrained Multivariate Least Squares")
    (description
     "Solves multivariate least squares (MLS) problems subject to constraints on the
coefficients, e.g., non-negativity, orthogonality, equality, inequality,
monotonicity, unimodality, smoothness, etc.  Includes flexible functions for
solving MLS problems subject to user-specified equality and/or inequality
constraints, as well as a wrapper function that implements 24 common constraint
options.  Also does k-fold or generalized cross-validation to tune constraint
options for MLS problems.  See ten Berge (1993, ISBN:9789066950832) for an
overview of MLS problems, and see Goldfarb and Idnani (1983)
<doi:10.1007/BF02591962> for a discussion of the underlying quadratic
programming algorithm.")
    (license license:gpl2+)))

(define-public r-cml
  (package
    (name "r-cml")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cml" version))
       (sha256
        (base32 "1k1fj3j6kxpnxzykqbrcv09q8xhp749apfir0hzkp1f2apyjxymi"))))
    (properties `((upstream-name . "cml")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan))
    (home-page "https://cran.r-project.org/package=cml")
    (synopsis "Conditional Manifold Learning")
    (description
     "Finds a low-dimensional embedding of high-dimensional data, conditioning on
available manifold information.  The current version supports conditional MDS
(based on either conditional SMACOF in Bui (2021) <@code{arXiv:2111.13646>} or
closed-form solution in Bui (2022) <doi:10.1016/j.patrec.2022.11.007>) and
conditional ISOMAP in Bui (2021) <@code{arXiv:2111.13646>}.")
    (license license:gpl2)))

(define-public r-cmhnpa
  (package
    (name "r-cmhnpa")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CMHNPA" version))
       (sha256
        (base32 "08pjnc2l2ip8x9hbgsp74alrk520an5kq0lxwqh33smfw1frw4ql"))))
    (properties `((upstream-name . "CMHNPA")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-car))
    (home-page "https://cran.r-project.org/package=CMHNPA")
    (synopsis "Cochran-Mantel-Haenszel and Nonparametric ANOVA")
    (description
     "Cochran-Mantel-Haenszel methods (Cochran (1954) <doi:10.2307/3001616>; Mantel
and Haenszel (1959) <doi:10.1093/jnci/22.4.719>; Landis et al. (1978)
<doi:10.2307/1402373>) are a suite of tests applicable to categorical data.  A
competitor to those tests is the procedure of Nonparametric ANOVA which was
initially introduced in Rayner and Best (2013) <doi:10.1111/anzs.12041>.  The
methodology was then extended in Rayner et al. (2015) <doi:10.1111/anzs.12113>.
This package employs functions related to both methodologies and serves as an
accompaniment to the book: An Introduction to CochranâMantelâHaenszel and
Non-Parametric ANOVA. The package also contains the data sets used in that text.")
    (license license:gpl3)))

(define-public r-cmhc
  (package
    (name "r-cmhc")
    (version "0.2.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmhc" version))
       (sha256
        (base32 "1rjwc58f43iv3ri7z42z3gzfxcpkrzbd20r07rm6m14d7d5wqw0w"))))
    (properties `((upstream-name . "cmhc")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-rlang
                             r-readr
                             r-httr
                             r-dplyr
                             r-digest
                             r-aws-s3))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mountainMath/cmhc")
    (synopsis "Access, Retrieve, and Work with CMHC Data")
    (description
     "Wrapper around the Canadian Mortgage and Housing Corporation (CMHC) web
interface.  It enables programmatic and reproducible access to a wide variety of
housing data from CMHC.")
    (license license:expat)))

(define-public r-cmgfm
  (package
    (name "r-cmgfm")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CMGFM" version))
       (sha256
        (base32 "0km485aajgwb0jyp7fvgz82dw22la659js4d4hg2zbkn562pz4m3"))))
    (properties `((upstream-name . "CMGFM")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-mass r-irlba r-gfm))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CMGFM")
    (synopsis "Covariate-Augumented Generalized Factor Model")
    (description
     "Covariate-augumented generalized factor model is designed to account for
cross-modal heterogeneity, capture nonlinear dependencies among the data,
incorporate additional information, and provide excellent interpretability while
maintaining high computational efficiency.")
    (license license:gpl3)))

(define-public r-cmfsurrogate
  (package
    (name "r-cmfsurrogate")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CMFsurrogate" version))
       (sha256
        (base32 "1n0kf6mby71zccymdl75yw8rafkl9y7kn9j2pipqf15zvbqdl33j"))))
    (properties `((upstream-name . "CMFsurrogate")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=CMFsurrogate")
    (synopsis "Calibrated Model Fusion Approach to Combine Surrogate Markers")
    (description
     "Uses a calibrated model fusion approach to optimally combine multiple surrogate
markers.  Specifically, two initial estimates of optimal composite scores of the
markers are obtained; the optimal calibrated combination of the two estimated
scores is then constructed which ensures both validity of the final combined
score and optimality with respect to the proportion of treatment effect
explained (PTE) by the final combined score.  The primary function,
pte.estimate.multiple(), estimates the PTE of the identified combination of
multiple surrogate markers.  Details are described in Wang et al (2022)
<doi:10.1111/biom.13677>.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-cmfrec
  (package
    (name "r-cmfrec")
    (version "3.5.1-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmfrec" version))
       (sha256
        (base32 "0hlz10zrwdk9p0rybfqn04104bv0d9024d0ca1d6v66ymzy3gwlw"))))
    (properties `((upstream-name . "cmfrec")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/david-cortes/cmfrec")
    (synopsis "Collective Matrix Factorization for Recommender Systems")
    (description
     "Collective matrix factorization (a.k.a.  multi-view or multi-way factorization,
Singh, Gordon, (2008) <doi:10.1145/1401890.1401969>) tries to approximate a
(potentially very sparse or having many missing values) matrix X as the product
of two low-dimensional matrices, optionally aided with secondary information
matrices about rows and/or columns of X', which are also factorized using the
same latent components.  The intended usage is for recommender systems,
dimensionality reduction, and missing value imputation.  Implements extensions
of the original model (Cortes, (2018) <@code{arXiv:1809.00366>}) and can produce
different factorizations such as the weighted implicit-feedback model (Hu,
Koren, Volinsky, (2008) <doi:10.1109/ICDM.2008.22>), the
weighted-lambda-regularization model, (Zhou, Wilkinson, Schreiber, Pan, (2008)
<doi:10.1007/978-3-540-68880-8_32>), or the enhanced model with implicit
features (Rendle, Zhang, Koren, (2019) <@code{arXiv:1905.01395>}), with or
without side information.  Can use gradient-based procedures or
alternating-least squares procedures (Koren, Bell, Volinsky, (2009)
<doi:10.1109/MC.2009.263>), with either a Cholesky solver, a faster conjugate
gradient solver (Takacs, Pilaszy, Tikk, (2011) <doi:10.1145/2043932.2043987>),
or a non-negative coordinate descent solver (Franc, Hlavac, Navara, (2005)
<doi:10.1007/11556121_50>), providing efficient methods for sparse and dense
data, and mixtures thereof.  Supports L1 and L2 regularization in the main
models, offers alternative most-popular and content-based models, and implements
functionality for cold-start recommendations and imputation of 2D data.")
    (license license:expat)))

(define-public r-cmf
  (package
    (name "r-cmf")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CMF" version))
       (sha256
        (base32 "08fy6iz535z3v92dra184fyiaqikdv7m5z8hd394mji1qpwicbaa"))))
    (properties `((upstream-name . "CMF")))
    (build-system r-build-system)
    (propagated-inputs (list r-cpp11))
    (home-page "https://cran.r-project.org/package=CMF")
    (synopsis "Collective Matrix Factorization")
    (description
     "Collective matrix factorization (CMF) finds joint low-rank representations for a
collection of matrices with shared row or column entities.  This code learns a
variational Bayesian approximation for CMF, supporting multiple likelihood
potentials and missing data, while identifying both factors shared by multiple
matrices and factors private for each matrix.  For further details on the method
see Klami et al. (2014) <@code{arXiv:1312.5921>}.  The package can also be used
to learn Bayesian canonical correlation analysis (CCA) and group factor analysis
(GFA) models, both of which are special cases of CMF. This is likely to be
useful for people looking for CCA and GFA solutions supporting missing data and
non-Gaussian likelihoods.  See Klami et al. (2013)
<https://research.cs.aalto.fi/pml/online-papers/klami13a.pdf> and	Virtanen et
al. (2012) <http://proceedings.mlr.press/v22/virtanen12.html> for details on
Bayesian CCA and GFA, respectively.")
    (license license:gpl2+)))

(define-public r-cmenet
  (package
    (name "r-cmenet")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmenet" version))
       (sha256
        (base32 "0v3fassl21wdyx7s4shsib936fr41qr9hxjgcjc2f8az0ljd1p70"))))
    (properties `((upstream-name . "cmenet")))
    (build-system r-build-system)
    (propagated-inputs (list r-sparsenet
                             r-rcpparmadillo
                             r-rcpp
                             r-mass
                             r-hiernet
                             r-glmnet))
    (home-page "https://cran.r-project.org/package=cmenet")
    (synopsis "Bi-Level Selection of Conditional Main Effects")
    (description
     "This package provides functions for implementing cmenet - a bi-level variable
selection method for conditional main effects (see Mak and Wu (2018)
<doi:10.1080/01621459.2018.1448828>).  CMEs are reparametrized interaction
effects which capture the conditional impact of a factor at a fixed level of
another factor.  Compared to traditional two-factor interactions, CMEs can
quantify more interpretable interaction effects in many problems.  The current
implementation performs variable selection on only binary CMEs; we are working
on an extension for the continuous setting.")
    (license license:gpl2+)))

(define-public r-cmcr
  (package
    (name "r-cmcr")
    (version "0.1.11")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmcR" version))
       (sha256
        (base32 "15d85mjy6y68jysji0910kg9vp69iz4pbb2l4vmn501xq4md3kx3"))))
    (properties `((upstream-name . "cmcR")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-x3ptools
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-scales
                             r-rlang
                             r-quantreg
                             r-purrr
                             r-patchwork
                             r-magrittr
                             r-imager
                             r-ggplotify
                             r-ggplot2
                             r-ggnewscale
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cmcR")
    (synopsis "An Implementation of the 'Congruent Matching Cells' Method")
    (description
     "An open-source implementation of the Congruent Matching Cells method for
cartridge case identification as proposed by Song (2013)
<https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=911193> as well as an
extension of the method proposed by Tong et al. (2015)
<doi:10.6028/jres.120.008>.  Provides a wide range of pre, inter, and
post-processing options when working with cartridge case scan data and their
associated comparisons.  See the @code{cmcR} package website for more details
and examples.")
    (license license:gpl3+)))

(define-public r-cmce
  (package
    (name "r-cmce")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmce" version))
       (sha256
        (base32 "0d52ci906zbd4q43qylcyw93acxh7f20jn3r0k74ynyy47131dnd"))))
    (properties `((upstream-name . "cmce")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cmce")
    (synopsis
     "Computer Model Calibration for Deterministic and Stochastic Simulators")
    (description
     "This package implements the Bayesian calibration model described in Pratola and
Chkrebtii (2018) <DOI:10.5705/ss.202016.0403> for stochastic and deterministic
simulators.  Additive and multiplicative discrepancy models are currently
supported.  See <http://www.matthewpratola.com/software> for more information
and examples.")
    (license license:agpl3)))

(define-public r-cmbclust
  (package
    (name "r-cmbclust")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmbClust" version))
       (sha256
        (base32 "01yjiscnligy6wpn752sqm53xhx0qxjbfd4dc8p7c31kbzfpif2x"))))
    (properties `((upstream-name . "cmbClust")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cmbClust")
    (synopsis "Conditional Mixture Modeling and Model-Based Clustering")
    (description
     "Conditional mixture model fitted via EM (Expectation Maximization) algorithm for
model-based clustering, including parsimonious procedure, optimal conditional
order exploration, and visualization.")
    (license license:gpl2+)))

(define-public r-cmars
  (package
    (name "r-cmars")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmaRs" version))
       (sha256
        (base32 "028z0x6a6aq3n0kplqg4pwqa7xilpi4s919xrqvd2lqnabhbjy8l"))))
    (properties `((upstream-name . "cmaRs")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-ryacas0
                             r-rocr
                             r-rmosek
                             r-mpv
                             r-matrix
                             r-earth
                             r-auc))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cmaRs")
    (synopsis
     "Implementation of the Conic Multivariate Adaptive Regression Splines in R")
    (description
     "An implementation of Conic Multivariate Adaptive Regression Splines (CMARS) in
R. See Weber et al. (2011) CMARS: a new contribution to nonparametric regression
with multivariate adaptive regression splines supported by continuous
optimization, <DOI:10.1080/17415977.2011.624770>.  It constructs models by using
the terms obtained from the forward step of MARS and then estimates parameters
by using Tikhonov regularization and conic quadratic optimization.  It is
possible to construct models for prediction and binary classification.  It
provides performance measures for the model developed.  The package needs the
optimisation software MOSEK <https://www.mosek.com/> to construct the models.
Please follow the instructions in Rmosek for the installation.")
    (license license:gpl2+)))

(define-public r-cmapviz
  (package
    (name "r-cmapviz")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CMapViz" version))
       (sha256
        (base32 "1s7xyp13p7fpbq0bghk07dfv90339kxs7k3343jqhrn8djf3as67"))))
    (properties `((upstream-name . "CMapViz")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-scales
                             r-reshape2
                             r-readxl
                             r-ggplot2
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=CMapViz")
    (synopsis
     "Representation Tool For Output Of Connectivity Map (CMap) Analysis")
    (description
     "Automatically displays graphical visualization for exported data table
(permutated results) from Connectivity Map (CMap) (2006)
<doi:10.1126/science.1132939>.  It allows the representation of the statistics
(p-value and enrichment) according to each cell lines in the form of a bubble
plot.")
    (license license:gpl3)))

(define-public r-cmapss
  (package
    (name "r-cmapss")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CMAPSS" version))
       (sha256
        (base32 "1rig2v1cl9ybnbikqfwbp4ji1jcxm6383xbdf8wz2f3lxk7iis8z"))))
    (properties `((upstream-name . "CMAPSS")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack))
    (home-page "https://cran.r-project.org/package=CMAPSS")
    (synopsis "Commercial Modular Aero-Propulsion System Simulation Data Set")
    (description
     "This package contains the Commercial Modular Aero-Propulsion System Simulation
(C-MAPSS) data set.")
    (license license:gpl3)))

(define-public r-cmahalanobis
  (package
    (name "r-cmahalanobis")
    (version "0.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmahalanobis" version))
       (sha256
        (base32 "1lbw1ffn3lhillzmgg8q4klqybw4hka1jn37b3npzixc0mij8ywb"))))
    (properties `((upstream-name . "cmahalanobis")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2 r-mice r-ggplot2))
    (home-page "https://cran.r-project.org/package=cmahalanobis")
    (synopsis
     "Calculate Distance Measures for a Given List of Data Frames with Factors")
    (description
     "It provides functions that calculate Mahalanobis distance, Euclidean distance,
Manhattan distance and Chebyshev distance between each pair of species in a list
of data frames.  These metrics are fundamental in various fields, such as
cluster analysis, classification, and other applications of machine learning and
data mining, where assessing similarity or dissimilarity between data is
crucial.  The package is designed to be flexible and easily integrated into data
analysis workflows, providing reliable tools for evaluating distances in
multidimensional contexts.")
    (license license:gpl3)))

(define-public r-cmaesr
  (package
    (name "r-cmaesr")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmaesr" version))
       (sha256
        (base32 "03zx2nrw24wmmjjpyh8pswasjjq0amf0g375fm2b3s111dx8fbj9"))))
    (properties `((upstream-name . "cmaesr")))
    (build-system r-build-system)
    (propagated-inputs (list r-smoof r-paramhelpers r-ggplot2 r-checkmate
                             r-bbmisc))
    (home-page "https://github.com/jakobbossek/cmaesr")
    (synopsis "Covariance Matrix Adaptation Evolution Strategy")
    (description
     "Pure R implementation of the Covariance Matrix Adaptation - Evolution Strategy
(CMA-ES) with optional restarts (IPOP-CMA-ES).")
    (license license:bsd-2)))

(define-public r-cmaes
  (package
    (name "r-cmaes")
    (version "1.0-12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cmaes" version))
       (sha256
        (base32 "0wk8zkf585ipnxajmibip85cyz7wc5br0cph3cvnacbh7yf2zvay"))))
    (properties `((upstream-name . "cmaes")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cmaes")
    (synopsis "Covariance Matrix Adapting Evolutionary Strategy")
    (description "Single objective optimization using a CMA-ES.")
    (license license:gpl2)))

(define-public r-clvtools
  (package
    (name "r-clvtools")
    (version "0.11.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CLVTools" version))
       (sha256
        (base32 "143c9b23xaqi9pxq416a2d1hbpjqdcnvz6nzl77s4kgfn5whabsl"))))
    (properties `((upstream-name . "CLVTools")))
    (build-system r-build-system)
    (propagated-inputs (list r-testthat
                             r-rcppgsl
                             r-rcpparmadillo
                             r-rcpp
                             r-optimx
                             r-numderiv
                             r-matrix
                             r-mass
                             r-lubridate
                             r-ggplot2
                             r-formula
                             r-digest
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/bachmannpatrick/CLVTools")
    (synopsis "Tools for Customer Lifetime Value Estimation")
    (description
     "This package provides a set of state-of-the-art probabilistic modeling
approaches to derive estimates of individual customer lifetime values (CLV).
Commonly, probabilistic approaches focus on modelling 3 processes, i.e.
individuals attrition, transaction, and spending process.  Latent customer
attrition models, which are also known as \"buy-'til-you-die models\", model the
attrition as well as the transaction process.  They are used to make inferences
and predictions about transactional patterns of individual customers such as
their future purchase behavior.  Moreover, these models have also been used to
predict individualsâ long-term engagement in activities such as playing an
online game or posting to a social media platform.  The spending process is
usually modelled by a separate probabilistic model.  Combining these results
yields in lifetime values estimates for individual customers.  This package
includes fast and accurate implementations of various probabilistic models for
non-contractual settings (e.g., grocery purchases or hotel visits).  All
implementations support time-invariant covariates, which can be used to control
for e.g., socio-demographics.  If such an extension has been proposed in
literature, we further provide the possibility to control for time-varying
covariates to control for e.g., seasonal patterns.  Currently, the package
includes the following latent attrition models to model individuals attrition
and transaction process: [1] Pareto/NBD model
(Pareto/Negative-Binomial-Distribution), [2] the Extended Pareto/NBD model
(Pareto/Negative-Binomial-Distribution with time-varying covariates), [3] the
BG/NBD model (Beta-Gamma/Negative-Binomial-Distribution) and the [4] GGom/NBD
(Gamma-Gompertz/Negative-Binomial-Distribution).  Further, we provide an
implementation of the Gamma/Gamma model to model the spending process of
individuals.")
    (license license:gpl3)))

(define-public r-clv
  (package
    (name "r-clv")
    (version "0.3-2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clv" version))
       (sha256
        (base32 "1zbi4i6z0sphkkjifr2h0pms9ysifh62iwcpmh9kmv2wl5m51vms"))))
    (properties `((upstream-name . "clv")))
    (build-system r-build-system)
    (propagated-inputs (list r-cluster r-class))
    (home-page "https://cran.r-project.org/package=clv")
    (synopsis "Cluster Validation Techniques")
    (description
     "Package contains most of the popular internal and external cluster validation
methods ready to use for the most of the outputs produced by functions coming
from package \"cluster\".  Package contains also functions and examples of usage
for cluster stability approach that might be applied to algorithms implemented
in \"cluster\" package as well as user defined clustering algorithms.")
    (license license:gpl2+)))

(define-public r-clusvis
  (package
    (name "r-clusvis")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClusVis" version))
       (sha256
        (base32 "06yckdl3gxjia1gjjqpc29lvy4f7qf47fncslng9ggjnks6il145"))))
    (properties `((upstream-name . "ClusVis")))
    (build-system r-build-system)
    (propagated-inputs (list r-varsellcm
                             r-rmixmod
                             r-rcpparmadillo
                             r-rcpp
                             r-mvtnorm
                             r-mgcv
                             r-mass))
    (home-page "https://cran.r-project.org/package=ClusVis")
    (synopsis
     "Gaussian-Based Visualization of Gaussian and Non-Gaussian Model-Based Clustering")
    (description
     "Gaussian-Based Visualization of Gaussian and Non-Gaussian Model-Based Clustering
done on any type of data.  Visualization is based on the probabilities of
classification.")
    (license license:gpl2+)))

(define-public r-clustvarsel
  (package
    (name "r-clustvarsel")
    (version "2.3.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clustvarsel" version))
       (sha256
        (base32 "0hzvfcjs1k13j695jx6m0fgmcxy284gp4d59b7zmnvqib153x89x"))))
    (properties `((upstream-name . "clustvarsel")))
    (build-system r-build-system)
    (propagated-inputs (list r-mclust r-matrix r-iterators r-foreach r-bma))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=clustvarsel")
    (synopsis "Variable Selection for Gaussian Model-Based Clustering")
    (description
     "Variable selection for Gaussian model-based clustering as implemented in the
mclust package.  The methodology allows to find the (locally) optimal subset of
variables in a data set that have group/cluster information.  A greedy or
headlong search can be used, either in a forward-backward or backward-forward
direction, with or without sub-sampling at the hierarchical clustering stage for
starting mclust models.  By default the algorithm uses a sequential search, but
parallelisation is also available.")
    (license license:gpl2+)))

(define-public r-clustvarlv
  (package
    (name "r-clustvarlv")
    (version "2.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClustVarLV" version))
       (sha256
        (base32 "0maylgf6czlll5zn3xj68acmllxi4x2r4ri6bdx8vl9apzax1rgy"))))
    (properties `((upstream-name . "ClustVarLV")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppeigen
                             r-rcpp
                             r-plyr
                             r-iterators
                             r-foreach
                             r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ClustVarLV")
    (synopsis "Clustering of Variables Around Latent Variables")
    (description
     "This package provides functions for the clustering of variables around Latent
Variables, for 2-way or 3-way data.  Each cluster of variables, which may be
defined as a local or directional cluster, is associated with a latent variable.
 External variables measured on the same observations or/and additional
information on the variables can be taken into account.  A \"noise\" cluster or
sparse latent variables can also be defined.")
    (license license:gpl3)))

(define-public r-clusttmb
  (package
    (name "r-clusttmb")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clustTMB" version))
       (sha256
        (base32 "0dzqchr66cwcmvvaz1yfxfh46kd5f2qhlaivynyxww4rix5grlhy"))))
    (properties `((upstream-name . "clustTMB")))
    (build-system r-build-system)
    (propagated-inputs (list r-tmb
                             r-sf
                             r-reformulas
                             r-rcppeigen
                             r-moeclust
                             r-mclust
                             r-matrix
                             r-lme4
                             r-fmesher
                             r-clustmixtype
                             r-cluster))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Andrea-Havron/clustTMB")
    (synopsis "Spatio-Temporal Finite Mixture Model using 'TMB'")
    (description
     "Fits a spatio-temporal finite mixture model using TMB'.  Covariate, spatial and
temporal random effects can be incorporated into the gating formula using
multinomial logistic regression, the expert formula using a generalized linear
mixed model framework, or both.")
    (license license:gpl3)))

(define-public r-clustshiny
  (package
    (name "r-clustshiny")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CLUSTShiny" version))
       (sha256
        (base32 "19mh5g1ylvlab4xjxw7girxk9zkpxxczhbfijf11b592hbw0qxqk"))))
    (properties `((upstream-name . "CLUSTShiny")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny
                             r-rmarkdown
                             r-psycho
                             r-mass
                             r-klar
                             r-dplyr
                             r-cluster))
    (home-page "https://cran.r-project.org/package=CLUSTShiny")
    (synopsis "Interactive Document for Working with Cluster Analysis")
    (description
     "An interactive document on the topic of cluster analysis using rmarkdown and
shiny packages.  Runtime examples are provided in the package function as well
as at <https://analyticmodels.shinyapps.io/@code{ClusterAnalysis/>}.")
    (license license:gpl2)))

(define-public r-clustringr
  (package
    (name "r-clustringr")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clustringr" version))
       (sha256
        (base32 "07f0ywpkf8igic7ijvvrjlngq3smjcv9nqnah41fp6wfgvh49ifq"))))
    (properties `((upstream-name . "clustringr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidygraph
                             r-stringr
                             r-stringi
                             r-stringdist
                             r-rlang
                             r-magrittr
                             r-igraph
                             r-ggraph
                             r-ggplot2
                             r-forcats
                             r-dplyr
                             r-assertthat))
    (home-page "https://cran.r-project.org/package=clustringr")
    (synopsis "Cluster Strings by Edit-Distance")
    (description
     "Returns an edit-distance based clusterization of an input vector of strings.
Each cluster will contain a set of strings w/ small mutual edit-distance (e.g.,
Levenshtein, optimum-sequence-alignment, Damerau-Levenshtein), as computed by
stringdist::stringdist().  The set of all mutual edit-distances is then used by
graph algorithms (from package igraph') to single out subsets of high
connectivity.")
    (license license:expat)))

(define-public r-clustrd
  (package
    (name "r-clustrd")
    (version "1.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clustrd" version))
       (sha256
        (base32 "1pgl5yb37nsm0b1iniy7hadcxcbhlp5xwg77av74f568qp1pgx2c"))))
    (properties `((upstream-name . "clustrd")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-rarpack
                             r-plyr
                             r-ggrepel
                             r-ggplot2
                             r-ggally
                             r-fpc
                             r-dplyr
                             r-corpcor
                             r-cluster
                             r-ca))
    (home-page "https://cran.r-project.org/package=clustrd")
    (synopsis "Methods for Joint Dimension Reduction and Clustering")
    (description
     "This package provides a class of methods that combine dimension reduction and
clustering of continuous, categorical or mixed-type data (Markos, Iodice D'Enza
and van de Velden 2019; <DOI:10.18637/jss.v091.i10>).  For continuous data, the
package contains implementations of factorial K-means (Vichi and Kiers 2001;
<DOI:10.1016/S0167-9473(00)00064-5>) and reduced K-means (De Soete and Carroll
1994; <DOI:10.1007/978-3-642-51175-2_24>); both methods that combine principal
component analysis with K-means clustering.  For categorical data, the package
provides MCA K-means (Hwang, Dillon and Takane 2006;
<DOI:10.1007/s11336-004-1173-x>), i-FCB (Iodice D'Enza and Palumbo 2013,
<DOI:10.1007/s00180-012-0329-x>) and Cluster Correspondence Analysis (van de
Velden, Iodice D'Enza and Palumbo 2017; <DOI:10.1007/s11336-016-9514-0>), which
combine multiple correspondence analysis with K-means.  For mixed-type data, it
provides mixed Reduced K-means and mixed Factorial K-means (van de Velden,
Iodice D'Enza and Markos 2019; <DOI:10.1002/wics.1456>), which combine PCA for
mixed-type data with K-means.")
    (license license:gpl3)))

(define-public r-clustransition
  (package
    (name "r-clustransition")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clusTransition" version))
       (sha256
        (base32 "0q5cxkb5mrygyp2zg177rwn5cgpnyqln7yjvjflb48ll3jr98342"))))
    (properties `((upstream-name . "clusTransition")))
    (build-system r-build-system)
    (propagated-inputs (list r-flexclust))
    (home-page "https://cran.r-project.org/package=clusTransition")
    (synopsis "Monitor Changes in Cluster Solutions of Dynamic Datasets")
    (description
     "Monitor and trace changes in clustering solutions of accumulating datasets at
successive time points.  The clusters can adopt External and Internal transition
at succeeding time points.  The External transitions comprise of Survived,
Merged, Split, Disappeared, and newly Emerged candidates.  In contrast, Internal
transition includes changes in location and cohesion of the survived clusters.
The package uses MONIC framework developed by Spiliopoulou, Ntoutsi,
Theodoridis, and Schult (2006)<doi:10.1145/1150402.1150491> .")
    (license license:gpl3)))

(define-public r-clustra
  (package
    (name "r-clustra")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clustra" version))
       (sha256
        (base32 "115rf9n5cc07yprminw3hh25zlmrv9v0jv63s29mx43iq28wvbnw"))))
    (properties `((upstream-name . "clustra")))
    (build-system r-build-system)
    (propagated-inputs (list r-mixsim r-mgcv r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=clustra")
    (synopsis "Clustering Longitudinal Trajectories")
    (description
     "Clusters longitudinal trajectories over time (can be unequally spaced, unequal
length time series and/or partially overlapping series) on a common time axis.
Performs k-means clustering on a single continuous variable measured over time,
where each mean is defined by a thin plate spline fit to all points in a
cluster.  Distance is MSE across trajectory points to cluster spline.  Provides
graphs of derived cluster splines, silhouette plots, and Adjusted Rand Index
evaluations of the number of clusters.  Scales well to large data with multicore
parallelism available to speed computation.")
    (license (license:fsdg-compatible "BSD 2-clause License + file LICENSE"))))

(define-public r-clustorus
  (package
    (name "r-clustorus")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClusTorus" version))
       (sha256
        (base32 "052jq96xr9qrc203ib11qsni50j0jzdpfwmbnd5rypfvff6w5kxc"))))
    (properties `((upstream-name . "ClusTorus")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-purrr
                             r-igraph
                             r-ggplot2
                             r-cowplot
                             r-bambi))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/sungkyujung/ClusTorus")
    (synopsis "Prediction and Clustering on the Torus by Conformal Prediction")
    (description
     "This package provides various tools of for clustering multivariate angular data
on the torus.  The package provides angular adaptations of usual clustering
methods such as the k-means clustering, pairwise angular distances, which can be
used as an input for distance-based clustering algorithms, and implements
clustering based on the conformal prediction framework.  Options for the
conformal scores include scores based on a kernel density estimate, multivariate
von Mises mixtures, and naive k-means clusters.  Moreover, the package provides
some basic data handling tools for angular data.")
    (license license:gpl3)))

(define-public r-clustofvar
  (package
    (name "r-clustofvar")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClustOfVar" version))
       (sha256
        (base32 "0grhkab7s58ji4cf7cxh7ahd2dxrj8aqfdf3119b40zxkxbwxcr0"))))
    (properties `((upstream-name . "ClustOfVar")))
    (build-system r-build-system)
    (propagated-inputs (list r-pcamixdata))
    (home-page "https://cran.r-project.org/package=ClustOfVar")
    (synopsis "Clustering of Variables")
    (description
     "Cluster analysis of a set of variables.  Variables can be quantitative,
qualitative or a mixture of both.")
    (license license:gpl2+)))

(define-public r-clustnet
  (package
    (name "r-clustnet")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clustNet" version))
       (sha256
        (base32 "05yphmjjkc42k945b8qhdrlws5bzr3f0wbancyibn8xh5697wqsx"))))
    (properties `((upstream-name . "clustNet")))
    (build-system r-build-system)
    (propagated-inputs (list r-rbgl
                             r-pcalg
                             r-igraph
                             r-graph
                             r-clue
                             r-bidag))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=clustNet")
    (synopsis "Network-Based Clustering")
    (description
     "Network-based clustering using a Bayesian network mixture model with optional
covariate adjustment.")
    (license license:gpl3)))

(define-public r-clustmixtype
  (package
    (name "r-clustmixtype")
    (version "0.4-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clustMixType" version))
       (sha256
        (base32 "1clby7x9jz0jpzmzni6g8zicysnf7ccxliglxr6ljigvkf747bg1"))))
    (properties `((upstream-name . "clustMixType")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-rlang r-rcolorbrewer r-dplyr
                             r-combinat))
    (home-page "https://cran.r-project.org/package=clustMixType")
    (synopsis "k-Prototypes Clustering for Mixed Variable-Type Data")
    (description
     "This package provides functions to perform k-prototypes partitioning clustering
for mixed variable-type data according to Z.Huang (1998): Extensions to the
k-Means Algorithm for Clustering Large Data Sets with Categorical Variables,
Data Mining and Knowledge Discovery 2, 283-304.")
    (license license:gpl2+)))

(define-public r-clustmd
  (package
    (name "r-clustmd")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clustMD" version))
       (sha256
        (base32 "0w4s9dab2mm5x0xibyl6s101c64if945a2cmwin9psd95p76mcny"))))
    (properties `((upstream-name . "clustMD")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis
                             r-truncnorm
                             r-reshape2
                             r-mvtnorm
                             r-msm
                             r-mclust
                             r-mass
                             r-ggplot2))
    (home-page "https://cran.r-project.org/package=clustMD")
    (synopsis "Model Based Clustering for Mixed Data")
    (description
     "Model-based clustering of mixed data (i.e.  data which consist of continuous,
binary, ordinal or nominal variables) using a parsimonious mixture of latent
Gaussian variable models.")
    (license license:gpl2)))

(define-public r-clustmc
  (package
    (name "r-clustmc")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClustMC" version))
       (sha256
        (base32 "1b7l5b9h93qyfh8bbk70a0cyrv4d37vm2d141y743d3vyr711l8y"))))
    (properties `((upstream-name . "ClustMC")))
    (build-system r-build-system)
    (propagated-inputs (list r-usedist
                             r-psych
                             r-procs
                             r-magrittr
                             r-lifecycle
                             r-dplyr
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/SGS2000/ClustMC")
    (synopsis "Cluster-Based Multiple Comparisons")
    (description
     "Multiple comparison techniques are typically applied following an F test from an
ANOVA to decide which means are significantly different from one another.  As an
alternative to traditional methods, cluster analysis can be performed to group
the means of different treatments into non-overlapping clusters.  Treatments in
different groups are considered statistically different.  Several approaches
have been proposed, with varying clustering methods and cut-off criteria.  This
package implements cluster-based multiple comparisons tests and also provides a
visual representation in the form of a dendrogram.  Di Rienzo, J. A., Guzman, A.
W., & Casanoves, F. (2002) <jstor.org/stable/1400690>.  Bautista, M. G., Smith,
D. W., & Steiner, R. L. (1997) <doi:10.2307/1400402>.")
    (license license:expat)))

(define-public r-clustlearn
  (package
    (name "r-clustlearn")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clustlearn" version))
       (sha256
        (base32 "11f82p777n5qwiqig2anyi6dxpb75kkgslkq7ii3v9h111jk303m"))))
    (properties `((upstream-name . "clustlearn")))
    (build-system r-build-system)
    (propagated-inputs (list r-proxy r-cli))
    (home-page "https://github.com/Ediu3095/clustlearn")
    (synopsis "Learn Clustering Techniques Through Examples and Code")
    (description
     "Clustering methods, which (if asked) can provide step-by-step explanations of
the algorithms used, as described in Ezugwu et.  al., (2022)
<doi:10.1016/j.engappai.2022.104743>; and datasets to test them on, which
highlight the strengths and weaknesses of each technique, as presented in the
clustering section of scikit-learn (Pedregosa et al., 2011)
<https://jmlr.csail.mit.edu/papers/v12/pedregosa11a.html>.")
    (license license:expat)))

(define-public r-clustimpute
  (package
    (name "r-clustimpute")
    (version "0.2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClustImpute" version))
       (sha256
        (base32 "0ss7zsnamh8ir2wpgy6swxck93yr4dd7g7hvyzc1cv6g3k28fb49"))))
    (properties `((upstream-name . "ClustImpute")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rlang
                             r-magrittr
                             r-knitr
                             r-ggplot2
                             r-dplyr
                             r-copula
                             r-clusterr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ClustImpute")
    (synopsis "K-Means Clustering with Build-in Missing Data Imputation")
    (description
     "This k-means algorithm is able to cluster data with missing values and as a
by-product completes the data set.  The implementation can deal with missing
values in multiple variables and is computationally efficient since it
iteratively uses the current cluster assignment to define a plausible
distribution for missing value imputation.  Weights are used to shrink early
random draws for missing values (i.e., draws based on the cluster assignments
after few iterations) towards the global mean of each feature.  This shrinkage
slowly fades out after a fixed number of iterations to reflect the increasing
credibility of cluster assignments.  See the vignette for details.")
    (license license:gpl3)))

(define-public r-clustgeo
  (package
    (name "r-clustgeo")
    (version "2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClustGeo" version))
       (sha256
        (base32 "03f7appg9n90ahzjhh5si9iv1vm06im9qmhgfc72fvqrmvqy2alh"))))
    (properties `((upstream-name . "ClustGeo")))
    (build-system r-build-system)
    (propagated-inputs (list r-spdep r-sp))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ClustGeo")
    (synopsis "Hierarchical Clustering with Spatial Constraints")
    (description
     "This package implements a Ward-like hierarchical clustering algorithm including
soft spatial/geographical constraints.")
    (license license:gpl2+)))

(define-public r-clustervar
  (package
    (name "r-clustervar")
    (version "0.0.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClusterVAR" version))
       (sha256
        (base32 "1596imfnk0kfygw3p7pcn3wkcppkq15rqvm1sdn3kfykwcb794jr"))))
    (properties `((upstream-name . "ClusterVAR")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales
                             r-parabar
                             r-mvtnorm
                             r-mass
                             r-iterators
                             r-foreach
                             r-fastdummies
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=ClusterVAR")
    (synopsis "Fitting Latent Class Vector-Autoregressive (VAR) Models")
    (description
     "Estimates latent class vector-autoregressive models via EM algorithm on
time-series data for model-based clustering and classification.  Includes model
selection criteria for selecting the number of lags and clusters.")
    (license license:gpl2)))

(define-public r-clustertend
  (package
    (name "r-clustertend")
    (version "1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clustertend" version))
       (sha256
        (base32 "0zhpx8lg7cxywin9j5kglj2had20wy3mwwgjygv2gjibj7a6i3cl"))))
    (properties `((upstream-name . "clustertend")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=clustertend")
    (synopsis "Check the Clustering Tendency")
    (description
     "Calculate some statistics aiming to help analyzing the clustering tendency of
given data.  In the first version, Hopkins statistic is implemented.  See
Hopkins and Skellam (1954) <doi:10.1093/oxfordjournals.aob.a083391>.")
    (license license:expat)))

(define-public r-clusterstability
  (package
    (name "r-clusterstability")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClusterStability" version))
       (sha256
        (base32 "1y88dv7n2cxm5w9pbg36dvx55nzvsnq4vbmx401147xr5p03yk9w"))))
    (properties `((upstream-name . "ClusterStability")))
    (build-system r-build-system)
    (propagated-inputs (list r-weightedcluster r-rcpp r-copula r-cluster))
    (home-page "https://cran.r-project.org/package=ClusterStability")
    (synopsis
     "Assessment of Stability of Individual Objects or Clusters in Partitioning Solutions")
    (description
     "Allows one to assess the stability of individual objects, clusters and whole
clustering solutions based on repeated runs of the K-means and K-medoids
partitioning algorithms.")
    (license license:gpl3)))

(define-public r-clustersim
  (package
    (name "r-clustersim")
    (version "0.51-5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clusterSim" version))
       (sha256
        (base32 "1lkq2dylimigfpvl4981a6xnn9bi462g0bbfkjz90sak9azzlnwx"))))
    (properties `((upstream-name . "clusterSim")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-e1071 r-cluster r-ade4))
    (home-page "https://cran.r-project.org/package=clusterSim")
    (synopsis "Searching for Optimal Clustering Procedure for a Data Set")
    (description
     "Distance measures (GDM1, GDM2,	Sokal-Michener, Bray-Curtis, for symbolic
interval-valued data), cluster quality indices (Calinski-Harabasz, Baker-Hubert,
Hubert-Levine, Silhouette, Krzanowski-Lai, Hartigan, Gap,	Davies-Bouldin),	data
normalization formulas (metric data, interval-valued symbolic data), data
generation (typical and non-typical data), HI@code{NoV} method,	replication
analysis, linear ordering methods, spectral clustering, agreement indices
between two partitions, plot functions (for categorical and symbolic
interval-valued data). (MILLIGAN, G.W., COOPER, M.C. (1985)
<doi:10.1007/BF02294245>, HUBERT, L., ARABIE, P. (1985)
<doi:10.1007%2FBF01908075>, RAND, W.M. (1971)
<doi:10.1080/01621459.1971.10482356>, JAJUGA, K., WALESIAK, M. (2000)
<doi:10.1007/978-3-642-57280-7_11>, MILLIGAN, G.W., COOPER, M.C. (1988)
<doi:10.1007/BF01897163>, JAJUGA, K., WALESIAK, M., BAK, A. (2003)
<doi:10.1007/978-3-642-55721-7_12>, DAVIES, D.L., BOULDIN, D.W. (1979)
<doi:10.1109/TPAMI.1979.4766909>, CALINSKI, T., HARABASZ, J. (1974)
<doi:10.1080/03610927408827101>, HUBERT, L. (1974)
<doi:10.1080/01621459.1974.10480191>, TIBSHIRANI, R., WALTHER, G., HASTIE, T.
(2001) <doi:10.1111/1467-9868.00293>, BRECKENRIDGE, J.N. (2000)
<doi:10.1207/S15327906MBR3502_5>, WALESIAK, M., DUDEK, A. (2008)
<doi:10.1007/978-3-540-78246-9_11>).")
    (license license:gpl2+)))

(define-public r-clusterses
  (package
    (name "r-clusterses")
    (version "2.6.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clusterSEs" version))
       (sha256
        (base32 "0d8b79mg0wxfpmx3xq22p9apa2cs2ylbml7lf37w386s6kdgz7ns"))))
    (properties `((upstream-name . "clusterSEs")))
    (build-system r-build-system)
    (propagated-inputs (list r-sandwich
                             r-plm
                             r-mlogit
                             r-lmtest
                             r-formula
                             r-dfidx
                             r-aer))
    (home-page "https://cran.r-project.org/package=clusterSEs")
    (synopsis "Calculate Cluster-Robust p-Values and Confidence Intervals")
    (description
     "Calculate p-values and confidence intervals using cluster-adjusted t-statistics
(based on Ibragimov and Muller (2010) <DOI:10.1198/jbes.2009.08046>, pairs
cluster bootstrapped t-statistics, and wild cluster bootstrapped t-statistics
(the latter two techniques based on Cameron, Gelbach, and Miller (2008)
<DOI:10.1162/rest.90.3.414>.  Procedures are included for use with GLM, ivreg,
plm (pooling or fixed effects), and mlogit models.")
    (license license:gpl2+)))

(define-public r-clusterrepro
  (package
    (name "r-clusterrepro")
    (version "0.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clusterRepro" version))
       (sha256
        (base32 "0s7qqvaf5yxxwhw6qyzfmk65c49yz405gljarwav6aglkx9883cl"))))
    (properties `((upstream-name . "clusterRepro")))
    (build-system r-build-system)
    (home-page "https://www.ncbi.nlm.nih.gov/pubmed/16613834.")
    (synopsis "Reproducibility of Gene Expression Clusters")
    (description
     "This is a function for validating microarray clusters via reproducibility, based
on the paper referenced below.")
    (license license:gpl2)))

(define-public r-clusterranktest
  (package
    (name "r-clusterranktest")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClusterRankTest" version))
       (sha256
        (base32 "01gzalhibqcdx3a6yc2cm1v77rscva73v5m5m0qkrgqdp9c8ph2a"))))
    (properties `((upstream-name . "ClusterRankTest")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ClusterRankTest")
    (synopsis "Rank Tests for Clustered Data")
    (description
     "Nonparametric rank based tests (rank-sum tests and signed-rank tests) for
clustered data, especially useful for clusters having informative cluster size
and intra-cluster group size.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-clusternomics
  (package
    (name "r-clusternomics")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clusternomics" version))
       (sha256
        (base32 "05nkw6h2dvky07fj50myzw5xlkqyiflbn4vwqw8a1q2idv4awi7b"))))
    (properties `((upstream-name . "clusternomics")))
    (build-system r-build-system)
    (propagated-inputs (list r-plyr r-mass r-magrittr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/evelinag/clusternomics")
    (synopsis "Integrative Clustering for Heterogeneous Biomedical Datasets")
    (description
     "Integrative context-dependent clustering for heterogeneous biomedical datasets.
Identifies local clustering structures in related datasets, and a global
clusters that exist across the datasets.")
    (license license:expat)))

(define-public r-clustermq
  (package
    (name "r-clustermq")
    (version "0.9.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clustermq" version))
       (sha256
        (base32 "1zr3na4if3a6za0fmx37slz3gjhgddc6ca78mvmgfi7n9wlczhyx"))))
    (properties `((upstream-name . "clustermq")))
    (build-system r-build-system)
    (inputs (list zlib))
    (propagated-inputs (list r-rcpp r-r6 r-progress r-narray r-globals))
    (native-inputs (list pkg-config r-knitr))
    (home-page "https://mschubert.github.io/clustermq/")
    (synopsis
     "Evaluate Function Calls on HPC Schedulers (LSF, SGE, SLURM, PBS/Torque)")
    (description
     "Evaluate arbitrary function calls using workers on HPC schedulers in single line
of code.  All processing is done on the network without accessing the file
system.  Remote schedulers are supported via SSH.")
    (license (list license:asl2.0
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-clustermole
  (package
    (name "r-clustermole")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clustermole" version))
       (sha256
        (base32 "1wfnv93b5rrdpad64gc3sv919yis92xa03ja29lsvcmkiqpbjsq9"))))
    (properties `((upstream-name . "clustermole")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-singscore
                             r-rlang
                             r-magrittr
                             r-gsva
                             r-gseabase
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://igordot.github.io/clustermole/")
    (synopsis
     "Unbiased Single-Cell Transcriptomic Data Cell Type Identification")
    (description
     "Assignment of cell type labels to single-cell RNA sequencing (@code{scRNA-seq})
clusters is often a time-consuming process that involves manual inspection of
the cluster marker genes complemented with a detailed literature search.  This
is especially challenging when unexpected or poorly described populations are
present.  The clustermole R package provides methods to query thousands of human
and mouse cell identity markers sourced from a variety of databases.")
    (license license:expat)))

(define-public r-clustermi
  (package
    (name "r-clustermi")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clusterMI" version))
       (sha256
        (base32 "0irc1fcsvwkyv1g9zyjk9l6hmr1mj78rlndkd2ggg44r22mc1p0m"))))
    (properties `((upstream-name . "clusterMI")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr
                             r-rfast
                             r-reshape2
                             r-rcpparmadillo
                             r-rcpp
                             r-npbayesimputecat
                             r-mix
                             r-micemd
                             r-mice
                             r-mclust
                             r-knockoff
                             r-gridextra
                             r-glmnet
                             r-ggplot2
                             r-fpc
                             r-factominer
                             r-e1071
                             r-dicer
                             r-clusterr
                             r-cat))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=clusterMI")
    (synopsis "Cluster Analysis with Missing Values by Multiple Imputation")
    (description
     "Allows clustering of incomplete observations by addressing missing values using
multiple imputation.  For achieving this goal, the methodology consists in three
steps, following Audigier and Niang 2022 <doi:10.1007/s11634-022-00519-1>.  I)
Missing data imputation using dedicated models.  Four multiple imputation
methods are proposed, two are based on joint modelling and two are fully
sequential methods, as discussed in Audigier et al. (2021)
<doi:10.48550/@code{arXiv.2106.04424>}.  II) cluster analysis of imputed data
sets.  Six clustering methods are available (distances-based or model-based),
but custom methods can also be easily used.  III) Partition pooling.  The set of
partitions is aggregated using Non-negative Matrix Factorization based method.
An associated instability measure is computed by bootstrap (see Fang, Y. and
Wang, J., 2012 <doi:10.1016/j.csda.2011.09.003>).  Among applications, this
instability measure can be used to choose a number of clusters with missing
values.  The package also proposes several diagnostic tools to tune the number
of imputed data sets, to tune the number of iterations in fully sequential
imputation, to check the fit of imputation models, etc.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-clustering-sc-dp
  (package
    (name "r-clustering-sc-dp")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clustering.sc.dp" version))
       (sha256
        (base32 "0l5grxvjxzc89qn0nvd79ljzjp89vgxinms291hxzvgbid6yn5sc"))))
    (properties `((upstream-name . "clustering.sc.dp")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=clustering.sc.dp")
    (synopsis
     "Optimal Distance-Based Clustering for Multidimensional Data with Sequential Constraint")
    (description
     "This package provides a dynamic programming algorithm for optimal clustering
multidimensional data with sequential constraint.  The algorithm minimizes the
sum of squares of within-cluster distances.  The sequential constraint allows
only subsequent items of the input data to form a cluster.  The sequential
constraint is typically required in clustering data streams or items with time
stamps such as video frames, GPS signals of a vehicle, movement data of a
person, e-pen data, etc.  The algorithm represents an extension of Ckmeans.1d.dp
to multiple dimensional spaces.  Similarly to the one-dimensional case, the
algorithm guarantees optimality and repeatability of clustering.  Method
clustering.sc.dp() can find the optimal clustering if the number of clusters is
known.  Otherwise, methods findwithinss.sc.dp() and backtracking.sc.dp() can be
used.  See Szkaliczki, T. (2016) \"clustering.sc.dp: Optimal Clustering with
Sequential Constraint by Using Dynamic Programming\" <doi: 10.32614/RJ-2016-022>
for more information.")
    (license license:lgpl3+)))

(define-public r-clustering
  (package
    (name "r-clustering")
    (version "1.7.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Clustering" version))
       (sha256
        (base32 "051x3140xr8g0grlmsff4m8gfc613hrfgldy0a7nm0f9w90ragsx"))))
    (properties `((upstream-name . "Clustering")))
    (build-system r-build-system)
    (propagated-inputs (list r-xtable
                             r-toordinal
                             r-sqldf
                             r-shiny
                             r-pvclust
                             r-pracma
                             r-gmp
                             r-ggplot2
                             r-future
                             r-foreach
                             r-dplyr
                             r-data-table
                             r-clusterr
                             r-cluster
                             r-apcluster
                             r-amap))
    (home-page "https://github.com/laperez/clustering")
    (synopsis "Techniques for Evaluating Clustering")
    (description
     "The design of this package allows us to run different clustering packages and
compare the results between them, to determine which algorithm behaves best from
the data provided.  See Martos, L.A.P., GarcÃ­a-Vico, Ã.M., GonzÃ¡lez, P. et
al.(2023) <doi:10.1007/s13748-022-00294-2> \"Clustering: an R library to
facilitate the analysis and comparison of cluster algorithms.\", Martos, L.A.P.,
GarcÃ­a-Vico, Ã.M., GonzÃ¡lez, P. et al. \"A Multiclustering Evolutionary
Hyperrectangle-Based Algorithm\" <doi:10.1007/s44196-023-00341-3> and L.A.P.,
GarcÃ­a-Vico, Ã.M., GonzÃ¡lez, P. et al. \"An Evolutionary Fuzzy System for
Multiclustering in Data Streaming\" <doi:10.1016/j.procs.2023.12.058>.")
    (license license:gpl2+)))

(define-public r-clusterhd
  (package
    (name "r-clusterhd")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clusterHD" version))
       (sha256
        (base32 "16mk0bgvahxpjfawxkpjlfh9j1n5dldl6lhi7d1ssf5zaha35jkm"))))
    (properties `((upstream-name . "clusterHD")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-mclust r-cluster
                             r-ckmeans-1d-dp))
    (home-page "https://arxiv.org/abs/2010.00950")
    (synopsis "Tools for Clustering High-Dimensional Data")
    (description
     "This package provides tools for clustering high-dimensional data.  In
particular, it contains the methods described in
<doi:10.1093/bioinformatics/btaa243>, <@code{arXiv:2010.00950>}.")
    (license license:gpl2+)))

(define-public r-clusterhap
  (package
    (name "r-clusterhap")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clusterhap" version))
       (sha256
        (base32 "1ic6588mqp146jsvrxlxk449zw4n81xixgrny9r29497z7hg5a1m"))))
    (properties `((upstream-name . "clusterhap")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=clusterhap")
    (synopsis "Clustering Genotypes in Haplotypes")
    (description
     "One haplotype is a combination of SNP (Single Nucleotide Polymorphisms) within
the QTL (Quantitative Trait Loci).  clusterhap groups together all individuals
of a population with the same haplotype.  Each group contains individual with
the same allele in each SNP, whether or not missing data.  Thus, clusterhap
groups individuals, that to be imputed, have a non-zero probability of having
the same alleles in the entire sequence of SNP's.  Moreover, clusterhap
calculates such probability from relative frequencies.")
    (license license:gpl3)))

(define-public r-clusteredmutations
  (package
    (name "r-clusteredmutations")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClusteredMutations" version))
       (sha256
        (base32 "1n31nnvpjh1faw751k8m3ga3wfl0yhdpnszwckqhfzlma1jr8z04"))))
    (properties `((upstream-name . "ClusteredMutations")))
    (build-system r-build-system)
    (propagated-inputs (list r-seriation))
    (home-page "https://cran.r-project.org/package=ClusteredMutations")
    (synopsis "Location and Visualization of Clustered Somatic Mutations")
    (description
     "Identification and visualization of groups of closely spaced mutations in the
DNA sequence of cancer genome.  The extremely mutated zones are searched in the
symmetric dissimilarity matrix using the anti-Robinson matrix properties.
Different data sets are obtained to describe and plot the clustered mutations
information.")
    (license license:gpl3)))

(define-public r-clustercons
  (package
    (name "r-clustercons")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clusterCons" version))
       (sha256
        (base32 "1k1y6cqpb5fyi2mbx2i4jbiwz0fni44lnq0xnv3pl0x3dpscwh6q"))))
    (properties `((upstream-name . "clusterCons")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer r-lattice r-cluster r-apcluster))
    (home-page "https://github.com/biomedicalinformaticsgroup/clusterCons")
    (synopsis "Consensus Clustering using Multiple Algorithms and Parameters")
    (description
     "This package provides functions for calculation of robustness measures for
clusters and cluster membership based on generating consensus matrices from
bootstrapped clustering experiments in which a random proportion of rows of the
data set are used in each individual clustering.  This allows the user to
prioritise clusters and the members of clusters based on their consistency in
this regime.  The functions allow the user to select several algorithms to use
in the re-sampling scheme and with any of the parameters that the algorithm
would normally take.  See Simpson, T. I., Armstrong, J. D. & Jarman, A. P.
(2010) <doi:10.1186/1471-2105-11-590> and Monti, S., Tamayo, P., Mesirov, J. &
Golub, T. (2003) <doi:10.1023/a:1023949509487>.")
    (license license:gpl3+)))

(define-public r-clusterbootstrap
  (package
    (name "r-clusterbootstrap")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClusterBootstrap" version))
       (sha256
        (base32 "1ha50yzc2arlz4c2g7r9w891fk775xfbhz0gky3zxawlsa02213s"))))
    (properties `((upstream-name . "ClusterBootstrap")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-dplyr))
    (home-page "https://github.com/mathijsdeen/ClusterBootstrap")
    (synopsis
     "Analyze Clustered Data with Generalized Linear Models using the Cluster Bootstrap")
    (description
     "This package provides functionality for the analysis of clustered data using the
cluster bootstrap.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-clusterability
  (package
    (name "r-clusterability")
    (version "0.1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clusterability" version))
       (sha256
        (base32 "15gimcs6wrasafg1ys7id0mkg9fvacxbwpgg9d4b5avk4gff39bs"))))
    (properties `((upstream-name . "clusterability")))
    (build-system r-build-system)
    (propagated-inputs (list r-diptest))
    (home-page "https://cran.r-project.org/package=clusterability")
    (synopsis "Performs Tests for Cluster Tendency of a Data Set")
    (description
     "Test for cluster tendency (clusterability) of a data set.  The methods
implemented - reducing the data set to a single dimension using principal
component analysis or computing pairwise distances, and performing a
multimodality test like the Dip Test or Silverman's Critical Bandwidth Test -
are described in Adolfsson, Ackerman, and Brownstein (2019)
<doi:10.1016/j.patcog.2018.10.026>.  Such methods can inform whether clustering
algorithms are appropriate for a data set.")
    (license license:gpl2)))

(define-public r-cluster-obeu
  (package
    (name "r-cluster-obeu")
    (version "1.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Cluster.OBeu" version))
       (sha256
        (base32 "10i7mnaq968my1c5hi8bdsj05m64wlmrf4n4m118is5h1q7zss8r"))))
    (properties `((upstream-name . "Cluster.OBeu")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-reshape2
                             r-reshape
                             r-rcurl
                             r-mclust
                             r-jsonlite
                             r-dendextend
                             r-data-tree
                             r-clvalid
                             r-cluster
                             r-car))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/okgreece/Cluster.OBeu")
    (synopsis "Cluster Analysis 'OpenBudgets.eu'")
    (description
     "Estimate and return the needed parameters for visualisations designed for
@code{OpenBudgets} <http://openbudgets.eu/> data.  Calculate cluster analysis
measures in Budget data of municipalities across Europe, according to the
@code{OpenBudgets} data model.  It involves a set of techniques and algorithms
used to find and divide the data into groups of similar observations.  Also, can
be used generally to extract visualisation parameters convert them to JSON
format and use them as input in a different graphical interface.")
    (license (list license:gpl2
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-cluster-datasets
  (package
    (name "r-cluster-datasets")
    (version "1.0-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cluster.datasets" version))
       (sha256
        (base32 "0i68s9305q08fhynpq24qnlw03gg4hbk4184z3q3ycbi8njpr4il"))))
    (properties `((upstream-name . "cluster.datasets")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cluster.datasets")
    (synopsis "Cluster Analysis Data Sets")
    (description
     "This package provides a collection of data sets for teaching cluster analysis.")
    (license license:gpl2+)))

(define-public r-clusteff
  (package
    (name "r-clusteff")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clustEff" version))
       (sha256
        (base32 "1zgj7nq0rba51xkm88vj9w70glk8z8g3y1awlfv38kf37s2yrs5c"))))
    (properties `((upstream-name . "clustEff")))
    (build-system r-build-system)
    (propagated-inputs (list r-qrcm r-ggpubr r-ggplot2 r-fda r-cluster))
    (home-page "https://cran.r-project.org/package=clustEff")
    (synopsis "Clusters of Effects Curves in Quantile Regression Models")
    (description
     "Clustering method to cluster both effects curves, through quantile regression
coefficient modeling, and curves in functional data analysis.  Sottile G. and
Adelfio G. (2019) <doi:10.1007/s00180-018-0817-8>.")
    (license license:gpl2)))

(define-public r-clustcr2
  (package
    (name "r-clustcr2")
    (version "1.7.3.01")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClusTCR2" version))
       (sha256
        (base32 "1l54x7b9pkkmrdhry41qikyhhnsr2s669jdqmviskjljk9wyyyqi"))))
    (properties `((upstream-name . "ClusTCR2")))
    (build-system r-build-system)
    (propagated-inputs (list r-vlf
                             r-stringr
                             r-sna
                             r-scales
                             r-rcolorbrewer
                             r-plyr
                             r-network
                             r-ggseqlogo
                             r-ggplot2
                             r-desctools))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ClusTCR2")
    (synopsis
     "Identifying Similar T Cell Receptor Hyper-Variable Sequences with 'ClusTCR2'")
    (description
     "Enhancing T cell receptor (TCR) sequence analysis, @code{ClusTCR2}', based on
@code{ClusTCR} python program, leverages Hamming distance to compare the
complement-determining region three (CDR3) sequences for sequence similarity,
variable gene (V gene) and length.  The second step employs the Markov Cluster
Algorithm to identify clusters within an undirected graph, providing a summary
of amino acid motifs and matrix for generating network plots.  Tailored for
single-cell RNA-seq data with integrated TCR-seq information, @code{ClusTCR2} is
integrated into the Single Cell TCR and Expression Grouped Ontologies (STEGO) R
application or STEGO.R'.  See the two publications for more details.  Sebastiaan
Valkiers, Max Van Houcke, Kris Laukens, Pieter Meysman (2021)
<doi:10.1093/bioinformatics/btab446>, Kerry A. Mullan, My Ha, Sebastiaan
Valkiers, Nicky de Vrij, Benson Ogunjimi, Kris Laukens, Pieter Meysman (2023)
<doi:10.1101/2023.09.27.559702>.")
    (license license:gpl3+)))

(define-public r-clustblock
  (package
    (name "r-clustblock")
    (version "4.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClustBlock" version))
       (sha256
        (base32 "1gqq6wq79c6ikz8nxrahqdnl8g204y4sw82fvmrykh8xv3hzv2cp"))))
    (properties `((upstream-name . "ClustBlock")))
    (build-system r-build-system)
    (propagated-inputs (list r-factominer))
    (home-page "https://cran.r-project.org/package=ClustBlock")
    (synopsis "Clustering of Datasets")
    (description
     "Hierarchical and partitioning algorithms to cluster blocks of variables.  The
partitioning algorithm includes an option called noise cluster to set aside
atypical blocks of variables.  The CLUSTATIS method (for quantitative blocks)
(Llobell, Cariou, Vigneau, Labenne & Qannari (2020)
<doi:10.1016/j.foodqual.2018.05.013>, Llobell, Vigneau & Qannari (2019)
<doi:10.1016/j.foodqual.2019.02.017>) and the CLUSCATA method (for
Check-All-That-Apply data) (Llobell, Cariou, Vigneau, Labenne & Qannari (2019)
<doi:10.1016/j.foodqual.2018.09.006>, Llobell, Giacalone, Labenne & Qannari
(2019) <doi:10.1016/j.foodqual.2019.05.017>) are the core of this package.  The
CATATIS methods allows to compute some indices and tests to control the quality
of CATA data.  Multivariate analysis and clustering of subjects for quantitative
multiblock data, CATA, RATA, Free Sorting and JAR experiments are available.
Clustering of rows in multi-block context (notably with @code{ClusMB} strategy)
is also included.")
    (license license:gpl3)))

(define-public r-clustassess
  (package
    (name "r-clustassess")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClustAssess" version))
       (sha256
        (base32 "0b8p5dpb843rv8q1hsc74zhxyn9wjgdxwpwrbq2yx4jmy8v65gzq"))))
    (properties `((upstream-name . "ClustAssess")))
    (build-system r-build-system)
    (propagated-inputs (list r-uwot
                             r-stringr
                             r-rlang
                             r-reshape2
                             r-rcpp
                             r-progress
                             r-matrix
                             r-magrittr
                             r-irlba
                             r-igraph
                             r-ggplot2
                             r-foreach
                             r-fastcluster
                             r-dplyr
                             r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Core-Bioinformatics/ClustAssess")
    (synopsis "Tools for Assessing Clustering")
    (description
     "This package provides a set of tools for evaluating clustering robustness using
proportion of ambiguously clustered pairs (Senbabaoglu et al. (2014)
<doi:10.1038/srep06207>), as well as similarity across methods and method
stability using element-centric clustering comparison (Gates et al. (2019)
<doi:10.1038/s41598-019-44892-y>).  Additionally, this package enables
stability-based parameter assessment for graph-based clustering pipelines
typical in single-cell data analysis.")
    (license license:expat)))

(define-public r-clustanalytics
  (package
    (name "r-clustanalytics")
    (version "0.5.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clustAnalytics" version))
       (sha256
        (base32 "063n6s1q2kc7a42fajd2z0rd0v6dxs443hv1vlaq6xhli8l8cylk"))))
    (properties `((upstream-name . "clustAnalytics")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncnorm
                             r-rdpack
                             r-rcpp
                             r-mclust
                             r-mcclust
                             r-igraph
                             r-fossil
                             r-dplyr
                             r-boot
                             r-aricode))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/martirm/clustAnalytics")
    (synopsis "Cluster Evaluation on Graphs")
    (description
     "Evaluates the stability and significance of clusters on igraph graphs.  Supports
weighted and unweighted graphs.  Implements the cluster evaluation methods
defined by Arratia A, Renedo M (2021) <doi:10.7717/peerj-cs.600>.  Also includes
an implementation of the Reduced Mutual Information introduced by Newman et al.
(2020) <doi:10.1103/@code{PhysRevE.101.042304>}.")
    (license license:gpl3+)))

(define-public r-clust-bin-pair
  (package
    (name "r-clust-bin-pair")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clust.bin.pair" version))
       (sha256
        (base32 "11lqd3vmx4kg08n6iv9na8rra49dkldx4f8jyf43hppbjrbvfinm"))))
    (properties `((upstream-name . "clust.bin.pair")))
    (build-system r-build-system)
    (home-page "https://github.com/dgopstein/clust.bin.pair")
    (synopsis "Statistical Methods for Analyzing Clustered Matched Pair Data")
    (description
     "Tests, utilities, and case studies for analyzing significance in clustered
binary matched-pair data.  The central function clust.bin.pair uses one of
several tests to calculate a Chi-square statistic.  Implemented are the tests
Eliasziw (1991) <doi:10.1002/sim.4780101211>, Obuchowski (1998)
<doi:10.1002/(SICI)1097-0258(19980715)17:13%3C1495::AID-SIM863%3E3.0.CO;2-I>,
Durkalski (2003) <doi:10.1002/sim.1438>, and Yang (2010)
<doi:10.1002/bimj.201000035> with @code{McNemar} (1947) <doi:10.1007/BF02295996>
included for comparison.  The utility functions nested.to.contingency and
paired.to.contingency convert data between various useful formats.  Thyroids and
psychiatry are the canonical datasets from Obuchowski and Petryshen (1989)
<doi:10.1016/0165-1781(89)90196-0> respectively.")
    (license license:expat)))

(define-public r-clusscluster
  (package
    (name "r-clusscluster")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClussCluster" version))
       (sha256
        (base32 "1436849m2mnm8j7lf653zv8lcvvg2ch8kkks4bvr39kx21wxy8ss"))))
    (properties `((upstream-name . "ClussCluster")))
    (build-system r-build-system)
    (propagated-inputs (list r-venndiagram r-scales r-rlang r-reshape2
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ClussCluster")
    (synopsis
     "Simultaneous Detection of Clusters and Cluster-Specific Genes in High-Throughput Transcriptome Data")
    (description
     "This package implements a new method @code{ClussCluster} descried in Ge Jiang
and Jun Li, \"Simultaneous Detection of Clusters and Cluster-Specific Genes in
High-throughput Transcriptome Data\" (Unpublished).  Simultaneously perform
clustering analysis and signature 	gene selection on high-dimensional
transcriptome data sets. 	To do so, @code{ClussCluster} incorporates a
Lasso-type 	regularization penalty term to the objective function of K-	means so
that cell-type-specific signature genes can be 	identified while clustering the
cells.")
    (license license:gpl3)))

(define-public r-clusroc
  (package
    (name "r-clusroc")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClusROC" version))
       (sha256
        (base32 "055ppcnzwkapnyf9xvld4bvkccwf494gqcb2qq0vnsa8n6bz5k46"))))
    (properties `((upstream-name . "ClusROC")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgl
                             r-rcpparmadillo
                             r-rcpp
                             r-numderiv
                             r-nlme
                             r-iterators
                             r-ggpubr
                             r-ggplot2
                             r-foreach
                             r-ellipse
                             r-doparallel))
    (home-page "https://github.com/toduckhanh/ClusROC")
    (synopsis
     "ROC Analysis in Three-Class Classification Problems for Clustered Data")
    (description
     "Statistical methods for ROC surface analysis in three-class classification
problems for clustered data and in presence of covariates.  In particular, the
package allows to obtain covariate-specific point and interval estimation for:
(i) true class fractions (TCFs) at fixed pairs of thresholds; (ii) the ROC
surface; (iii) the volume under ROC surface (VUS); (iv) the optimal pairs of
thresholds.  Methods considered in points (i), (ii) and (iv) are proposed and
discussed in To et al. (2022) <doi:10.1177/09622802221089029>.  Referring to
point (iv), three different selection criteria are implemented: Generalized
Youden Index (GYI), Closest to Perfection (@code{CtP}) and Maximum Volume (MV).
Methods considered in point (iii) are proposed and discussed in Xiong et al.
(2018) <doi:10.1177/0962280217742539>.  Visualization tools are also provided.
We refer readers to the articles cited above for all details.")
    (license license:gpl3)))

(define-public r-clusrank
  (package
    (name "r-clusrank")
    (version "1.0-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clusrank" version))
       (sha256
        (base32 "194h15ggymnzm70wm5w6xwjdjl0d7k2hnr5b93zhhncy3jrd590g"))))
    (properties `((upstream-name . "clusrank")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-mass))
    (home-page "https://github.com/wenjie2wang/clusrank")
    (synopsis "Wilcoxon Rank Tests for Clustered Data")
    (description
     "Non-parametric tests (Wilcoxon rank sum test and Wilcoxon signed rank test) for
clustered data documented in Jiang et.  al (2020) <doi:10.18637/jss.v096.i06>.")
    (license license:gpl3+)))

(define-public r-cluspred
  (package
    (name "r-cluspred")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClusPred" version))
       (sha256
        (base32 "12pm5vkfxpaincv9ajid0p07l0mjc2kfqqfg0ls2pcxmmkh8wwb4"))))
    (properties `((upstream-name . "ClusPred")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam
                             r-rcpparmadillo
                             r-rcpp
                             r-quantreg
                             r-aldqr
                             r-ald))
    (home-page "https://arxiv.org/abs/2012.14159")
    (synopsis
     "Simultaneous Semi-Parametric Estimation of Clustering and Regression")
    (description
     "Parameter estimation of regression models with fixed group effects, when the
group variable is missing while group-related variables are available.
Parametric and semi-parametric approaches described in Marbac et al. (2020)
<@code{arXiv:2012.14159>} are implemented.")
    (license license:gpl2+)))

(define-public r-clusevol
  (package
    (name "r-clusevol")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clusEvol" version))
       (sha256
        (base32 "192zi43flpwfazgjd5ci0620hbad77z6s527vp6qwywcly3aqxmw"))))
    (properties `((upstream-name . "clusEvol")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis
                             r-plotly
                             r-ggplot2
                             r-fpc
                             r-dplyr
                             r-clustersim
                             r-cluster))
    (home-page "https://github.com/vmoprojs/clusEvol")
    (synopsis "Procedure for Cluster Evolution Analytics")
    (description
     "Cluster Evolution Analytics allows us to use exploratory what if questions in
the sense that the present information of an object is plugged-in a dataset in a
previous time frame so that we can explore its evolution (and of its neighbors)
to the present.  See the URL for the papers associated with this package, as for
instance, Morales-OÃ±ate and Morales-OÃ±ate (2024)
<https://mpra.ub.uni-muenchen.de/120220>.")
    (license license:gpl3+)))

(define-public r-cluscov
  (package
    (name "r-cluscov")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cluscov" version))
       (sha256
        (base32 "0345v5r6b53243h5bir29v0w77pmwjqjkqfrjnk5j5r1wbh98q1w"))))
    (properties `((upstream-name . "cluscov")))
    (build-system r-build-system)
    (propagated-inputs (list r-quantreg r-mass))
    (home-page "https://cran.r-project.org/package=cluscov")
    (synopsis "Clustered Covariate Regression")
    (description
     "Clustered covariate regression enables estimation and inference in both linear
and non-linear models with linear predictor functions even when the design
matrix is column rank deficient.  Routines in this package implement algorithms
in Soale and Tsyawo (2019) <doi:10.13140/RG.2.2.32355.81441>.")
    (license license:gpl2)))

(define-public r-clusboot
  (package
    (name "r-clusboot")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClusBoot" version))
       (sha256
        (base32 "08b3mw4r20z6d6d7w0rmzsz3f11icpzmca5fv7p1mk1m0l1nckfw"))))
    (properties `((upstream-name . "ClusBoot")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ClusBoot")
    (synopsis
     "Bootstrap a Clustering Solution to Establish the Stability of the Clusters")
    (description
     "Providing a cluster allocation for n samples, either with an $n \\times p$ data
matrix or an $n \\times n$ distance matrix, a bootstrap procedure is performed.
The proportion of bootstrap replicates where a pair of samples cluster in the
same cluster indicates who tightly the samples in a particular cluster clusters
together.")
    (license license:expat)))

(define-public r-clump
  (package
    (name "r-clump")
    (version "0.8.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CluMP" version))
       (sha256
        (base32 "1vpxl2rcknqx32b94b48iirkh7r7cdri9mcljrw29gsbvhrfc46k"))))
    (properties `((upstream-name . "CluMP")))
    (build-system r-build-system)
    (propagated-inputs (list r-tableone
                             r-rlang
                             r-nbclust
                             r-mass
                             r-ggplot2
                             r-dplyr
                             r-data-table
                             r-amap))
    (home-page "https://arxiv.org/ftp/arxiv/papers/1807/1807.05926.pdf")
    (synopsis "Clustering of Micro Panel Data")
    (description
     "Two-step feature-based clustering method designed for micro panel (longitudinal)
data with the artificial panel data generator.  See Sobisek, Stachova, Fojtik
(2018) <@code{arXiv:1807.05926>}.")
    (license license:gpl3+)))

(define-public r-clugenr
  (package
    (name "r-clugenr")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clugenr" version))
       (sha256
        (base32 "0wqhqy6ivhz0nhl0gr5gcxqdvi5ha4mhqgvgjmgaqibpi03dy3l8"))))
    (properties `((upstream-name . "clugenr")))
    (build-system r-build-system)
    (propagated-inputs (list r-mathjaxr))
    (native-inputs (list r-knitr))
    (home-page "https://clugen.github.io/clugenr/")
    (synopsis "Multidimensional Cluster Generation Using Support Lines")
    (description
     "An implementation of the clugen algorithm for generating multidimensional
clusters with arbitrary distributions.  Each cluster is supported by a line
segment, the position, orientation and length of which guide where the
respective points are placed.  This package is described in Fachada & de Andrade
(2023) <doi:10.1016/j.knosys.2023.110836>.")
    (license license:expat)))

(define-public r-cluer
  (package
    (name "r-cluer")
    (version "1.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClueR" version))
       (sha256
        (base32 "0zj75q4aqkf6l7720cc38rjx51lmqfp6gmgxp7pkk2ixdlpmh3sy"))))
    (properties `((upstream-name . "ClueR")))
    (build-system r-build-system)
    (propagated-inputs (list r-e1071))
    (home-page "https://cran.r-project.org/package=ClueR")
    (synopsis "Cluster Evaluation")
    (description
     "CLUster Evaluation (CLUE) is a computational method for identifying optimal
number of clusters in a given time-course dataset clustered by cmeans or kmeans
algorithms and subsequently identify key kinases or pathways from each cluster.
Its implementation in R is called @code{ClueR}.  See README on
<https://github.com/P@code{YangLab/ClueR>} for more details.  P Yang et al.
(2015) <doi:10.1371/journal.pcbi.1004403>.")
    (license license:gpl3)))

(define-public r-clubpro
  (package
    (name "r-clubpro")
    (version "0.6.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clubpro" version))
       (sha256
        (base32 "0p407zd2gr4yxxpa97c37yxrvdkid00qf1ird58yl44wrwszh90w"))))
    (properties `((upstream-name . "clubpro")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppprogress r-rcpparmadillo r-rcpp r-lattice))
    (native-inputs (list r-knitr))
    (home-page "https://timbeechey.github.io/clubpro/")
    (synopsis "Classification Using Binary Procrustes Rotation")
    (description
     "This package implements a classification method described by Grice (2011,
ISBN:978-0-12-385194-9) using binary procrustes rotation; a simplified version
of procrustes rotation.")
    (license license:gpl3+)))

(define-public r-clttools
  (package
    (name "r-clttools")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clttools" version))
       (sha256
        (base32 "0va9k1b4xsb2sgpxzvid6sa8m6b8i3r4kgghclmb78nnrs480cwi"))))
    (properties `((upstream-name . "clttools")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=clttools")
    (synopsis "Central Limit Theorem Experiments (Theoretical and Simulation)")
    (description
     "Central limit theorem experiments presented by data frames or plots.  Functions
include generating theoretical sample space, corresponding probability, and
simulated results as well.")
    (license license:gpl2)))

(define-public r-clsiep15
  (package
    (name "r-clsiep15")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CLSIEP15" version))
       (sha256
        (base32 "0qh9rlw89sjjmidhb84cb4jawxj6x2nhrgbwhrzw5qyx570dgwgb"))))
    (properties `((upstream-name . "CLSIEP15")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CLSIEP15")
    (synopsis
     "Clinical and Laboratory Standards Institute (CLSI) EP15-A3 Calculations")
    (description
     "Calculations of \"EP15-A3 document.  A manual for user verification of precision
and estimation of bias\" CLSI (2014, ISBN:1-56238-966-1).")
    (license license:expat)))

(define-public r-clrng
  (package
    (name "r-clrng")
    (version "0.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clrng" version))
       (sha256
        (base32 "18brzhpivgzmvvjqkbkmrzw52ylz3d9l02l88020rb18pgr78clp"))))
    (properties `((upstream-name . "clrng")))
    (build-system r-build-system)
    (propagated-inputs (list r-rviennacl r-rcppeigen r-rcpp r-gpur))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=clrng")
    (synopsis "Parallel Random Number Generation on GPU")
    (description
     "Builds on @code{gpuR} and utilizes the @code{clRNG} ('@code{OpenCL}') library to
provide efficient tools to generate independent random numbers in parallel on a
GPU and save the results as R objects, ensuring high-quality random numbers even
when R is used interactively or in an ad-hoc manner.  Includes Fisher's
simulation method adapted from Patefield, William M (1981) <doi:10.2307/2346669>
and MRG31k3p Random Number Generator from @code{clRNG} library by Advanced Micro
Devices, Inc. (2015) <https://github.com/@code{clMathLibraries/clRNG>}.")
    (license license:gpl3)))

(define-public r-clr
  (package
    (name "r-clr")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clr" version))
       (sha256
        (base32 "088ks9lrhlyvg3yvlfmb0091yp6qp5bzg9h5r6ryv3bk6y56sajx"))))
    (properties `((upstream-name . "clr")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-lubridate r-dplyr))
    (home-page "https://cran.r-project.org/package=clr")
    (synopsis "Curve Linear Regression via Dimension Reduction")
    (description
     "This package provides a new methodology for linear regression with both curve
response and curve regressors, which is described in Cho, Goude, Brossat and Yao
(2013) <doi:10.1080/01621459.2012.722900> and (2015)
<doi:10.1007/978-3-319-18732-7_3>.  The key idea behind this methodology is
dimension reduction based on a singular value decomposition in a Hilbert space,
which reduces the curve regression problem to several scalar linear regression
problems.")
    (license license:lgpl2.0+)))

(define-public r-clptheory
  (package
    (name "r-clptheory")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clptheory" version))
       (sha256
        (base32 "1ix3yh4w97llx8dw2pp1gpwgrfag2zr4wb2hp3z3j3ggs587yic4"))))
    (properties `((upstream-name . "clptheory")))
    (build-system r-build-system)
    (propagated-inputs (list r-popdemo r-magrittr r-dplyr r-car))
    (home-page "https://github.com/dbasu-umass/clptheory/")
    (synopsis "Compute Price of Production and Labor Values")
    (description
     "Computes the uniform rate of profit, the vector of price of production and the
vector of labor values; and also compute measures of deviation between relative
prices of production and relative values.
<https://scholarworks.umass.edu/econ_workingpaper/347/>.  You provide the
input-output data and clptheory does the calculations for you.")
    (license license:expat)))

(define-public r-cloudutil
  (package
    (name "r-cloudutil")
    (version "0.1.12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cloudUtil" version))
       (sha256
        (base32 "18g946j00anlk20d0fh01w0xyj1kwyy7jhlgz5a85wmp6s2gkz74"))))
    (properties `((upstream-name . "cloudUtil")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cloudUtil")
    (synopsis "Cloud Utilization Plots")
    (description
     "This package provides means of plots for comparing utilization data of compute
systems.")
    (license license:gpl2)))

(define-public r-cloudstor
  (package
    (name "r-cloudstor")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cloudstoR" version))
       (sha256
        (base32 "0x9pl9x5sjs5vwcz5i1r5ymyv3rlv9adjc5y9kvxljdxgvnv6i08"))))
    (properties `((upstream-name . "cloudstoR")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml
                             r-rio
                             r-keyring
                             r-httr
                             r-getpass
                             r-curl
                             r-cli))
    (home-page "https://pdparker.github.io/cloudstoR/")
    (synopsis "Simplifies Access to Cloudstor API")
    (description
     "Access Cloudstor via their @code{WebDAV} API. This package can read, write, and
navigate Cloudstor from R.")
    (license license:gpl3+)))

(define-public r-cloudos
  (package
    (name "r-cloudos")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cloudos" version))
       (sha256
        (base32 "0d6lg7y58w62ikwm83xvc8wky396y4xs5cx3cfn1wxnsnrs462d1"))))
    (properties `((upstream-name . "cloudos")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-rappdirs
                             r-jsonlite
                             r-httr
                             r-ggplot2
                             r-dplyr))
    (home-page "https://github.com/lifebit-ai/cloudos")
    (synopsis "R Client Library for CloudOS")
    (description
     "The @code{CloudOS} client library for R makes it easy to interact with
@code{CloudOS} in the R environment for analysis.")
    (license license:expat)))

(define-public r-cloudml
  (package
    (name "r-cloudml")
    (version "0.6.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cloudml" version))
       (sha256
        (base32 "1j15q9yb2rc4fbjxfh21fiq6is8dnb8nfyi7g8iazgfwb3p9ahpx"))))
    (properties `((upstream-name . "cloudml")))
    (build-system r-build-system)
    (inputs (list python))
    (propagated-inputs (list r-yaml
                             r-withr
                             r-tfruns
                             r-rstudioapi
                             r-rprojroot
                             r-processx
                             r-packrat
                             r-jsonlite
                             r-config))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cloudml")
    (synopsis "Interface to the Google Cloud Machine Learning Platform")
    (description
     "Interface to the Google Cloud Machine Learning Platform
<https://cloud.google.com/ml-engine>, which provides cloud tools for training
machine learning models.")
    (license license:asl2.0)))

(define-public r-cloudfs
  (package
    (name "r-cloudfs")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cloudfs" version))
       (sha256
        (base32 "0qrx46q2vryfq88w6b8s1wzck4kx0hln41l98q65la1wnfn1ck0q"))))
    (properties `((upstream-name . "cloudfs")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-httr
                             r-googledrive
                             r-glue
                             r-dplyr
                             r-desc
                             r-cli
                             r-aws-s3))
    (native-inputs (list r-knitr))
    (home-page "https://g6t.github.io/cloudfs/")
    (synopsis "Streamlined Interface to Interact with Cloud Storage Platforms")
    (description
     "This package provides a unified interface for simplifying cloud storage
interactions, including uploading, downloading, reading, and writing files, with
functions for both Google Drive (<https://www.google.com/drive/>) and Amazon S3
(<https://aws.amazon.com/s3/>).")
    (license license:expat)))

(define-public r-closeloop
  (package
    (name "r-closeloop")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "closeloop" version))
       (sha256
        (base32 "1imwd16im4wvnha24gk453xrqq0bhhhbnn21pimfq0v02lj0248w"))))
    (properties `((upstream-name . "closeloop")))
    (build-system r-build-system)
    (propagated-inputs (list r-combinat))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/heorlytics/closeloop")
    (synopsis
     "Integrate Single-Arm Observational Data in Network Meta Analysis")
    (description
     "Calculate the distance between single-arm observational studies using covariate
information to remove heterogeneity in Network Meta-Analysis (NMA) of randomized
clinical trials.  Facilitate the inclusion of observational data in NMA,
enhancing the comprehensiveness and robustness of comparative effectiveness
research.  Schmitz (2018) <doi:10.1186/s12874-018-0509-7>.")
    (license license:expat)))

(define-public r-clordr
  (package
    (name "r-clordr")
    (version "1.7.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clordr" version))
       (sha256
        (base32 "0lrws22aijsfdr595g2dfxsvnvbq6bs18glbdc07qkb27kcpvv1p"))))
    (properties `((upstream-name . "clordr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tmvmixnorm
                             r-rootsolve
                             r-pbivnorm
                             r-mass
                             r-foreach
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=clordr")
    (synopsis
     "Composite Likelihood Inference and Diagnostics for Replicated Spatial Ordinal Data")
    (description
     "Composite likelihood parameter estimate and asymptotic covariance matrix are
calculated for the spatial ordinal data with replications, where spatial ordinal
response with covariate and both spatial exponential covariance within subject
and independent and identically distributed measurement error.  Parameter
estimation can be performed by either solving the gradient function or
maximizing composite log-likelihood.  Parametric bootstrapping is used to
estimate the Godambe information matrix and hence the asymptotic standard error
and covariance matrix with parallel processing option.  Moreover, the proposed
surrogate residual, which extends the results of Liu and Zhang (2017) <doi:
10.1080/01621459.2017.1292915>, can act as a useful tool for model diagnostics.")
    (license license:gpl2)))

(define-public r-clonetv2
  (package
    (name "r-clonetv2")
    (version "2.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CLONETv2" version))
       (sha256
        (base32 "1axkkagydpxdrz7ypw3x7bavaxk34lzj9bsdn1nah9nfr3cdia6h"))))
    (properties `((upstream-name . "CLONETv2")))
    (build-system r-build-system)
    (propagated-inputs (list r-sets r-ggrepel r-ggplot2 r-dbscan r-arules))
    (home-page "https://cran.r-project.org/package=CLONETv2")
    (synopsis "Clonality Estimates in Tumor")
    (description
     "Analyze data from next-generation sequencing experiments on genomic samples.
CLONETv2 offers a set of functions to compute allele specific copy number and
clonality from segmented data and SNPs position pileup.  The package has also
calculated the clonality of single nucleotide variants given read counts at
mutated positions.  The package has been developed at the laboratory of
Computational and Functional Oncology, Department of CIBIO, University of Trento
(Italy), under the supervision of prof Francesca Demichelis.  References: Prandi
et al. (2014) <doi:10.1186/s13059-014-0439-6>; Carreira et al. (2014)
<doi:10.1126/scitranslmed.3009448>; Romanel et al. (2015)
<doi:10.1126/scitranslmed.aac9511>.")
    (license license:expat)))

(define-public r-cloneseeker
  (package
    (name "r-cloneseeker")
    (version "1.0.11")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CloneSeeker" version))
       (sha256
        (base32 "19aj4c2q3wp4vp08j72700wwyqmkqxwml2fwmz0wsxdam8vp1ydi"))))
    (properties `((upstream-name . "CloneSeeker")))
    (build-system r-build-system)
    (propagated-inputs (list r-quantmod r-mc2d r-combinat))
    (home-page "http://oompa.r-forge.r-project.org/")
    (synopsis "Seeking and Finding Clones in Copy Number and Sequencing Data")
    (description
     "Defines the classes and functions used to simulate and to analyze data sets
describing copy number variants and, optionally, sequencing mutations in order
to detect clonal subsets.  See Zucker et al. (2019)
<doi:10.1093/bioinformatics/btz057>.")
    (license license:asl2.0)))

(define-public r-clonerate
  (package
    (name "r-clonerate")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cloneRate" version))
       (sha256
        (base32 "0ii1jbwk60dvqqrxr4z06xnajyf73ywhb06i42szcs6mjm1jxwsa"))))
    (properties `((upstream-name . "cloneRate")))
    (build-system r-build-system)
    (propagated-inputs (list r-stanheaders
                             r-rstantools
                             r-rstan
                             r-rmpfr
                             r-rcppparallel
                             r-rcppeigen
                             r-rcpp
                             r-bh
                             r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/bdj34/cloneRate")
    (synopsis "Estimate Growth Rates from Phylogenetic Trees")
    (description
     "Quickly estimate the net growth rate of a population or clone whose growth can
be approximated by a birth-death branching process.  Input should be
phylogenetic tree(s) of clone(s) with edge lengths corresponding to either time
or mutations.  Based on coalescent results in Johnson et al. (2023)
<doi:10.1093/bioinformatics/btad561>.  Simulation techniques as well as growth
rate methods build on prior work from Lambert A. (2018)
<doi:10.1016/j.tpb.2018.04.005> and Stadler T. (2009)
<doi:10.1016/j.jtbi.2009.07.018>.")
    (license license:expat)))

(define-public r-clogitl1
  (package
    (name "r-clogitl1")
    (version "1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clogitL1" version))
       (sha256
        (base32 "0y6a6s5l98i0vrj66biwr17g6pzpmm5kfz4c57af0yhv7c4s4was"))))
    (properties `((upstream-name . "clogitL1")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://cran.r-project.org/package=clogitL1")
    (synopsis
     "Fitting Exact Conditional Logistic Regression with Lasso and Elastic Net Penalties")
    (description
     "This package provides tools for the fitting and cross validation of exact
conditional logistic regression models with lasso and elastic net penalties.
Uses cyclic coordinate descent and warm starts to compute the entire path
efficiently.")
    (license license:gpl2)))

(define-public r-clogitboost
  (package
    (name "r-clogitboost")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clogitboost" version))
       (sha256
        (base32 "19wcb7229amlxn6xahxj6pf9rwfm02s7qkxz2yvyhnq95y0clxkm"))))
    (properties `((upstream-name . "clogitboost")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://cran.r-project.org/package=clogitboost")
    (synopsis "Boosting Conditional Logit Model")
    (description
     "This package provides a set of functions to fit a boosting conditional logit
model.")
    (license license:gpl2+)))

(define-public r-clockify
  (package
    (name "r-clockify")
    (version "0.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clockify" version))
       (sha256
        (base32 "0yancrksqpsjgrf5rhq25yl4hnc4vjq57bv5kqqpd0h1fw3xxr37"))))
    (properties `((upstream-name . "clockify")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringi
                             r-rlist
                             r-purrr
                             r-lubridate
                             r-logger
                             r-janitor
                             r-httr
                             r-dplyr
                             r-anytime))
    (home-page "https://cran.r-project.org/package=clockify")
    (synopsis "Wrapper for the 'Clockify' API")
    (description
     "This package provides a wrapper for the Clockify API
<https://docs.clockify.me/>, making it possible to query, insert and update time
keeping data.")
    (license license:gpl3)))

(define-public r-clmplus
  (package
    (name "r-clmplus")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clmplus" version))
       (sha256
        (base32 "024w8a4qj9sr0vqpfv5sm5gmcy4crin90sfx0z1y13iiznk7kvch"))))
    (properties `((upstream-name . "clmplus")))
    (build-system r-build-system)
    (propagated-inputs (list r-stmomo
                             r-reshape2
                             r-gridextra
                             r-ggplot2
                             r-forecast
                             r-chainladder))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://github.com/gpitt71/clmplus")
    (synopsis "Tool-Box of Chain Ladder Plus Models")
    (description
     "Implementation of the age-period-cohort models for the claim development
presented in the manuscript Replicating and extending chain-ladder via an
age-period-cohort structure on the claim development in a run-off triangle
<doi:10.48550/@code{arXiv.2301.03858>}.")
    (license license:gpl2+)))

(define-public r-clme
  (package
    (name "r-clme")
    (version "2.0-12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CLME" version))
       (sha256
        (base32 "161maq22r8wbd6c2dc8b47mh6991vc4iqmjr8g6yqb5gcwca8zhg"))))
    (properties `((upstream-name . "CLME")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-shiny
                             r-prettyr
                             r-openxlsx
                             r-nlme
                             r-mass
                             r-lme4
                             r-isotone))
    (home-page "https://cran.r-project.org/package=CLME")
    (synopsis "Constrained Inference for Linear Mixed Effects Models")
    (description
     "Estimation and inference for linear models where some or all of the
fixed-effects coefficients are subject to order restrictions.  This package uses
the robust residual bootstrap methodology for inference, and can handle some
structure in the residual variance matrix.")
    (license license:gpl3)))

(define-public r-cliquepercolation
  (package
    (name "r-cliquepercolation")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CliquePercolation" version))
       (sha256
        (base32 "17m8pj8wg2ngzip1ag3jm5fqi083ilrsi0rvpcg5jmqflwlka8h3"))))
    (properties `((upstream-name . "CliquePercolation")))
    (build-system r-build-system)
    (propagated-inputs (list r-qgraph
                             r-polychrome
                             r-pbapply
                             r-ohenery
                             r-matrix
                             r-magrittr
                             r-lessr
                             r-igraph
                             r-colorspace))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CliquePercolation")
    (synopsis "Clique Percolation for Networks")
    (description
     "Clique percolation community detection for weighted and unweighted networks as
well as threshold and plotting functions.  For more information see Farkas et
al. (2007) <doi:10.1088/1367-2630/9/6/180> and Palla et al. (2005)
<doi:10.1038/nature03607>.")
    (license license:gpl3)))

(define-public r-clipp
  (package
    (name "r-clipp")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clipp" version))
       (sha256
        (base32 "1yddihmjg90j9id825lyanqpfm4i67mdgvdm53pz20p8fcq4mlzw"))))
    (properties `((upstream-name . "clipp")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=clipp")
    (synopsis "Calculating Likelihoods by Pedigree Paring")
    (description
     "This package provides a fast and general implementation of the Elston-Stewart
algorithm that can calculate the likelihoods of large and complex pedigrees.
References for the Elston-Stewart algorithm are Elston & Stewart (1971)
<doi:10.1159/000152448>, Lange & Elston (1975) <doi:10.1159/000152714> and
Cannings et al. (1978) <doi:10.2307/1426718>.")
    (license license:gpl3)))

(define-public r-cliot
  (package
    (name "r-cliot")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cliot" version))
       (sha256
        (base32 "0gynh767vv02xn6j6mbakdsfb1s9m3pvr3idn9qy1qy6wbfya9h7"))))
    (properties `((upstream-name . "cliot")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cliot")
    (synopsis "Clinical Indices and Outcomes Tools")
    (description
     "Collection of indices and tools relating to cardiovascular, nephrology, and
hepatic research that aid epidemiological chort or retrospective chart review
with big data.  All indices and tools take commonly used lab values and patient
demographics and measurements to compute various risk and predictive values for
survival.  References to original literature and validation contained in each
function documentation.")
    (license license:gpl3)))

(define-public r-clinutils
  (package
    (name "r-clinutils")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clinUtils" version))
       (sha256
        (base32 "1i8bbfj9hbhjq7ppr3s3wxmnlis0j9xapdz88x44gcsmvxmr57dr"))))
    (properties `((upstream-name . "clinUtils")))
    (build-system r-build-system)
    (inputs (list pandoc))
    (propagated-inputs (list r-viridislite
                             r-plyr
                             r-knitr
                             r-htmlwidgets
                             r-haven
                             r-dt
                             r-data-table
                             r-crosstalk))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/openanalytics/clinUtils")
    (synopsis "General Utility Functions for Analysis of Clinical Data")
    (description
     "Utility functions to facilitate the import, the reporting and analysis of
clinical data.  Example datasets in SDTM and A@code{DaM} format, containing a
subset of patients/domains from the CDISC Pilot 01 study are also available as R
datasets to demonstrate the package functionalities.")
    (license license:expat)))

(define-public r-clintrialx
  (package
    (name "r-clintrialx")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clintrialx" version))
       (sha256
        (base32 "1bzhw9mspxc45min7y0qa31iklahpq6i7c8v3n9m4fszb7xsyafs"))))
    (properties `((upstream-name . "clintrialx")))
    (build-system r-build-system)
    (propagated-inputs (list r-xfun
                             r-tibble
                             r-rpostgresql
                             r-rmarkdown
                             r-readr
                             r-progress
                             r-lubridate
                             r-httr
                             r-dplyr
                             r-dbi))
    (native-inputs (list r-knitr))
    (home-page "http://www.indraneelchakraborty.com/clintrialx/")
    (synopsis "Connect and Work with Clinical Trials Data Sources")
    (description
     "Are you spending too much time fetching and managing clinical trial data?
Struggling with complex queries and bulk data extraction? What if you could
simplify this process with just a few lines of code? Introducing clintrialx -
Fetch clinical trial data from sources like @code{ClinicalTrials.gov}
<https://clinicaltrials.gov/> and the Clinical Trials Transformation Initiative
- Access to Aggregate Content of @code{ClinicalTrials.gov} database
<https://aact.ctti-clinicaltrials.org/>, supporting pagination and bulk
downloads.  Also, you can generate HTML reports based on the data obtained from
the sources!")
    (license license:asl2.0)))

(define-public r-clintools
  (package
    (name "r-clintools")
    (version "0.9.10.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clintools" version))
       (sha256
        (base32 "0f8y1l3mqij6y87xf07gq7r2frigswcff5p3v119l6rldmkhp4fl"))))
    (properties `((upstream-name . "clintools")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-survival
                             r-stringi
                             r-signal
                             r-scales
                             r-proc
                             r-parameters
                             r-pander
                             r-nlme
                             r-lme4
                             r-irr
                             r-ggplot2
                             r-dplyr))
    (home-page "https://github.com/lilleoel/clintools")
    (synopsis "Tools for Clinical Research")
    (description
     "Every research team have their own script for data management, statistics and
most importantly hemodynamic indices.  The purpose is to standardize scripts
utilized in clinical research.  The hemodynamic indices can be used in a
long-format dataframe, and add both periods of interest (trigger-periods), and
delete artifacts with deleter-files.  Transfer function analysis (Claassen et
al. (2016) <doi:10.1177/0271678X15626425>) and Mx (Czosnyka et al. (1996)
<doi:10.1161/01.str.27.10.1829>) can be calculated using this package.")
    (license license:expat)))

(define-public r-clinspacy
  (package
    (name "r-clinspacy")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clinspacy" version))
       (sha256
        (base32 "134nvkircy1a1rmsg2nszk2r8bcdmikmrx6plchdz8gxyjd6jmya"))))
    (properties `((upstream-name . "clinspacy")))
    (build-system r-build-system)
    (propagated-inputs (list r-reticulate r-rappdirs r-magrittr r-data-table
                             r-assertthat))
    (home-page "https://github.com/ML4LHS/clinspacy")
    (synopsis
     "Clinical Natural Language Processing using 'spaCy', 'scispaCy', and 'medspaCy'")
    (description
     "This package performs biomedical named entity recognition, Unified Medical
Language System (UMLS) concept mapping, and negation detection using the Python
@code{spaCy}', @code{scispaCy}', and @code{medspaCy} packages, and transforms
extracted data into a wide format for inclusion in machine learning models.  The
development of the @code{scispaCy} package is described by Neumann (2019)
<doi:10.18653/v1/W19-5034>.  The medspacy package uses @code{ConText}', an
algorithm for determining the context of clinical statements described by
Harkema (2009) <doi:10.1016/j.jbi.2009.05.002>.  Clinspacy also supports entity
embeddings from @code{scispaCy} and UMLS cui2vec concept embeddings developed by
Beam (2018) <@code{arXiv:1804.01486>}.")
    (license license:expat)))

(define-public r-clinsigmeasures
  (package
    (name "r-clinsigmeasures")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClinSigMeasures" version))
       (sha256
        (base32 "0vyn1j4qfxgh65jrq7wmm8nfw78vqllmrsdbzspl7hgf5zh477k1"))))
    (properties `((upstream-name . "ClinSigMeasures")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ClinSigMeasures")
    (synopsis "Clinical Significance Measures")
    (description
     "This package provides measures of effect sizes for summarized continuous
variables as well as diagnostic accuracy statistics for 2x2 table data.
Includes functions for Cohen's d, robust effect size, Cohen's q, partial
eta-squared, coefficient of variation, odds ratio, likelihood ratios,
sensitivity, specificity, positive and negative predictive values, Youden index,
number needed to treat, number needed to diagnose, and predictive summary index.")
    (license license:gpl3)))

(define-public r-clinsig
  (package
    (name "r-clinsig")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clinsig" version))
       (sha256
        (base32 "1wgfl9kks57yizrf8z6x7dhmbl3a80q8nnj3a5n2hpc9yr8l9ijf"))))
    (properties `((upstream-name . "clinsig")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=clinsig")
    (synopsis "Clinical Significance Functions")
    (description
     "This package provides functions for calculating clinical significance.")
    (license license:gpl2+)))

(define-public r-clinpk
  (package
    (name "r-clinpk")
    (version "0.13.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clinPK" version))
       (sha256
        (base32 "1mfm4z0gbwmk2pvwmrk2z00zjl580mbf3z38zpsb3nx8xlxvsv1b"))))
    (properties `((upstream-name . "clinPK")))
    (build-system r-build-system)
    (home-page "https://github.com/InsightRX/clinPK")
    (synopsis "Clinical Pharmacokinetics Toolkit")
    (description
     "This package provides equations commonly used in clinical pharmacokinetics and
clinical pharmacology, such as equations for dose individualization,
compartmental pharmacokinetics, drug exposure, anthropomorphic calculations,
clinical chemistry, and conversion of common clinical parameters.  Where
possible and relevant, it provides multiple published and peer-reviewed
equations within the respective R function.")
    (license license:expat)))

(define-public r-clinmon
  (package
    (name "r-clinmon")
    (version "0.6.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clinmon" version))
       (sha256
        (base32 "0cd5mrirfll0zbm9k8glwdqnh4qy4dlfnsypr3xhyf6ppgm35hlv"))))
    (properties `((upstream-name . "clinmon")))
    (build-system r-build-system)
    (propagated-inputs (list r-signal))
    (home-page "https://github.com/lilleoel/clinmon")
    (synopsis "Hemodynamic Calculations from Clinical Monitoring")
    (description
     "Every research team have their own script for calculation of hemodynamic
indexes.  This package makes it possible to insert a long-format dataframe, and
add both periods of interest (trigger-periods), and delete artifacts with
deleter-files.")
    (license license:expat)))

(define-public r-clinicalutilityrecal
  (package
    (name "r-clinicalutilityrecal")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClinicalUtilityRecal" version))
       (sha256
        (base32 "17xj9cmdkjrzx7mshka2hlkxh8887sprdqix7fd8jcr9bmc6ad9r"))))
    (properties `((upstream-name . "ClinicalUtilityRecal")))
    (build-system r-build-system)
    (propagated-inputs (list r-nloptr r-lattice r-ggplot2 r-cowplot r-caret))
    (home-page "https://cran.r-project.org/package=ClinicalUtilityRecal")
    (synopsis
     "Recalibration Methods for Improved Clinical Utility of Risk Scores")
    (description
     "Recalibrate risk scores (predicting binary outcomes) to improve clinical utility
of risk score using weighted logistic or constrained logistic recalibration
methods.  Additionally, produces plots to assess the potential for recalibration
to improve the clinical utility of a risk model.  Methods are described in
detail in Mishra, A. (2019) \"Methods for Risk Markers that Incorporate Clinical
Utility\" <http://hdl.handle.net/1773/44068>.")
    (license license:gpl2)))

(define-public r-clinicaltrialsummary
  (package
    (name "r-clinicaltrialsummary")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClinicalTrialSummary" version))
       (sha256
        (base32 "0b5by4sn9yvrvxr9921yqsgp8ma3g1hi2qbp5j9m836db1zjhyla"))))
    (properties `((upstream-name . "ClinicalTrialSummary")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://cran.r-project.org/package=ClinicalTrialSummary")
    (synopsis "Summary Measures for Clinical Trials with Survival Outcomes")
    (description
     "This package provides estimates of several summary measures for clinical trials
including the average hazard ratio, the weighted average hazard ratio, the
restricted superiority probability ratio, the restricted mean survival
difference and the ratio of restricted mean times lost, based on the short-term
and long-term hazard ratio model (Yang, 2005 <doi:10.1093/biomet/92.1.1>) which
accommodates various non-proportional hazards scenarios.  The inference
procedures and the asymptotic results for the summary measures are discussed in
Yang (2018, <doi:10.1002/sim.7676>).")
    (license license:gpl3+)))

(define-public r-clinicalsignificance
  (package
    (name "r-clinicalsignificance")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clinicalsignificance" version))
       (sha256
        (base32 "132zwgzrc9gf10x2ldr7mjbj8k83h87y7py9b34yv9s7jmciy62x"))))
    (properties `((upstream-name . "clinicalsignificance")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-rlang
                             r-purrr
                             r-lme4
                             r-insight
                             r-ggplot2
                             r-dplyr
                             r-cli
                             r-bayestestr
                             r-bayesfactor))
    (native-inputs (list r-knitr))
    (home-page "https://pedscience.github.io/clinicalsignificance/")
    (synopsis
     "Toolbox for Clinical Significance Analyses in Intervention Studies")
    (description
     "This package provides a clinical significance analysis can be used to determine
if an intervention has a meaningful or practical effect for patients.  You
provide a tidy data set plus a few more metrics and this package will take care
of it to make your results publication ready.")
    (license license:gpl3+)))

(define-public r-clinicalomicsdbr
  (package
    (name "r-clinicalomicsdbr")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clinicalomicsdbR" version))
       (sha256
        (base32 "1al919bdvmxfs8kxgi4hxwgsc9gjml6d00b7h813jhc4fi7ncq3p"))))
    (properties `((upstream-name . "clinicalomicsdbR")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6 r-jsonlite r-httr2 r-dplyr))
    (home-page "https://github.com/bzhanglab/clinicalomicsdbR")
    (synopsis
     "Interface with the 'ClinicalOmicsDB' API, Allowing for Easy Data Downloading and Importing")
    (description
     "This package provides an interface to the @code{ClinicalOmicsDB} API, allowing
for easy data downloading and importing. @code{ClinicalOmicsDB} is a database of
clinical and omics data from cancer patients.  The database is accessible at
<http://trials.linkedomics.org>.")
    (license license:expat)))

(define-public r-clinfun
  (package
    (name "r-clinfun")
    (version "1.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clinfun" version))
       (sha256
        (base32 "0dsbgj29s7c9pv6p2j3nvksnckym0gyb8hwqvks53mvy2pg9j1ni"))))
    (properties `((upstream-name . "clinfun")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm))
    (native-inputs (list r-knitr gfortran))
    (home-page "https://cran.r-project.org/package=clinfun")
    (synopsis "Clinical Trial Design and Data Analysis Functions")
    (description
     "Utilities to make your clinical collaborations easier if not fun.  It contains
functions for designing studies such as Simon 2-stage and group sequential
designs and for data analysis such as Jonckheere-Terpstra test and estimating
survival quantiles.")
    (license license:gpl2+)))

(define-public r-clindr
  (package
    (name "r-clindr")
    (version "2.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clinDR" version))
       (sha256
        (base32 "06q8ajfa0gj8ddr6vb456vra4id7la50aidx3j2bnyaysbavd108"))))
    (properties `((upstream-name . "clinDR")))
    (build-system r-build-system)
    (propagated-inputs (list r-waiter
                             r-tidyr
                             r-tibble
                             r-shiny
                             r-rstan
                             r-purrr
                             r-mvtnorm
                             r-glue
                             r-ggplot2
                             r-foreach
                             r-dplyr
                             r-dosefinding
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=clinDR")
    (synopsis
     "Simulation and Analysis Tools for Clinical Dose Response Modeling")
    (description
     "Bayesian and ML Emax model fitting, graphics and simulation for clinical dose
response.  The summary data from the dose response meta-analyses in Thomas,
Sweeney, and Somayaji (2014) <doi:10.1080/19466315.2014.924876> and Thomas and
Roy (2016) <doi:10.1080/19466315.2016.1256229> Wu, Banerjee, Jin, Menon, Martin,
and Heatherington(2017) <doi:10.1177/0962280216684528> are included in the
package.  The prior distributions for the Bayesian analyses default to the
posterior predictive distributions derived from these references.")
    (license license:gpl2+)))

(define-public r-clindatareview
  (package
    (name "r-clindatareview")
    (version "1.6.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clinDataReview" version))
       (sha256
        (base32 "146cibny0w7g75cvzrdnd5i2fx6bilp93wqfrjgzap17h97lhj1r"))))
    (properties `((upstream-name . "clinDataReview")))
    (build-system r-build-system)
    (arguments
     (list
      #:modules '((guix build r-build-system)
                  (guix build minify-build-system)
                  (guix build utils)
                  (ice-9 match))
      #:imported-modules `(,@%r-build-system-modules (guix build
                                                      minify-build-system))
      #:phases '(modify-phases %standard-phases
                  (add-after 'unpack 'process-javascript
                    (lambda* (#:key inputs #:allow-other-keys)
                      (with-directory-excursion "inst/"
                        (for-each (match-lambda
                                    ((source . target) (minify source
                                                               #:target target)))
                                  '())))))))
    (inputs (list pandoc))
    (propagated-inputs (list r-yaml
                             r-xml2
                             r-xfun
                             r-stringr
                             r-rmarkdown
                             r-plyr
                             r-plotly
                             r-knitr
                             r-jsonvalidate
                             r-jsonlite
                             r-htmlwidgets
                             r-htmltools
                             r-haven
                             r-ggplot2
                             r-data-table
                             r-crosstalk
                             r-clinutils
                             r-bookdown
                             r-base64enc))
    (native-inputs (list r-knitr esbuild))
    (home-page "https://github.com/openanalytics/clinDataReview")
    (synopsis "Clinical Data Review Tool")
    (description
     "Creation of interactive tables, listings and figures ('TLFs') and associated
report for exploratory analysis of data in a clinical trial, e.g. for clinical
oversight activities.  Interactive figures include sunburst, treemap,
scatterplot, line plot and barplot of counts data.  Interactive tables include
table of summary statistics (as counts of adverse events, enrollment table) and
listings.  Possibility to compare data (summary table or listing) across two
data batches/sets.  A clinical data review report is created via study-specific
configuration files and template R Markdown reports contained in the package.")
    (license license:expat)))

(define-public r-climwin
  (package
    (name "r-climwin")
    (version "1.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "climwin" version))
       (sha256
        (base32 "1r2x5941k8l9z3517389y120sfhrskdpchc0pkibznza8aa95r85"))))
    (properties `((upstream-name . "climwin")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape
                             r-rcpproll
                             r-numderiv
                             r-nlme
                             r-mumin
                             r-matrix
                             r-lubridate
                             r-lme4
                             r-gridextra
                             r-ggplot2
                             r-evd))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/LiamDBailey/climwin")
    (synopsis "Climate Window Analysis")
    (description
     "This package contains functions to detect and visualise periods of climate
sensitivity (climate windows) for a given biological response.  Please see van
de Pol et al. (2016) <doi:10.1111/2041-210X.12590> and Bailey and van de Pol
(2016) <doi:10.1371/journal.pone.0167980> for details.")
    (license license:gpl2)))

(define-public r-climprojdiags
  (package
    (name "r-climprojdiags")
    (version "0.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClimProjDiags" version))
       (sha256
        (base32 "039rnjpsbq90x6h9snz9iy37bwhapcmw9v98ngh82bsh19h8hwb1"))))
    (properties `((upstream-name . "ClimProjDiags")))
    (build-system r-build-system)
    (propagated-inputs (list r-pcict r-multiapply))
    (native-inputs (list r-knitr))
    (home-page "https://earth.bsc.es/gitlab/es/ClimProjDiags")
    (synopsis "Set of Tools to Compute Various Climate Indices")
    (description
     "Set of tools to compute metrics and indices for climate analysis.  The package
provides functions to compute extreme indices, evaluate the agreement between
models and combine theses models into an ensemble.  Multi-model time series of
climate indices can be computed either after averaging the 2-D fields from
different models provided they share a common grid or by combining time series
computed on the model native grid.  Indices can be assigned weights and/or
combined to construct new indices.")
    (license license:gpl3)))

(define-public r-climmobtools
  (package
    (name "r-climmobtools")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClimMobTools" version))
       (sha256
        (base32 "1kx1hkyn96bhw237hvzrkr1hc8nf02p90lz9gg0rzcjx0zhks4s7"))))
    (properties `((upstream-name . "ClimMobTools")))
    (build-system r-build-system)
    (propagated-inputs (list r-rspectra r-matrix r-lpsolve r-jsonlite r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://agrdatasci.github.io/ClimMobTools/")
    (synopsis "API Client for the 'ClimMob' Platform")
    (description
     "API client for @code{ClimMob}', an open source software for decentralized
large-N trials with the tricot approach <https://climmob.net/>.  Developed by
van Etten et al. (2019) <doi:10.1017/S0014479716000739>, it turns the research
paradigm on its head; instead of a few researchers designing complicated trials
to compare several technologies in search of the best solutions for the target
environment, it enables many participants to carry out reasonably simple
experiments that taken together can offer even more information.
@code{ClimMobTools} enables project managers to deep explore and analyse their
@code{ClimMob} data in R.")
    (license license:expat)))

(define-public r-climind
  (package
    (name "r-climind")
    (version "0.1-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClimInd" version))
       (sha256
        (base32 "0n5kd001nkpks16c3msvn2qvzyrjawa2rqwh8zph2qr5hgpwcpg7"))))
    (properties `((upstream-name . "ClimInd")))
    (build-system r-build-system)
    (propagated-inputs (list r-weathermetrics r-spei r-chron))
    (home-page "https://gitlab.com/indecis-eu/indecis")
    (synopsis "Climate Indices")
    (description
     "Computes 138 standard climate indices at monthly, seasonal and annual
resolution.  These indices were selected, based on their direct and significant
impacts on target sectors, after a thorough review of the literature in the
field of extreme weather events and natural hazards.  Overall, the selected
indices characterize different aspects of the frequency, intensity and duration
of extreme events, and are derived from a broad set of climatic variables,
including surface air temperature, precipitation, relative humidity, wind speed,
cloudiness, solar radiation, and snow cover.  The 138 indices have been
classified as follow: Temperature based indices (42), Precipitation based
indices (22), Bioclimatic indices (21), Wind-based indices (5), Aridity/
continentality indices (10), Snow-based indices (13), Cloud/radiation based
indices (6), Drought indices (8), Fire indices (5), Tourism indices (5).")
    (license license:gpl3+)))

(define-public r-climextremes
  (package
    (name "r-climextremes")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "climextRemes" version))
       (sha256
        (base32 "0dvkwdb37aqvl9qanaw4b7in6b4vjih3xjy0j16qdr5w76jcn804"))))
    (properties `((upstream-name . "climextRemes")))
    (build-system r-build-system)
    (propagated-inputs (list r-extremes r-boot))
    (home-page "https://bitbucket.org/lbl-cascade/climextremes-dev")
    (synopsis "Tools for Analyzing Climate Extremes")
    (description
     "This package provides functions for fitting GEV and POT (via point process
fitting) models for extremes in climate data, providing return values, return
probabilities, and return periods for stationary and nonstationary models.  Also
provides differences in return values and differences in log return
probabilities for contrasts of covariate values.  Functions for estimating risk
ratios for event attribution analyses, including uncertainty.  Under the hood,
many of the functions use functions from @code{extRemes}', including for fitting
the statistical models.  Details are given in Paciorek, Stone, and Wehner (2018)
<doi:10.1016/j.wace.2018.01.002>.")
    (license license:bsd-3)))

(define-public r-climetrics
  (package
    (name "r-climetrics")
    (version "1.0-15")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "climetrics" version))
       (sha256
        (base32 "0xgc0lklx2ry60gp38nbl922xhdyfvia3mg977y4gdhcz1jljfhp"))))
    (properties `((upstream-name . "climetrics")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-yaimpute
                             r-xts
                             r-terra
                             r-rts
                             r-raster))
    (native-inputs (list r-r-rsp))
    (home-page "https://r-gis.net/")
    (synopsis "Climate Change Metrics")
    (description
     "This package provides a framework that facilitates spatio-temporal analysis of
climate dynamics through exploring and measuring different dimensions of climate
change in space and time.")
    (license license:gpl3+)))

(define-public r-clime
  (package
    (name "r-clime")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clime" version))
       (sha256
        (base32 "15xc4cvllf6qpwa8a0lvsbivx4cricbgn0v3wc70xy69ngfa7zaj"))))
    (properties `((upstream-name . "clime")))
    (build-system r-build-system)
    (propagated-inputs (list r-lpsolve))
    (home-page "https://cran.r-project.org/package=clime")
    (synopsis
     "Constrained L1-Minimization for Inverse (Covariance) Matrix Estimation")
    (description
     "This package provides a robust constrained L1 minimization method for estimating
a large sparse inverse covariance matrix (aka precision matrix), and recovering
its support for building graphical models.  The computation uses linear
programming.  The method was published in TT Cai, W Liu, X Luo (2011)
<doi:10.1198/jasa.2011.tm10155>.")
    (license license:gpl2)))

(define-public r-climd
  (package
    (name "r-climd")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CLimd" version))
       (sha256
        (base32 "0mcvxknzahz4v198ys6gnd7pg8ixcabaxlimj82z5wa1dbm81x9i"))))
    (properties `((upstream-name . "CLimd")))
    (build-system r-build-system)
    (propagated-inputs (list r-raster r-qpdf r-ncdf4))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CLimd")
    (synopsis "Generating Rainfall Rasters from IMD NetCDF Data")
    (description
     "The developed function is a comprehensive tool for the analysis of India
Meteorological Department (IMD) @code{NetCDF} rainfall data.  Specifically
designed to process high-resolution daily gridded rainfall datasets.  It
provides four key functions to process IMD @code{NetCDF} rainfall data and
create rasters for various temporal scales, including annual, seasonal, monthly,
and weekly rainfall.  For method details see, Malik, A.
(2019).<DOI:10.1007/s12517-019-4454-5>.  It supports different aggregation
methods, such as sum, min, max, mean, and standard deviation.  These functions
are designed for spatio-temporal analysis of rainfall patterns, trend
analysis,geostatistical modeling of rainfall variability, identifying rainfall
anomalies and extreme events and can be an input for hydrological and
agricultural models.")
    (license license:gpl2+)))

(define-public r-climclass
  (package
    (name "r-climclass")
    (version "2.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClimClass" version))
       (sha256
        (base32 "1r836md31z2r5d9xckkbalzbhm4kf5paljv71kxpy53q92k7yi91"))))
    (properties `((upstream-name . "ClimClass")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2 r-ggplot2 r-geosphere))
    (home-page "https://cran.r-project.org/package=ClimClass")
    (synopsis "Climate Classification According to Several Indices")
    (description
     "Classification of climate according to Koeppen - Geiger, of aridity indices, of
continentality indices, of water balance after Thornthwaite, of viticultural
bioclimatic indices.  Drawing climographs: Thornthwaite, Peguy,
Bagnouls-Gaussen.")
    (license license:gpl3+)))

(define-public r-climatrends
  (package
    (name "r-climatrends")
    (version "0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "climatrends" version))
       (sha256
        (base32 "0b2afsff0yl2rcvff5mi6zz5xls9k9hzpay041mv11wc7ii8bw27"))))
    (properties `((upstream-name . "climatrends")))
    (build-system r-build-system)
    (propagated-inputs (list r-nasapower))
    (native-inputs (list r-knitr))
    (home-page "https://agrdatasci.github.io/climatrends/")
    (synopsis "Climate Variability Indices for Ecological Modelling")
    (description
     "Supports analysis of trends in climate change, ecological and crop modelling.")
    (license license:expat)))

(define-public r-climatestability
  (package
    (name "r-climatestability")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "climateStability" version))
       (sha256
        (base32 "0cnp67dskwlw60lzknh3nfx2raj90zk6z1bng8l1blsgmap565dd"))))
    (properties `((upstream-name . "climateStability")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/hannahlowens/climateStability")
    (synopsis "Estimating Climate Stability from Climate Model Data")
    (description
     "Climate stability measures are not formalized in the literature and tools for
generating stability metrics from existing data are nascent.  This package
provides tools for calculating climate stability from raster data encapsulating
climate change as a series of time slices.  The methods follow Owens and
Guralnick <doi:10.17161/bi.v14i0.9786> Biodiversity Informatics.")
    (license license:gpl3)))

(define-public r-climate
  (package
    (name "r-climate")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "climate" version))
       (sha256
        (base32 "16fwli2dhj9rf9qz3h6iy7g06y7z3vi7mndbhf4vx110iyjsh2wa"))))
    (properties `((upstream-name . "climate")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml r-stringi r-httr r-data-table r-curl))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/bczernecki/climate")
    (synopsis
     "Interface to Download Meteorological (and Hydrological) Datasets")
    (description
     "Automatize downloading of meteorological and hydrological data from publicly
available repositories: OGIMET (<http://ogimet.com/index.phtml.en>), University
of Wyoming - atmospheric vertical profiling data
(<http://weather.uwyo.edu/upperair/>), Polish Institute of Meteorology and Water
Management - National Research Institute (<https://danepubliczne.imgw.pl>), and
National Oceanic & Atmospheric Administration (NOAA).  This package also allows
for searching geographical coordinates for each observation and calculate
distances to the nearest stations.")
    (license license:expat)))

(define-public r-clikcorr
  (package
    (name "r-clikcorr")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clikcorr" version))
       (sha256
        (base32 "0zdnbcl5q293mmm6pbn4ri7p1q6z6sff74axsb3nyd153v2xamr5"))))
    (properties `((upstream-name . "clikcorr")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm))
    (home-page "https://cran.r-project.org/package=clikcorr")
    (synopsis "Censoring Data and Likelihood-Based Correlation Estimation")
    (description
     "This package provides a profile likelihood based method of estimation and
inference on the correlation coefficient of bivariate data with different types
of censoring and missingness.")
    (license license:gpl2+)))

(define-public r-cliftlrd
  (package
    (name "r-cliftlrd")
    (version "0.1-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CliftLRD" version))
       (sha256
        (base32 "0qsdv568klxg6chgw329jbfjmf6w61hly2vxp90yzdfkca03z2s4"))))
    (properties `((upstream-name . "CliftLRD")))
    (build-system r-build-system)
    (propagated-inputs (list r-liftlrd r-cnltreg))
    (home-page "https://cran.r-project.org/package=CliftLRD")
    (synopsis
     "Complex-Valued Wavelet Lifting Estimators of the Hurst Exponent for Irregularly Sampled Time Series")
    (description
     "Implementation of Hurst exponent estimators based on complex-valued lifting
wavelet energy from Knight, M. I and Nunes, M. A. (2018)
<doi:10.1007/s11222-018-9820-8>.")
    (license license:gpl2)))

(define-public r-clifro
  (package
    (name "r-clifro")
    (version "3.2-5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clifro" version))
       (sha256
        (base32 "1p2xy5r9axkj8yk6ywaq0w5i00bdfm15drjz227nx8p4vd3q6si8"))))
    (properties `((upstream-name . "clifro")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-stringr
                             r-scales
                             r-rvest
                             r-reshape2
                             r-rcolorbrewer
                             r-magrittr
                             r-lubridate
                             r-httr
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/clifro/")
    (synopsis "Easily Download and Visualise Climate Data from CliFlo")
    (description
     "@code{CliFlo} is a web portal to the New Zealand National Climate Database and
provides public access (via subscription) to around 6,500 various climate
stations (see <https://cliflo.niwa.co.nz/> for more information).  Collating and
manipulating data from @code{CliFlo} (hence clifro) and importing into R for
further analysis, exploration and visualisation is now straightforward and
coherent.  The user is required to have an internet connection, and a current
@code{CliFlo} subscription (free) if data from stations, other than the public
Reefton electronic weather station, is sought.")
    (license license:gpl2)))

(define-public r-clifford
  (package
    (name "r-clifford")
    (version "1.0-8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clifford" version))
       (sha256
        (base32 "0gi4jajng1v0a45dl5qv8v279bm4lzfbkdsqp0bd1vil2ns1934j"))))
    (properties `((upstream-name . "clifford")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp
                             r-partitions
                             r-mathjaxr
                             r-magrittr
                             r-disordr
                             r-bh))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/RobinHankin/clifford")
    (synopsis "Arbitrary Dimensional Clifford Algebras")
    (description
     "This package provides a suite of routines for Clifford algebras, using the Map
class of the Standard Template Library.  Canonical reference: Hestenes (1987,
ISBN 90-277-1673-0, \"Clifford algebra to geometric calculus\").  Special cases
including Lorentz transforms, quaternion multiplication, and Grassman algebra,
are discussed.  Conformal geometric algebra theory is implemented.  Uses
@code{disordR} discipline.")
    (license license:gpl2+)))

(define-public r-cliff
  (package
    (name "r-cliff")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cliff" version))
       (sha256
        (base32 "0d7aswvsqlyai3rxxbfy08cs4qbi9fjjls62y1p95bmnhq1b3bwf"))))
    (properties `((upstream-name . "cliff")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-processx r-ellipsis))
    (home-page "https://github.com/RTagBot/cliff")
    (synopsis "Execute Command Line Programs Interactively")
    (description
     "Execute command line programs and format results for interactive use.  It is
based on the package processx so it does not use shell to start up the process
like system() and system2().  It also provides a simpler and cleaner interface
than processx::run().")
    (license license:expat)))

(define-public r-clidatajp
  (package
    (name "r-clidatajp")
    (version "0.5.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clidatajp" version))
       (sha256
        (base32 "1wpj9wydjaq0jnnacwbrggqpncy9z8q792l0qv297a9vxqhd9pqz"))))
    (properties `((upstream-name . "clidatajp")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-stringi
                             r-rvest
                             r-rlang
                             r-magrittr
                             r-httr
                             r-dplyr
                             r-curl))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=clidatajp")
    (synopsis "Data from Japan Meteorological Agency")
    (description
     "Includes climate data from Japan Meteorological Agency ('JMA')
<https://www.jma.go.jp/jma/indexe.html>.  Can download climate data from JMA'.")
    (license license:expat)))

(define-public r-clidamonger
  (package
    (name "r-clidamonger")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clidamonger" version))
       (sha256
        (base32 "1rcfa6d3vfx6bbjjggrqfz10lppql7hjiy06jsrgybw2j0x73hmk"))))
    (properties `((upstream-name . "clidamonger")))
    (build-system r-build-system)
    (home-page "https://github.com/IWUGERMANY/clidamonger")
    (synopsis
     "Monthly Climate Data for Germany, Usable for Heating and Cooling Calculations")
    (description
     "This data package contains monthly climate data in Germany, it can be used for
heating and cooling calculations (external temperature, heating / cooling days,
solar radiation).")
    (license (license:fsdg-compatible "CC BY 4.0"))))

(define-public r-clickstream
  (package
    (name "r-clickstream")
    (version "1.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clickstream" version))
       (sha256
        (base32 "1pbw74kd1ig6xc9llv8idizx0rya2454kpd9z62ybwvy68vyargs"))))
    (properties `((upstream-name . "clickstream")))
    (build-system r-build-system)
    (propagated-inputs (list r-rsolnp
                             r-reshape2
                             r-plyr
                             r-mass
                             r-linprog
                             r-igraph
                             r-ggplot2
                             r-data-table
                             r-clickclust
                             r-arules))
    (home-page "https://cran.r-project.org/package=clickstream")
    (synopsis "Analyzes Clickstreams Based on Markov Chains")
    (description
     "This package provides a set of tools to read, analyze and write lists of click
sequences on websites (i.e., clickstream).  A click can be represented by a
number, character or string.  Clickstreams can be modeled as zero- (only
computes occurrence probabilities), first- or higher-order Markov chains.")
    (license license:gpl2)))

(define-public r-clickr
  (package
    (name "r-clickr")
    (version "0.9.43")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clickR" version))
       (sha256
        (base32 "00qd4m6w5q99v6rm9wcxc8mwwi9ik8iiis0pzydb3qwrx0bfaj5m"))))
    (properties `((upstream-name . "clickR")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringdist r-future-apply r-future r-beeswarm))
    (home-page "https://cran.r-project.org/package=clickR")
    (synopsis
     "Semi-Automatic Preprocessing of Messy Data with Change Tracking for Dataset Cleaning")
    (description
     "This package provides tools for assessing data quality, performing exploratory
analysis, and semi-automatic preprocessing of messy data with change tracking
for integral dataset cleaning.")
    (license license:gpl2+)))

(define-public r-clickhousehttp
  (package
    (name "r-clickhousehttp")
    (version "0.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClickHouseHTTP" version))
       (sha256
        (base32 "0k8rl7vf4dd2jp8xk03v007mrmjz5w4lbgagmsylv73lm35485zh"))))
    (properties `((upstream-name . "ClickHouseHTTP")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr r-dbi r-data-table r-arrow))
    (home-page "https://github.com/patzaw/ClickHouseHTTP")
    (synopsis "Simple HTTP Database Interface to 'ClickHouse'")
    (description
     "@code{ClickHouse} (<https://clickhouse.com/>) is an open-source, high
performance columnar OLAP (online analytical processing of queries) database
management system for real-time analytics using SQL. This DBI backend relies on
the @code{ClickHouse} HTTP interface and support HTTPS protocol.")
    (license license:gpl3)))

(define-public r-clickclustcont
  (package
    (name "r-clickclustcont")
    (version "0.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClickClustCont" version))
       (sha256
        (base32 "1caymvpwvxq4rirnjm2kwzvqm1pl01rdc3785k8mq4k2m0n6l2rz"))))
    (properties `((upstream-name . "ClickClustCont")))
    (build-system r-build-system)
    (propagated-inputs (list r-gtools))
    (home-page "https://cran.r-project.org/package=ClickClustCont")
    (synopsis "Mixtures of Continuous Time Markov Models")
    (description
     "This package provides an expectation maximization (EM) algorithm to fit a
mixture of continuous time Markov models for use with clickstream or other
sequence type data.  Gallaugher, M.P.B and @code{McNicholas}, P.D. (2018)
<@code{arXiv:1802.04849>}.")
    (license license:gpl2+)))

(define-public r-clickclust
  (package
    (name "r-clickclust")
    (version "1.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClickClust" version))
       (sha256
        (base32 "09pb8fpddyzqznwxz1njpvwyqd45ywbaxj9sx5dzg134c7cz1z5j"))))
    (properties `((upstream-name . "ClickClust")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ClickClust")
    (synopsis "Model-Based Clustering of Categorical Sequences")
    (description
     "Clustering categorical sequences by means of finite mixtures with Markov model
components is the main utility of @code{ClickClust}.  The package also allows
detecting blocks of equivalent states by forward and backward state selection
procedures.")
    (license license:gpl2+)))

(define-public r-clickb
  (package
    (name "r-clickb")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clickb" version))
       (sha256
        (base32 "0cbhwvxb7xa34wf10saq65wiwlmw1cgnbiqgv6mfyd8dcdv25rwg"))))
    (properties `((upstream-name . "clickb")))
    (build-system r-build-system)
    (propagated-inputs (list r-mcmcpack r-mclust r-discreteweibull))
    (home-page "https://cran.r-project.org/package=clickb")
    (synopsis "Web Data Analysis by Bayesian Mixture of Markov Models")
    (description
     "Designed for web usage data analysis, it implements tools to process web
sequences and identify web browsing profiles through sequential classification.
Sequences clusters are identified by using a model-based approach, specifically
mixture of discrete time first-order Markov models for categorical web
sequences.  A Bayesian approach is used to estimate model parameters and
identify sequences classification as proposed by Fruehwirth-Schnatter and
Pamminger (2010) <doi:10.1214/10-BA606>.")
    (license license:expat)))

(define-public r-clickableimagemap
  (package
    (name "r-clickableimagemap")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clickableImageMap" version))
       (sha256
        (base32 "0p1wjar63y9qzss5i4pdfilkxaci0gi30vhw550db52pgcx21ywk"))))
    (properties `((upstream-name . "clickableImageMap")))
    (build-system r-build-system)
    (propagated-inputs (list r-gtable r-gridextra r-ggplotify r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=clickableImageMap")
    (synopsis "Implement 'tableGrob' Object as a Clickable Image Map")
    (description
     "Implement @code{tableGrob} object as a clickable image map.  The
@code{clickableImageMap} package is designed to be more convenient and more
configurable than the edit() function.  Limitations that I have encountered with
edit() are cannot control (1) positioning (2) size (3) appearance and formatting
of fonts In contrast, when the table is implemented as a @code{tableGrob}', all
of these features are controllable.  In particular, the ggplot2 grid system
allows exact positioning of the table relative to other graphics etc.")
    (license license:gpl2+)))

(define-public r-cliapp
  (package
    (name "r-cliapp")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cliapp" version))
       (sha256
        (base32 "0yaahalirm89s5snhqpz11s36fp5ri5af9w6ljqlvfd94y6ckvfb"))))
    (properties `((upstream-name . "cliapp")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-withr
                             r-selectr
                             r-r6
                             r-progress
                             r-prettycode
                             r-glue
                             r-fansi
                             r-crayon
                             r-cli))
    (home-page "https://github.com/r-lib/cliapp#readme")
    (synopsis "Create Rich Command Line Applications")
    (description
     "Create rich command line applications, with colors, headings, lists, alerts,
progress bars, etc.  It uses CSS for custom themes.  This package is now
superseded by the cli package.  Please use cli instead in new projects.")
    (license license:expat)))

(define-public r-clhs
  (package
    (name "r-clhs")
    (version "0.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clhs" version))
       (sha256
        (base32 "04hd0p51j15294fv1a9qx61p5yfmh8hcx784v3x1s0kx7km34saz"))))
    (properties `((upstream-name . "clhs")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp
                             r-sf
                             r-reshape2
                             r-rcpparmadillo
                             r-rcpp
                             r-raster
                             r-plyr
                             r-ggplot2
                             r-cluster))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/pierreroudier/clhs/")
    (synopsis "Conditioned Latin Hypercube Sampling")
    (description
     "Conditioned Latin hypercube sampling, as published by Minasny and
@code{McBratney} (2006) <DOI:10.1016/j.cageo.2005.12.009>.  This method proposes
to stratify sampling in presence of ancillary data.  An extension of this
method, which propose to associate a cost to each individual and take it into
account during the optimisation process, is also proposed (Roudier et al., 2012,
<DOI:10.1201/b12728>).")
    (license license:gpl2+)))

(define-public r-clevr
  (package
    (name "r-clevr")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clevr" version))
       (sha256
        (base32 "0r47mq0k55v3jvkzv1nlajqmcj03gq0igrxlcwhfrhbam9vwvapx"))))
    (properties `((upstream-name . "clevr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-matrix r-bh))
    (home-page "https://github.com/cleanzr/clevr")
    (synopsis "Clustering and Link Prediction Evaluation in R")
    (description
     "This package provides tools for evaluating link prediction and clustering
algorithms with respect to ground truth.  Includes efficient implementations of
common performance measures such as pairwise precision/recall, cluster
homogeneity/completeness, variation of information, Rand index etc.")
    (license license:gpl2)))

(define-public r-clespr
  (package
    (name "r-clespr")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clespr" version))
       (sha256
        (base32 "1993kd70w48a110im47vcpll0c6nfrm7m33r6l8rzgwnpsmcls8g"))))
    (properties `((upstream-name . "clespr")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-pbivnorm
                             r-mass
                             r-magic
                             r-foreach
                             r-doparallel
                             r-clordr
                             r-aer))
    (home-page "https://cran.r-project.org/package=clespr")
    (synopsis "Composite Likelihood Estimation for Spatial Data")
    (description
     "Composite likelihood approach is implemented to estimating statistical models
for spatial ordinal and proportional data based on Feng et al. (2014)
<doi:10.1002/env.2306>.  Parameter estimates are identified by maximizing
composite log-likelihood functions using the limited memory BFGS optimization
algorithm with bounding constraints, while standard errors are obtained by
estimating the Godambe information matrix.")
    (license license:gpl2)))

(define-public r-clear
  (package
    (name "r-clear")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cleaR" version))
       (sha256
        (base32 "1vvmaaqqrd65l9hm3yjf88ajmlaf1sl7iy816ypjy9ww9x7dcyf4"))))
    (properties `((upstream-name . "cleaR")))
    (build-system r-build-system)
    (home-page "https://github.com/joundso/cleaR")
    (synopsis "Clean the R Console and Environment")
    (description
     "Small package to clean the R console and the R environment with the call of just
one function.")
    (license license:gpl3)))

(define-public r-cleants
  (package
    (name "r-cleants")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cleanTS" version))
       (sha256
        (base32 "04k84989a0jvdd015yrd6wqnfk19yq0a4qpdnm3l0137h7s2xq8k"))))
    (properties `((upstream-name . "cleanTS")))
    (build-system r-build-system)
    (propagated-inputs (list r-transformr
                             r-tibble
                             r-stringr
                             r-shiny
                             r-lubridate
                             r-imputets
                             r-imputetestbench
                             r-glue
                             r-ggtext
                             r-ggplot2
                             r-gganimate
                             r-data-table))
    (home-page "https://github.com/Mayur1009/cleanTS")
    (synopsis "Testbench for Univariate Time Series Cleaning")
    (description
     "This package provides a reliable and efficient tool for cleaning univariate time
series data.  It implements reliable and efficient procedures for automating the
process of cleaning univariate time series data.  The package provides
integration with already developed and deployed tools for missing value
imputation and outlier detection.  It also provides a way of visualizing large
time-series data in different resolutions.")
    (license license:gpl3+)))

(define-public r-cleanrmd
  (package
    (name "r-cleanrmd")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cleanrmd" version))
       (sha256
        (base32 "120jg8kp6m6pka5nvgvwjyl4ljybv193sqvyjr8p19w3q7665nm6"))))
    (properties `((upstream-name . "cleanrmd")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmarkdown r-jsonlite r-htmltools))
    (home-page "https://pkg.garrickadenbuie.com/cleanrmd/")
    (synopsis "Clean Class-Less 'R Markdown' HTML Documents")
    (description
     "This package provides a collection of clean R Markdown HTML document templates
using classy-looking classless CSS styles.  These documents use a minimal set of
dependencies but still look great, making them suitable for use a package
vignettes or for sharing results via email.")
    (license license:expat)))

(define-public r-cleanr
  (package
    (name "r-cleanr")
    (version "1.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cleanr" version))
       (sha256
        (base32 "04rjl8q6hlmw4xc4p4khda6090d39dwig331fzjqiad3bs2xavdy"))))
    (properties `((upstream-name . "cleanr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rprojroot r-pkgload r-fritools r-checkmate))
    (native-inputs (list r-rasciidoc))
    (home-page "https://gitlab.com/fvafrcu/cleanr")
    (synopsis "Helps You to Code Cleaner")
    (description
     "Check your R code for some of the most common layout flaws.  Many tried to teach
us how to write code less dreadful, be it implicitly as B. W. Kernighan and D.
M. Ritchie (1988) <ISBN:0-13-110362-8> in The C Programming Language did, be it
explicitly as R.C. Martin (2008) <ISBN:0-13-235088-2> in Clean Code: A Handbook
of Agile Software Craftsmanship did.  So we should check our code for files too
long or wide, functions with too many lines, too wide lines, too many arguments
or too many levels of nesting.  Note: This is not a static code analyzer like
pylint or the like.  Checkout <https://cran.r-project.org/package=lintr>
instead.")
    (license license:bsd-2)))

(define-public r-cleannlp
  (package
    (name "r-cleannlp")
    (version "3.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cleanNLP" version))
       (sha256
        (base32 "0qddi649ifgwlgbv7jh0im00dhhs740sgpkid39j01kdsv9czlil"))))
    (properties `((upstream-name . "cleanNLP")))
    (build-system r-build-system)
    (inputs (list python))
    (propagated-inputs (list r-udpipe r-stringi r-reticulate r-matrix))
    (native-inputs (list r-knitr))
    (home-page "https://statsmaths.github.io/cleanNLP/")
    (synopsis "Tidy Data Model for Natural Language Processing")
    (description
     "This package provides a set of fast tools for converting a textual corpus into a
set of normalized tables.  Users may make use of the udpipe back end with no
external dependencies, or a Python back ends with @code{spaCy}
<https://spacy.io>.  Exposed annotation tasks include tokenization, part of
speech tagging, named entity recognition, and dependency parsing.")
    (license license:lgpl2.0)))

(define-public r-cleaningvalidation
  (package
    (name "r-cleaningvalidation")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CleaningValidation" version))
       (sha256
        (base32 "0wfywvmglsjckf734g7lq2gq9366ya2bsrihiinx9n37ydc5w6kg"))))
    (properties `((upstream-name . "CleaningValidation")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-lme4
                             r-ggplot2
                             r-dunn-test
                             r-dplyr
                             r-cowplot
                             r-boot
                             r-aer))
    (home-page "https://github.com/ChandlerXiandeYang/CleaningValidation")
    (synopsis
     "Cleaning Validation Functions for Pharmaceutical Cleaning Process")
    (description
     "This package provides essential Cleaning Validation functions for complying with
pharmaceutical cleaning process regulatory standards.  The package includes
non-parametric methods to analyze drug active-ingredient residue (DAR), cleaning
agent residue (CAR), and microbial colonies (Mic) for non-Poisson distributions.
 Additionally, Poisson methods are provided for Mic analysis when Mic data
follow a Poisson distribution.")
    (license license:gpl3)))

(define-public r-cleangeo
  (package
    (name "r-cleangeo")
    (version "0.3-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cleangeo" version))
       (sha256
        (base32 "0ijxa9d871zb3j7ks7va0lqrv5cywb8kiciy1c42faif1xk8wlxp"))))
    (properties `((upstream-name . "cleangeo")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp r-sf))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/eblondel/cleangeo")
    (synopsis "Cleaning Geometries from Spatial Objects")
    (description
     "This package provides a set of utility tools to inspect spatial objects,
facilitate handling and reporting of topology errors and geometry validity issue
with sp objects.  Finally, it provides a geometry cleaner that will fix all
geometry problems, and eliminate (at least reduce) the likelihood of having
issues when doing spatial data processing.")
    (license license:gpl2+)))

(define-public r-cleaner
  (package
    (name "r-cleaner")
    (version "1.5.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cleaner" version))
       (sha256
        (base32 "1rkyrp8pa5sznjszxfwgkiymmdwrm87k56ghgk39yp8f919ifkpl"))))
    (properties `((upstream-name . "cleaner")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-rlang
                             r-pillar
                             r-knitr
                             r-crayon
                             r-backports))
    (home-page "https://msberends.github.io/cleaner/")
    (synopsis "Fast and Easy Data Cleaning")
    (description
     "Data cleaning functions for classes logical, factor, numeric, character,
currency and Date to make data cleaning fast and easy.  Relying on very few
dependencies, it provides smart guessing, but with user options to override
anything if needed.")
    (license license:gpl2)))

(define-public r-cleanepi
  (package
    (name "r-cleanepi")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cleanepi" version))
       (sha256
        (base32 "10vpdynil63gnx9rdzzdcaprn6639qgc415wg615izykz7c0g42l"))))
    (properties `((upstream-name . "cleanepi")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr
                             r-snakecase
                             r-rlang
                             r-readr
                             r-numberize
                             r-matchmaker
                             r-magrittr
                             r-lubridate
                             r-linelist
                             r-janitor
                             r-dplyr
                             r-checkmate
                             r-arsenal))
    (native-inputs (list r-knitr))
    (home-page "https://epiverse-trace.github.io/cleanepi/")
    (synopsis "Clean and Standardize Epidemiological Data")
    (description
     "Cleaning and standardizing tabular data package, tailored specifically for
curating epidemiological data.  It streamlines various data cleaning tasks that
are typically expected when working with datasets in epidemiology.  It returns
the processed data in the same format, ensuring seamless integration into
existing workflows.  Additionally, it generates a comprehensive report detailing
the outcomes of each cleaning task.")
    (license license:expat)))

(define-public r-cleandata
  (package
    (name "r-cleandata")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cleandata" version))
       (sha256
        (base32 "1lm7k25j16p888xvd7rzzd3sb3namzjlpjn22xmmpzlzyl0h7dhk"))))
    (properties `((upstream-name . "cleandata")))
    (build-system r-build-system)
    (native-inputs (list r-r-rsp))
    (home-page "https://github.com/sherrisherry/cleandata")
    (synopsis
     "To Inspect and Manipulate Data; and to Keep Track of This Process")
    (description
     "This package provides functions to work with data frames to prepare data for
further analysis.  The functions for imputation, encoding, partitioning, and
other manipulation can produce log files to keep track of process.")
    (license license:expat)))

(define-public r-cleancall
  (package
    (name "r-cleancall")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cleancall" version))
       (sha256
        (base32 "079l5knm3lrvnfbwcvg2g62sqbg7iira5x0gxd4fk1pysnm5hwmf"))))
    (properties `((upstream-name . "cleancall")))
    (build-system r-build-system)
    (home-page "https://github.com/r-lib/cleancall#readme")
    (synopsis "C Resource Cleanup via Exit Handlers")
    (description
     "Wrapper of .Call() that runs exit handlers to clean up C resources.  Helps
managing C (non-R) resources while using the R API.")
    (license license:expat)))

(define-public r-cleanbsequences
  (package
    (name "r-cleanbsequences")
    (version "2.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CleanBSequences" version))
       (sha256
        (base32 "1ijybrl1x2rb70x6q07bbyv5mm0gw927wnf94mhz199z4s37iv4g"))))
    (properties `((upstream-name . "CleanBSequences")))
    (build-system r-build-system)
    (propagated-inputs (list r-pwalign r-biostrings))
    (home-page "https://cran.r-project.org/package=CleanBSequences")
    (synopsis "Curing of Biological Sequences")
    (description
     "Curates biological sequences massively, quickly, without errors and without
internet connection.  Biological sequences curing is performed by aligning the
forward and / or revers primers or ends of cloning vectors with the sequences to
be cleaned.  After the alignment, new subsequences are generated without
biological fragment not desired by the user.  Pozzi et al (2020)
<doi:10.1007/s00438-020-01671-z>.")
    (license license:gpl2+)))

(define-public r-clean
  (package
    (name "r-clean")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clean" version))
       (sha256
        (base32 "0zvk3a5yz54g2mn7y1d91z6ljglbyq1hkh4iip1dfyi15chrqv7y"))))
    (properties `((upstream-name . "clean")))
    (build-system r-build-system)
    (propagated-inputs (list r-cleaner))
    (home-page "https://github.com/msberends/cleaner")
    (synopsis "Fast and Easy Data Cleaning")
    (description
     "This package provides a wrapper around the new cleaner package, that allows data
cleaning functions for classes logical', factor', numeric', character', currency
and Date to make data cleaning fast and easy.  Relying on very few dependencies,
it provides smart guessing, but with user options to override anything if
needed.")
    (license license:gpl2)))

(define-public r-clda
  (package
    (name "r-clda")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clda" version))
       (sha256
        (base32 "03zfanvpz1h42h2z38a63fck1p5hqig4w2svknzpw7mryji5q9b1"))))
    (properties `((upstream-name . "clda")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=clda")
    (synopsis "Convolution-Based Linear Discriminant Analysis")
    (description
     "This package contains a time series classification method that obtains a set of
filters that maximize the between-class and minimize the within-class distances.")
    (license license:gpl3+)))

(define-public r-cld3
  (package
    (name "r-cld3")
    (version "1.6.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cld3" version))
       (sha256
        (base32 "0zxl4h2bx4kkhz4jax2nlx2bqf0vfy41ibds4iasv848jqifnxfs"))))
    (properties `((upstream-name . "cld3")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (native-inputs (list pkg-config))
    (home-page "https://cran.r-project.org/package=cld3")
    (synopsis "Google's Compact Language Detector 3")
    (description
     "Google's Compact Language Detector 3 is a neural network model for language
identification and the successor of cld2 (available from CRAN).  The algorithm
is still experimental and takes a novel approach to language detection with
different properties and outcomes.  It can be useful to combine this with the
Bayesian classifier results from cld2'.  See
<https://github.com/google/cld3#readme> for more information.")
    (license license:asl2.0)))

(define-public r-cld2
  (package
    (name "r-cld2")
    (version "1.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cld2" version))
       (sha256
        (base32 "1mzsr6rmqhvvk5p38y3kwd5hmyiaxgg60ay2gvh4d8psn7fx9cyv"))))
    (properties `((upstream-name . "cld2")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://cran.r-project.org/package=cld2")
    (synopsis "Google's Compact Language Detector 2")
    (description
     "Bindings to Google's C++ library Compact Language Detector 2 (see
<https://github.com/cld2owners/cld2#readme> for more information).
Probabilistically detects over 80 languages in plain text or HTML. For
mixed-language input it returns the top three detected languages and their
approximate proportion of the total classified text bytes (e.g. 80% English and
20% French out of 1000 bytes).  There is also a cld3 package on CRAN which uses
a neural network model instead.")
    (license license:asl2.0)))

(define-public r-clast
  (package
    (name "r-clast")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CLAST" version))
       (sha256
        (base32 "10g07jdnmbjk5k5xy4c8jh45aw16bjdwik91djiml82ysnbqiq9y"))))
    (properties `((upstream-name . "CLAST")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CLAST")
    (synopsis "Exact Confidence Limits after a Sequential Trial")
    (description
     "The user first provides design vectors n, a and b as well as null (p0) and
alternative (p1) benchmark values for the probability of success.  The key
function \"mv.plots.SM()\" calculates mean values of exact upper and lower limits
based on four different rank ordering methods.  These plots form the basis of
selecting a rank ordering.  The function \"inference()\" calculates exact limits
from a provided realisation and ordering choice.  For more information, see
\"Exact confidence limits after a group sequential single arm binary trial\" by
Lloyd, C.J. (2020), Statistics in Medicine, Volume 38, 2389-2399,
<doi:10.1002/sim.8909>.")
    (license license:gpl2)))

(define-public r-classmap
  (package
    (name "r-classmap")
    (version "1.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "classmap" version))
       (sha256
        (base32 "125895ym1jhdd4gm7ywlhfzn66kra1a8bbkq3502vg38zvdsm3ci"))))
    (properties `((upstream-name . "classmap")))
    (build-system r-build-system)
    (propagated-inputs (list r-rpart
                             r-robustbase
                             r-randomforest
                             r-kernlab
                             r-gridextra
                             r-ggplot2
                             r-e1071
                             r-cluster
                             r-cellwise))
    (native-inputs (list r-knitr))
    (home-page "https://doi.org/10.1080/00401706.2021.1927849")
    (synopsis "Visualizing Classification Results")
    (description
     "This package provides tools to visualize the results of a classification of
cases.  The graphical displays include stacked plots, silhouette plots, quasi
residual plots, and class maps.  Implements the techniques described and
illustrated in Raymaekers, Rousseeuw and Hubert (2021), Class maps for
visualizing classification results, Technometrics, appeared online.
<doi:10.1080/00401706.2021.1927849> (open access) and Raymaekers and Rousseeuw
(2021), Silhouettes and quasi residual plots for neural nets and tree-based
classifiers, <@code{arXiv:2106.08814>}.  Examples can be found in the vignettes:
\"Discriminant_analysis_examples\",\"K_nearest_neighbors_examples\",
\"Support_vector_machine_examples\", \"Rpart_examples\", \"Random_forest_examples\",
and \"Neural_net_examples\".")
    (license license:gpl2+)))

(define-public r-classifly
  (package
    (name "r-classifly")
    (version "0.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "classifly" version))
       (sha256
        (base32 "195pa9g8764m8ddkz7wwzszh2zqqnx2fm7cdsm9q73k6qgf61xj8"))))
    (properties `((upstream-name . "classifly")))
    (build-system r-build-system)
    (propagated-inputs (list r-plyr r-class))
    (home-page "http://had.co.nz/classifly")
    (synopsis "Explore Classification Models in High Dimensions")
    (description
     "Given $p$-dimensional training data containing $d$ groups (the design space), a
classification algorithm (classifier) predicts which group new data belongs to.
Generally the input to these algorithms is high dimensional, and the boundaries
between groups will be high dimensional and perhaps curvilinear or
multi-faceted.  This package implements methods for understanding the division
of space between the groups.")
    (license license:expat)))

(define-public r-classifierplots
  (package
    (name "r-classifierplots")
    (version "1.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "classifierplots" version))
       (sha256
        (base32 "0agxm3vrbs8lqhk1xvfc3wzf0q0hxhgyp23j5qi5mi1drgnw1jj1"))))
    (properties `((upstream-name . "classifierplots")))
    (build-system r-build-system)
    (propagated-inputs (list r-rocr
                             r-rcpp
                             r-png
                             r-gridextra
                             r-ggplot2
                             r-data-table
                             r-caret))
    (home-page "https://github.com/adefazio/classifierplots")
    (synopsis
     "Generates a Visualization of Classifier Performance as a Grid of Diagnostic Plots")
    (description
     "Generates a visualization of binary classifier performance as a grid of
diagnostic plots with just one function call.  Includes ROC curves, prediction
density, accuracy, precision, recall and calibration plots, all using ggplot2
for easy modification.  Debug your binary classifiers faster and easier!")
    (license (license:fsdg-compatible "BSD 3-clause License + file LICENSE"))))

(define-public r-classgraph
  (package
    (name "r-classgraph")
    (version "0.7-6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "classGraph" version))
       (sha256
        (base32 "10nyrs5xh70ajhi1q6pvx4s5lkl2r46ddxanhiyn9vv9swr2hzsw"))))
    (properties `((upstream-name . "classGraph")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgraphviz r-graph))
    (home-page "https://cran.r-project.org/package=classGraph")
    (synopsis "Construct Graphs of S4 Class Hierarchies")
    (description
     "Construct directed graphs of S4 class hierarchies and visualize them.  In
general, these graphs typically are DAGs (directed acyclic graphs), often simple
trees in practice.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-classcomparison
  (package
    (name "r-classcomparison")
    (version "3.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClassComparison" version))
       (sha256
        (base32 "0lyc437cmf5yv6ikfcvqdi21z8f2pa60z0czf0cig1w1n65x3lw1"))))
    (properties `((upstream-name . "ClassComparison")))
    (build-system r-build-system)
    (propagated-inputs (list r-oompabase r-biobase))
    (home-page "http://oompa.r-forge.r-project.org/")
    (synopsis
     "Classes and Methods for \"Class Comparison\" Problems on Microarrays")
    (description
     "Defines the classes used for \"class comparison\" problems in the OOMPA project
(<http://oompa.r-forge.r-project.org/>).  Class comparison includes tests for
differential expression; see Simon's book for details on typical problem types.")
    (license license:asl2.0)))

(define-public r-clarketest
  (package
    (name "r-clarketest")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clarkeTest" version))
       (sha256
        (base32 "0p2lhpdic6rlx6qrb0kkc94anr1pbpvdznykli6ggsd4p5amqbpl"))))
    (properties `((upstream-name . "clarkeTest")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=clarkeTest")
    (synopsis "Distribution-Free Tests of Non-Nested Models")
    (description
     "Implementation of Clarke's distribution-free test of non-nested models.
Currently supported model functions are: lm(), glm() ('binomial', poisson',
negative binomial links), polr() ('MASS'), clm() ('ordinal'), and multinom()
('nnet').  For more information on the test, see Clarke (2007)
<doi:10.1093/pan/mpm004>.")
    (license license:gpl2+)))

(define-public r-clarify
  (package
    (name "r-clarify")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clarify" version))
       (sha256
        (base32 "0cda1xvcfd0lz3802h945jw98ala68z89vfgdixv4z6yn9fqzzcq"))))
    (properties `((upstream-name . "clarify")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-pbapply
                             r-mvnfast
                             r-marginaleffects
                             r-insight
                             r-ggplot2
                             r-chk))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/iqss/clarify")
    (synopsis "Simulation-Based Inference for Regression Models")
    (description
     "This package performs simulation-based inference as an alternative to the delta
method for obtaining valid confidence intervals and p-values for regression
post-estimation quantities, such as average marginal effects and predictions at
representative values.  This framework for simulation-based inference is
especially useful when the resulting quantity is not normally distributed and
the delta method approximation fails.  The methodology is described in King,
Tomz, and Wittenberg (2000) <doi:10.2307/2669316>.  clarify is meant to replace
some of the functionality of the archived package Zelig'; see the vignette
\"Translating Zelig to clarify\" for replicating this functionality.")
    (license license:gpl3+)))

(define-public r-clarifai
  (package
    (name "r-clarifai")
    (version "0.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clarifai" version))
       (sha256
        (base32 "0igi4xl27nz0r85hpws2zfc2gn5z2nmywp3saxgp74mh2y99lg6s"))))
    (properties `((upstream-name . "clarifai")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-curl))
    (native-inputs (list r-knitr))
    (home-page "http://github.com/soodoku/clarifai")
    (synopsis "Access to Clarifai API")
    (description
     "Get description of images from Clarifai API. For more information, see
<http://clarifai.com>.  Clarifai uses a large deep learning cloud to come up
with descriptive labels of the things in an image.  It also provides how
confident it is about each of the labels.")
    (license license:expat)))

(define-public r-clap
  (package
    (name "r-clap")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clap" version))
       (sha256
        (base32 "1mc2aqvf4l4dp39if2m60vn01nww3pikpsmw2m42iw5rzzxgswpq"))))
    (properties `((upstream-name . "clap")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-mclust r-fnn r-dplyr))
    (home-page "https://github.com/pridiltal/clap")
    (synopsis "Detecting Class Overlapping Regions in Multidimensional Data")
    (description
     "The issue of overlapping regions in multidimensional data arises when different
classes or clusters share similar feature representations, making it challenging
to delineate distinct boundaries between them accurately.  This package provides
methods for detecting and visualizing these overlapping regions using
partitional clustering techniques based on nearest neighbor distances.")
    (license license:gpl3)))

(define-public r-clamr
  (package
    (name "r-clamr")
    (version "2.1-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClamR" version))
       (sha256
        (base32 "1qf0xflzww2vdv3sl2s8lncmv4k7aa4wbgpqm9v8slsa615a6n09"))))
    (properties `((upstream-name . "ClamR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ClamR")
    (synopsis "Time Series Modeling for Climate Change Proxies")
    (description
     "Implementation of the Wilkinson and Ivany (2002) approach to paleoclimate
analysis, applied to isotope data extracted from clams.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-clam
  (package
    (name "r-clam")
    (version "2.6.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "clam" version))
       (sha256
        (base32 "0kfkr5rnzmfj1jjf2jwkaxnddalid982gbd44pgz4y1nw00kj71c"))))
    (properties `((upstream-name . "clam")))
    (build-system r-build-system)
    (propagated-inputs (list r-rintcal r-rice r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=clam")
    (synopsis "Classical Age-Depth Modelling of Cores from Deposits")
    (description
     "This package performs classical age-depth modelling of dated sediment deposits -
prior to applying more sophisticated techniques such as Bayesian age-depth
modelling.  Any radiocarbon dated depths are calibrated.  Age-depth models are
constructed by sampling repeatedly from the dated levels, each time drawing
age-depth curves.  Model types include linear interpolation, linear or
polynomial regression, and a range of splines.  See Blaauw (2010)
<doi:10.1016/j.quageo.2010.01.002>.")
    (license license:gpl2+)))

(define-public r-claimsproblems
  (package
    (name "r-claimsproblems")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ClaimsProblems" version))
       (sha256
        (base32 "10ylcikss9ld393cb40ddkkz7as1d5bnrna0sqwdrn1cb3p9p4w2"))))
    (properties `((upstream-name . "ClaimsProblems")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgl r-pracma r-geometry))
    (home-page "https://cran.r-project.org/package=ClaimsProblems")
    (synopsis "Analysis of Conflicting Claims")
    (description
     "The analysis of conflicting claims arises when an amount has to be divided among
a set of agents with claims that exceed what is available.  A rule is a way of
selecting a division among the claimants.  This package computes the main rules
introduced in the literature from the old times until nowadays.  The inventory
of rules covers the proportional and the adjusted proportional rules, the
constrained equal awards and the constrained equal losses rules, the constrained
egalitarian, the Pinilesâ and the minimal overlap rules, the random arrival
and the Talmud rules.  Besides, the Dominguez and Thomson and the average of
awards rules are also included.  All of them can be found in the book of W.
Thomson (2019), How to divide when there isn't enough.  From Aristotle, the
Talmud, and Maimonides to the axiomatics of resource allocation', with the
exception of the average of awards rule (MirÃ¡s Calvo et al. (2022),
<doi:10.1007/s00355-022-01414-6>).  In addition, graphical diagrams allow the
user to represent, among others, the set of awards, the paths of awards, and the
schedules of awards of a rule, and some indexes.  A good understanding of the
similarities and the differences of the rules is useful for a better decision
making.  Therefore this package could be helpful to students, researchers and
managers alike.")
    (license license:gpl3)))

(define-public r-cladorcpp
  (package
    (name "r-cladorcpp")
    (version "0.15.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cladoRcpp" version))
       (sha256
        (base32 "0msay6yvm6wc964gwrz31ky5w4mizakji3j6rpkydz0zlrl52v1j"))))
    (properties `((upstream-name . "cladoRcpp")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "http://phylo.wikidot.com/biogeobears")
    (synopsis "C++ Implementations of Phylogenetic Cladogenesis Calculations")
    (description
     "Various cladogenesis-related calculations that are slow in pure R are
implemented in C++ with Rcpp.  These include the calculation of the probability
of various scenarios for the inheritance of geographic range at the divergence
events on a phylogenetic tree, and other calculations necessary for models which
are not continuous-time markov chains (CTMC), but where change instead occurs
instantaneously at speciation events.  Typically these models must assess the
probability of every possible combination of (ancestor state, left descendent
state, right descendent state).  This means that there are up to (# of states)^3
combinations to investigate, and in biogeographical models, there can easily be
hundreds of states, so calculation time becomes an issue.  C++ implementation
plus clever tricks (many combinations can be eliminated a priori) can greatly
speed the computation time over naive R implementations.  CITATION INFO: This
package is the result of my Ph.D. research, please cite the package if you use
it! Type: citation(package=\"@code{cladoRcpp}\") to get the citation information.")
    (license license:gpl2+)))

(define-public r-claddis
  (package
    (name "r-claddis")
    (version "0.7.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Claddis" version))
       (sha256
        (base32 "1a5zfqv94bfk24g99r4yaqsydny0sl638zhm4k175xc250yraj7p"))))
    (properties `((upstream-name . "Claddis")))
    (build-system r-build-system)
    (propagated-inputs (list r-strap
                             r-phytools
                             r-partitions
                             r-multicool
                             r-geoscale
                             r-clipr
                             r-ape))
    (home-page "https://cran.r-project.org/package=Claddis")
    (synopsis "Measuring Morphological Diversity and Evolutionary Tempo")
    (description
     "Measures morphological diversity from discrete character data and estimates
evolutionary tempo on phylogenetic trees.  Imports morphological data from
#NEXUS (Maddison et al. (1997) <doi:10.1093/sysbio/46.4.590>) format with
read_nexus_matrix(), and writes to both #NEXUS and TNT format (Goloboff et al.
(2008) <doi:10.1111/j.1096-0031.2008.00217.x>).  Main functions are
test_rates(), which implements AIC and likelihood ratio tests for discrete
character rates introduced across Lloyd et al. (2012)
<doi:10.1111/j.1558-5646.2011.01460.x>, Brusatte et al. (2014)
<doi:10.1016/j.cub.2014.08.034>, Close et al. (2015)
<doi:10.1016/j.cub.2015.06.047>, and Lloyd (2016) <doi:10.1111/bij.12746>, and
calculate_morphological_distances(), which implements multiple discrete
character distance metrics from Gower (1971) <doi:10.2307/2528823>, Wills (1998)
<doi:10.1006/bijl.1998.0255>, Lloyd (2016) <doi:10.1111/bij.12746>, and Hopkins
and St John (2018) <doi:10.1098/rspb.2018.1784>.  This also includes the GED
correction from Lehmann et al. (2019) <doi:10.1111/pala.12430>.  Multiple
functions implement morphospace plots: plot_chronophylomorphospace() implements
Sakamoto and Ruta (2012) <doi:10.1371/journal.pone.0039752>, plot_morphospace()
implements Wills et al. (1994) <doi:10.1017/S009483730001263X>,
plot_changes_on_tree() implements Wang and Lloyd (2016)
<doi:10.1098/rspb.2016.0214>, and plot_morphospace_stack() implements Foote
(1993) <doi:10.1017/S0094837300015864>.  Other functions include
safe_taxonomic_reduction(), which implements Wilkinson (1995)
<doi:10.1093/sysbio/44.4.501>, map_dollo_changes() implements the Dollo
stochastic character mapping of Tarver et al. (2018) <doi:10.1093/gbe/evy096>,
and estimate_ancestral_states() implements the ancestral state options of Lloyd
(2018) <doi:10.1111/pala.12380>.  calculate_tree_length() and
reconstruct_ancestral_states() implements the generalised algorithms from
Swofford and Maddison (1992; no doi).")
    (license license:gpl2+)))

(define-public r-cla
  (package
    (name "r-cla")
    (version "0.96-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CLA" version))
       (sha256
        (base32 "1jrk6zr5x5kypa4zgwdhbnihxgi9bl34xmgqg7rlpsl2v53013mi"))))
    (properties `((upstream-name . "CLA")))
    (build-system r-build-system)
    (home-page "https://gitlab.math.ethz.ch/maechler/CLA/")
    (synopsis "Critical Line Algorithm in Pure R")
    (description
     "This package implements Markowitz Critical Line Algorithm ('CLA') for classical
mean-variance portfolio optimization, see Markowitz (1952)
<doi:10.2307/2975974>.  Care has been taken for correctness in light of previous
buggy implementations.")
    (license (list license:gpl3+
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-ckmrpop
  (package
    (name "r-ckmrpop")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CKMRpop" version))
       (sha256
        (base32 "0d4sai2h2cfzh4hbg8yh7wqb459j948j3s0m218d3gcippm22jpb"))))
    (properties `((upstream-name . "CKMRpop")))
    (build-system r-build-system)
    (propagated-inputs (list r-vroom
                             r-tidyr
                             r-tidygraph
                             r-tibble
                             r-stringr
                             r-readr
                             r-rcpp
                             r-purrr
                             r-magrittr
                             r-igraph
                             r-ggraph
                             r-ggplot2
                             r-ggforce
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CKMRpop")
    (synopsis
     "Forward-in-Time Simulation and Tallying of Pairwise Relationships")
    (description
     "This package provides an R wrapper around the program spip
(<https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1471-8286.2005.00884.x>), a
C program for the simulation of pedigrees within age-structured populations with
user-specified life histories.  Also includes a variety of functions to parse
spip output to compile information about related pairs amongst simulated,
sampled individuals, to assess the feasibility and potential accuracy of
close-kin mark-recapture (CKMR).  Full documentation and vignettes are mirrored
at <https://eriqande.github.io/CKMRpop/index.html> and can be read online there.")
    (license license:cc0)))

(define-public r-ckmeans-1d-dp
  (package
    (name "r-ckmeans-1d-dp")
    (version "4.3.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Ckmeans.1d.dp" version))
       (sha256
        (base32 "0ga0pjva0samik36mapllqr34w8fqrr3f6drnch7ziy1igdrj1d3"))))
    (properties `((upstream-name . "Ckmeans.1d.dp")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=Ckmeans.1d.dp")
    (synopsis "Optimal, Fast, and Reproducible Univariate Clustering")
    (description
     "Fast, optimal, and reproducible weighted univariate clustering by dynamic
programming.  Four problems are solved, including univariate k-means (Wang &
Song 2011) <doi:10.32614/RJ-2011-015> (Song & Zhong 2020)
<doi:10.1093/bioinformatics/btaa613>, k-median, k-segments, and multi-channel
weighted k-means.  Dynamic programming is used to minimize the sum of (weighted)
within-cluster distances using respective metrics.  Its advantage over heuristic
clustering in efficiency and accuracy is pronounced when there are many
clusters.  Multi-channel weighted k-means groups multiple univariate signals
into k clusters.  An auxiliary function generates histograms adaptive to
patterns in data.  This package provides a powerful set of tools for univariate
data analysis with guaranteed optimality, efficiency, and reproducibility,
useful for peak calling on temporal, spatial, and spectral data.")
    (license license:lgpl3+)))

(define-public r-cklrt
  (package
    (name "r-cklrt")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CKLRT" version))
       (sha256
        (base32 "1d8sg3ncns3fpjaghz1h1z9nfrl31v09xijrzzsias8xjrpi191b"))))
    (properties `((upstream-name . "CKLRT")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppeigen r-rcpp r-nlme r-mgcv r-mass))
    (home-page "https://cran.r-project.org/package=CKLRT")
    (synopsis
     "Composite Kernel Machine Regression Based on Likelihood Ratio Test")
    (description
     "Composite Kernel Machine Regression based on Likelihood Ratio Test (CKLRT): in
this package, we develop a kernel machine regression framework to model the
overall genetic effect of a SNP-set, considering the possible GE interaction.
Specifically, we use a composite kernel to specify the overall genetic effect
via a nonparametric function and we model additional covariates parametrically
within the regression framework.  The composite kernel is constructed as a
weighted average of two kernels, one corresponding to the genetic main effect
and one corresponding to the GE interaction effect.  We propose a likelihood
ratio test (LRT) and a restricted likelihood ratio test (RLRT) for statistical
significance.  We derive a Monte Carlo approach for the finite sample
distributions of LRT and RLRT statistics. (N. Zhao, H. Zhang, J. Clark, A.
Maity, M. Wu.  Composite Kernel Machine Regression based on Likelihood Ratio
Test with Application for Combined Genetic and Gene-environment Interaction
Effect (Submitted).).")
    (license license:gpl3)))

(define-public r-ckat
  (package
    (name "r-ckat")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CKAT" version))
       (sha256
        (base32 "03vxl91z2mhi1h0xgcwhw63mvj56156zgphm16ijdff63pqxaryr"))))
    (properties `((upstream-name . "CKAT")))
    (build-system r-build-system)
    (propagated-inputs (list r-compquadform))
    (home-page "https://cran.r-project.org/package=CKAT")
    (synopsis "Composite Kernel Association Test for Pharmacogenetics Studies")
    (description
     "Composite Kernel Association Test (CKAT) is a flexible and robust kernel machine
based approach to jointly test the genetic main effect and gene-treatment
interaction effect for a set of single-nucleotide polymorphisms (SNPs) in
pharmacogenetics (PGx) assessments embedded within randomized clinical trials.")
    (license license:gpl2)))

(define-public r-ckanr
  (package
    (name "r-ckanr")
    (version "0.7.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ckanr" version))
       (sha256
        (base32 "10bxlvx70wik3rih5ms8jb9nb111qca4ydz8rj2raywm8bd3rpcj"))))
    (properties `((upstream-name . "ckanr")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr
                             r-jsonlite
                             r-dplyr
                             r-dbplyr
                             r-dbi
                             r-crul))
    (home-page
     "https://docs.ropensci.org/ckanr/https://github.com/ropensci/ckanr")
    (synopsis
     "Client for the Comprehensive Knowledge Archive Network ('CKAN') API")
    (description
     "Client for CKAN API (<https://ckan.org/>).  Includes interface to CKAN APIs for
search, list, show for packages, organizations, and resources.  In addition,
provides an interface to the datastore API.")
    (license license:expat)))

(define-public r-cjoint
  (package
    (name "r-cjoint")
    (version "2.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cjoint" version))
       (sha256
        (base32 "1byahl2x3mdz66cicyjbi5qrcbq9xqcyyny5rzxkg5m5nfgxprqk"))))
    (properties `((upstream-name . "cjoint")))
    (build-system r-build-system)
    (propagated-inputs (list r-survey
                             r-shinyjs
                             r-shiny
                             r-sandwich
                             r-matrix
                             r-lmtest
                             r-ggplot2
                             r-dt))
    (home-page "https://cran.r-project.org/package=cjoint")
    (synopsis "AMCE Estimator for Conjoint Experiments")
    (description
     "An R implementation of the Average Marginal Component-specific Effects (AMCE)
estimator presented in Hainmueller, J., Hopkins, D., and Yamamoto T. (2014)
<DOI:10.1093/pan/mpt024> Causal Inference in Conjoint Analysis: Understanding
Multi-Dimensional Choices via Stated Preference Experiments.  Political Analysis
22(1):1-30.")
    (license license:gpl2+)))

(define-public r-cjive
  (package
    (name "r-cjive")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CJIVE" version))
       (sha256
        (base32 "1937q125w39rsl2i5imqlk25r7mr1hvpmjy2br0xq98vdkxazqsq"))))
    (properties `((upstream-name . "CJIVE")))
    (build-system r-build-system)
    (propagated-inputs (list r-rootsolve
                             r-reshape2
                             r-psych
                             r-gplots
                             r-ggplot2
                             r-fields))
    (home-page "https://cran.r-project.org/package=CJIVE")
    (synopsis "Canonical Joint and Individual Variation Explained (CJIVE)")
    (description
     "Joint and Individual Variation Explained (JIVE) is a method for decomposing
multiple datasets obtained on the same subjects into shared structure, structure
unique to each dataset, and noise.  The two most common implementations are
R.JIVE, an iterative approach, and AJIVE, which uses principal angle analysis.
JIVE estimates subspaces but interpreting these subspaces can be challenging
with AJIVE or R.JIVE. We expand upon insights into AJIVE as a canonical
correlation analysis (CCA) of principal component scores.  This reformulation,
which we call CJIVE, 1) provides an ordering of joint components by the degree
of correlation between corresponding canonical variables; 2) uses a
computationally efficient permutation test for the number of joint components,
which provides a p-value for each component; and 3) can be used to predict
subject scores for out-of-sample observations.  Please cite the following
article when utilizing this package: Murden, R., Zhang, Z., Guo, Y., & Risk, B.
(2022) <doi:10.3389/fnins.2022.969510>.")
    (license license:expat)))

(define-public r-cjbart
  (package
    (name "r-cjbart")
    (version "0.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cjbart" version))
       (sha256
        (base32 "1d6jg6m86i2vx1yq66flj22x061s2x8rxsasqnn688kaaqrya657"))))
    (properties `((upstream-name . "cjbart")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rlang
                             r-rdpack
                             r-randomforestsrc
                             r-ggplot2
                             r-bart))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/tsrobinson/cjbart")
    (synopsis "Heterogeneous Effects Analysis of Conjoint Experiments")
    (description
     "This package provides a tool for analyzing conjoint experiments using Bayesian
Additive Regression Trees ('BART'), a machine learning method developed by
Chipman, George and @code{McCulloch} (2010) <doi:10.1214/09-AOAS285>.  This tool
focuses specifically on estimating, identifying, and visualizing the
heterogeneity within marginal component effects, at the observation- and
individual-level.  It uses a variable importance measure ('VIMP') with delete-d
jackknife variance estimation, following Ishwaran and Lu (2019)
<doi:10.1002/sim.7803>, to obtain bias-corrected estimates of which variables
drive heterogeneity in the predicted individual-level effects.")
    (license license:asl2.0)))

(define-public r-cjar
  (package
    (name "r-cjar")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cjar" version))
       (sha256
        (base32 "0rq9ryhp2h3p927227chzwbjn7x22h9ckkha2kclhx0jh7swf5y7"))))
    (properties `((upstream-name . "cjar")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-r6
                             r-purrr
                             r-progress
                             r-openssl
                             r-memoise
                             r-magrittr
                             r-lubridate
                             r-jsonlite
                             r-jose
                             r-httr
                             r-glue
                             r-dplyr
                             r-assertthat))
    (home-page "https://cran.r-project.org/package=cjar")
    (synopsis "R Client for 'Customer Journey Analytics' ('CJA') API")
    (description
     "Connect to the CJA API, which powers CJA Workspace
<https://github.com/@code{AdobeDocs/cja-apis>}.  The package was developed with
the analyst in mind and will continue to be developed with the guiding
principles of iterative, repeatable, timely analysis.  New features are actively
being developed and we value your feedback and contribution to the process.")
    (license license:expat)))

(define-public r-cjamp
  (package
    (name "r-cjamp")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CJAMP" version))
       (sha256
        (base32 "0caznbqy5hsp7h0gkdbv966vfpq8z1khvbizi4vpc9mxck1nqc99"))))
    (properties `((upstream-name . "CJAMP")))
    (build-system r-build-system)
    (propagated-inputs (list r-optimx))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CJAMP")
    (synopsis "Copula-Based Joint Analysis of Multiple Phenotypes")
    (description
     "We provide a computationally efficient and robust implementation of the recently
proposed C-JAMP (Copula-based Joint Analysis of Multiple Phenotypes) method
(Konigorski et al., 2019, submitted).  C-JAMP allows estimating and testing the
association of one or multiple predictors on multiple outcomes in a joint model,
and is implemented here with a focus on large-scale genome-wide association
studies with two phenotypes.  The use of copula functions allows modeling a wide
range of multivariate dependencies between the phenotypes, and previous results
are supporting that C-JAMP can increase the power of association studies to
identify associated genetic variants in comparison to existing methods
(Konigorski, Yilmaz, Pischon, 2016, <DOI:10.1186/s12919-016-0045-6>; Konigorski,
Yilmaz, Bull, 2014, <DOI:10.1186/1753-6561-8-S1-S72>).  In addition to the
C-JAMP functions, functions are available to generate genetic and phenotypic
data, to compute the minor allele frequency (MAF) of genetic markers, and to
estimate the phenotypic variance explained by genetic markers.")
    (license license:gpl2)))

(define-public r-ciw
  (package
    (name "r-ciw")
    (version "0.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ciw" version))
       (sha256
        (base32 "1znn3prdyw3jdamjk3d7b4f0z4bj1i5d08zl8vp9qzdmf46msnh1"))))
    (properties `((upstream-name . "ciw")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml r-data-table r-curl))
    (home-page "https://github.com/eddelbuettel/ciw")
    (synopsis "Watch the CRAN Incoming Directories")
    (description
     "Directory reads and summaries are provided for one or more of the subdirectories
of the <https://cran.r-project.org/incoming/> directory, and a compact summary
object is returned.  The package name is a contraption of CRAN Incoming
Watcher'.")
    (license license:gpl2+)))

(define-public r-civis
  (package
    (name "r-civis")
    (version "3.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "civis" version))
       (sha256
        (base32 "0ahrav9gd0dy05vxapg5x0csadwcnm4nfcwwk752j9nksd1hl3wg"))))
    (properties `((upstream-name . "civis")))
    (build-system r-build-system)
    (propagated-inputs (list r-memoise r-jsonlite r-httr r-future))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/civisanalytics/civis-r")
    (synopsis "R Client for the 'Civis Platform API'")
    (description
     "This package provides a convenient interface for making requests directly to the
Civis Platform API <https://www.civisanalytics.com/platform/>.  Full
documentation available here <https://civisanalytics.github.io/civis-r/>.")
    (license license:bsd-3)))

(define-public r-civ
  (package
    (name "r-civ")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "civ" version))
       (sha256
        (base32 "12k8wqv33p3pvvcg5sr8bvgxgnmsyp6nfpnz00x3y43wax35s7h0"))))
    (properties `((upstream-name . "civ")))
    (build-system r-build-system)
    (propagated-inputs (list r-kcmeans r-aer))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/thomaswiemann/civ")
    (synopsis "Categorical Instrumental Variables")
    (description
     "Implementation of the categorical instrumental variable (CIV) estimator proposed
by Wiemann (2023) <@code{arXiv:2311.17021>}.  CIV allows for optimal
instrumental variable estimation in settings with relatively few observations
per category.  To obtain valid inference in these challenging settings, CIV
leverages a regularization assumption that implies existence of a latent
categorical variable with fixed finite support achieving the same first stage
fit as the observed instrument.")
    (license license:gpl3+)))

(define-public r-ciuupi2
  (package
    (name "r-ciuupi2")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ciuupi2" version))
       (sha256
        (base32 "04x02qmqqyrc4h4z4mpl4zn5vr9y28k6j6n30fbr9q238zd543db"))))
    (properties `((upstream-name . "ciuupi2")))
    (build-system r-build-system)
    (propagated-inputs (list r-statmod r-precisesums r-pracma r-nloptr
                             r-functional))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ciuupi2")
    (synopsis "Kabaila and Giri (2009) Confidence Interval")
    (description
     "Computes a confidence interval for a specified linear combination of the
regression parameters in a linear regression model with iid normal errors with
unknown variance when there is uncertain prior information that a distinct
specified linear combination of the regression parameters takes a specified
number.  This confidence interval, found by numerical nonlinear constrained
optimization, has the required minimum coverage and utilizes this uncertain
prior information through desirable expected length properties.  This confidence
interval is proposed by Kabaila, P. and Giri, K. (2009)
<doi:10.1016/j.jspi.2009.03.018>.")
    (license license:gpl2)))

(define-public r-ciuupi
  (package
    (name "r-ciuupi")
    (version "1.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ciuupi" version))
       (sha256
        (base32 "0nxci8x9v78l4plcd6p1b827xjd40ncda9cqqhawfm059z8j73n8"))))
    (properties `((upstream-name . "ciuupi")))
    (build-system r-build-system)
    (propagated-inputs (list r-statmod r-pracma r-nloptr r-functional))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ciuupi")
    (synopsis "Confidence Intervals Utilizing Uncertain Prior Information")
    (description
     "Computes a confidence interval for a specified linear combination of the
regression parameters in a linear regression model with iid normal errors with
known variance when there is uncertain prior information that a distinct
specified linear combination of the regression parameters takes a given value.
This confidence interval, found by numerical nonlinear constrained optimization,
has the required minimum coverage and utilizes this uncertain prior information
through desirable expected length properties.  This confidence interval has the
following three practical applications.  Firstly, if the error variance has been
accurately estimated from previous data then it may be treated as being
effectively known.  Secondly, for sufficiently large (dimension of the response
vector) minus (dimension of regression parameter vector), greater than or equal
to 30 (say), if we replace the assumed known value of the error variance by its
usual estimator in the formula for the confidence interval then the resulting
interval has, to a very good approximation, the same coverage probability and
expected length properties as when the error variance is known.  Thirdly, some
more complicated models can be approximated by the linear regression model with
error variance known when certain unknown parameters are replaced by estimates.
This confidence interval is described in Mainzer, R. and Kabaila, P. (2019)
<doi:10.32614/RJ-2019-026>, and is a member of the family of confidence
intervals proposed by Kabaila, P. and Giri, K. (2009)
<doi:10.1016/j.jspi.2009.03.018>.")
    (license license:gpl2)))

(define-public r-ciu
  (package
    (name "r-ciu")
    (version "0.6.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ciu" version))
       (sha256
        (base32 "0pqs8ivbybbrjar978bl05awgaks33nqfm7l9z68iv2sj4a9hv21"))))
    (properties `((upstream-name . "ciu")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-ggplot2 r-crayon))
    (home-page "https://cran.r-project.org/package=ciu")
    (synopsis "Contextual Importance and Utility")
    (description
     "Implementation of the Contextual Importance and Utility (CIU) concepts for
Explainable AI (XAI).  A recent description of CIU can be found in e.g.
FrÃ¤mling (2020) <@code{arXiv:2009.13996>}.")
    (license license:expat)))

(define-public r-citrus
  (package
    (name "r-citrus")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "citrus" version))
       (sha256
        (base32 "1pzzyppqfh3qvc1xi2947lnshv7z2c21r8fribhc1avj76j26q5y"))))
    (properties `((upstream-name . "citrus")))
    (build-system r-build-system)
    (propagated-inputs (list r-treeclust
                             r-tibble
                             r-stringr
                             r-rpart-plot
                             r-rpart
                             r-rlang
                             r-rcolorbrewer
                             r-ggplot2
                             r-ggally
                             r-dplyr
                             r-clustmixtype))
    (home-page "https://cran.r-project.org/package=citrus")
    (synopsis
     "Customer Intelligence Tool for Rapid Understandable Segmentation")
    (description
     "This package provides a tool to easily run and visualise supervised and
unsupervised state of the art customer segmentation.  It is built like a
pipeline covering the 3 main steps in a segmentation project: pre-processing,
modelling, and plotting.  Users can either run the pipeline as a whole, or
choose to run any one of the three individual steps.  It is equipped with a
supervised option (tree optimisation) and an unsupervised option (k-clustering)
as default models.")
    (license license:expat)))

(define-public r-citools
  (package
    (name "r-citools")
    (version "0.6.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ciTools" version))
       (sha256
        (base32 "0d6aq4wcxi1q59g4kfx49x1li41rfwx2z2v4xzz2xkldn6h1794z"))))
    (properties `((upstream-name . "ciTools")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-mass
                             r-lme4
                             r-dplyr
                             r-boot
                             r-arm))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://github.com/jthaman/ciTools")
    (synopsis
     "Confidence or Prediction Intervals, Quantiles, and Probabilities for Statistical Models")
    (description
     "This package provides functions to append confidence intervals, prediction
intervals, and other quantities of interest to data frames.  All appended
quantities are for the response variable, after conditioning on the model and
covariates.  This package has a data frame first syntax that allows for easy
piping.  Currently supported models include (log-) linear, (log-) linear mixed,
generalized linear models, generalized linear mixed models, and accelerated
failure time models.")
    (license license:gpl3+)))

(define-public r-cito
  (package
    (name "r-cito")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cito" version))
       (sha256
        (base32 "0ayzwk684a0clq67h6ycifphcrhshdx5kpww9yi0v627pyx3jfv6"))))
    (properties `((upstream-name . "cito")))
    (build-system r-build-system)
    (propagated-inputs (list r-torchvision
                             r-torch
                             r-tibble
                             r-progress
                             r-parabar
                             r-lme4
                             r-gridextra
                             r-coro
                             r-cli
                             r-checkmate
                             r-abind))
    (native-inputs (list r-knitr))
    (home-page "https://citoverse.github.io/cito/")
    (synopsis "Building and Training Neural Networks")
    (description
     "The cito package provides a user-friendly interface for training and
interpreting deep neural networks (DNN).  cito simplifies the fitting of DNNs by
supporting the familiar formula syntax, hyperparameter tuning under
cross-validation, and helps to detect and handle convergence problems.  DNNs can
be trained on CPU, GPU and @code{MacOS} GPUs.  In addition, cito has many
downstream functionalities such as various explainable AI (@code{xAI}) metrics
(e.g. variable importance, partial dependence plots, accumulated local effect
plots, and effect estimates) to interpret trained DNNs.  cito optionally
provides confidence intervals (and p-values) for all @code{xAI} metrics and
predictions.  At the same time, cito is computationally efficient because it is
based on the deep learning framework torch'.  The torch package is native to R,
so no Python installation or other API is required for this package.")
    (license license:gpl3+)))

(define-public r-citmre
  (package
    (name "r-citmre")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "citmre" version))
       (sha256
        (base32 "08n8ldfdnpizk55j9iba65b6dkqxlqmsvfgvmn7cnrzgb4achcxd"))))
    (properties `((upstream-name . "citmre")))
    (build-system r-build-system)
    (propagated-inputs (list r-xts
                             r-xml2
                             r-rvest
                             r-plotly
                             r-lubridate
                             r-jsonlite
                             r-httr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/DavRodEcon/citmre")
    (synopsis "Colombian Index Tool Market Rate Exchange")
    (description
     "Downloads the Representative Market Rate Exchange (RMRE) from the
<www.datos.gov.co> source.  Allows setting the data series in time frequencies,
splitting the time series through start and end functions, transforming the data
set in log returns or levels, and making a Dynamic graph.")
    (license license:expat)))

(define-public r-citmic
  (package
    (name "r-citmic")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CITMIC" version))
       (sha256
        (base32 "0zq2gkayspb6bffrpjnhwb4njkm6iz3yg740njabdlszr53l3ayd"))))
    (properties `((upstream-name . "CITMIC")))
    (build-system r-build-system)
    (propagated-inputs (list r-igraph r-fastmatch))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CITMIC")
    (synopsis "Estimation of Cell Infiltration Based on Cell Crosstalk")
    (description
     "This package provides a systematic biology tool was developed to identify cell
infiltration via an Individualized Cell crosstalk network.  CITMIC first
constructed a weighted cell crosstalk network by integrating Cell-target
interaction information, biological process data from the Gene Ontology (GO)
database, and gene transcriptomic data in a specific sample, and then, it used a
network propagation algorithm on the network to identify cell infiltration for
the sample.  Ultimately, cell infiltration in the patient dataset was obtained
by normalizing the centrality scores of the cells.")
    (license license:gpl2+)))

(define-public r-cities
  (package
    (name "r-cities")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cities" version))
       (sha256
        (base32 "1047y1n8mldbnq8g7p43bcvsxz2hbcidbwvafcj1h01rsfgbfkd1"))))
    (properties `((upstream-name . "cities")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-plotly r-ggthemes r-ggplot2 r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://hakeemwahabapp.shinyapps.io/cities/")
    (synopsis "Clinical Trials with Intercurrent Events Simulator")
    (description
     "Simulates clinical trials and summarizes causal effects and treatment policy
estimands in the presence of intercurrent events in a transparent and intuitive
manner.")
    (license license:gpl3+)))

(define-public r-citecorp
  (package
    (name "r-citecorp")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "citecorp" version))
       (sha256
        (base32 "0lqxa6qfysrk3rpg9fnsxhrfsd0qsbfxhc3b43090fhlxq9gk3wm"))))
    (properties `((upstream-name . "citecorp")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-fauxpas r-data-table r-crul))
    (home-page "https://github.com/ropenscilabs/citecorp")
    (synopsis "Client for the Open Citations Corpus")
    (description
     "Client for the Open Citations Corpus (<http://opencitations.net/>).  Includes a
set of functions for getting one identifier type from another, as well as
getting references and citations for a given identifier.")
    (license license:expat)))

(define-public r-citationchaser
  (package
    (name "r-citationchaser")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "citationchaser" version))
       (sha256
        (base32 "11ilh8fpqvljzriwwkzmw5idxff82spyv4b36lsl1s0lfbgjis69"))))
    (properties `((upstream-name . "citationchaser")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-scales
                             r-networkd3
                             r-mess
                             r-maditr
                             r-jsonlite
                             r-httr
                             r-dplyr
                             r-data-table))
    (home-page "https://cran.r-project.org/package=citationchaser")
    (synopsis "Perform Forward and Backwards Chasing in Evidence Syntheses")
    (description
     "In searching for research articles, we often want to obtain lists of references
from across studies, and also obtain lists of articles that cite a particular
study.  In systematic reviews, this supplementary search technique is known as
citation chasing': forward citation chasing looks for all records citing one or
more articles of known relevance; backward citation chasing looks for all
records referenced in one or more articles.  Traditionally, this process would
be done manually, and the resulting records would need to be checked one-by-one
against included studies in a review to identify potentially relevant records
that should be included in a review.  This package contains functions to
automate this process by making use of the Lens.org API. An input article list
can be used to return a list of all referenced records, and/or all citing
records in the Lens.org database (consisting of @code{PubMed}, @code{PubMed}
Central, @code{CrossRef}, Microsoft Academic Graph and CORE;
<https://www.lens.org>).")
    (license license:gpl3+)))

(define-public r-citation
  (package
    (name "r-citation")
    (version "0.8.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "citation" version))
       (sha256
        (base32 "0s6hsxfa72apslp4prfl2b9n1ybvsynlh69772rh9x0niysgm43g"))))
    (properties `((upstream-name . "citation")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml r-withr r-jsonlite r-desc))
    (home-page "https://github.com/pik-piam/citation")
    (synopsis "Software Citation Tools")
    (description
     "This package provides a collection of functions to extract citation information
from R packages and to deal with files in citation file format
(<https://citation-file-format.github.io/>), extending the functionality already
provided by the citation() function in the utils package.")
    (license license:bsd-2)))

(define-public r-citan
  (package
    (name "r-citan")
    (version "2022.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CITAN" version))
       (sha256
        (base32 "09m9f6s9y7ygbixcymg93vsrqz5jsjp968cjhxnj1v73hzalk168"))))
    (properties `((upstream-name . "CITAN")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi r-rsqlite r-dbi r-agop))
    (home-page "https://github.com/gagolews/CITAN")
    (synopsis "CITation ANalysis Toolpack")
    (description
     "Supports quantitative research in scientometrics and bibliometrics.  Provides
various tools for preprocessing bibliographic data retrieved, e.g., from
Elsevier's @code{SciVerse} Scopus, computing bibliometric impact of individuals,
or modelling phenomena encountered in the social sciences.  This package is
deprecated, see agop instead.")
    (license license:lgpl3+)))

(define-public r-cit
  (package
    (name "r-cit")
    (version "2.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cit" version))
       (sha256
        (base32 "0dipl9d96f59zdc5bpw5xpls78mm614ljz95k898q35qzsz8g5lf"))))
    (properties `((upstream-name . "cit")))
    (build-system r-build-system)
    (inputs (list gsl gsl))
    (home-page "https://github.com/USCbiostats/cit")
    (synopsis "Causal Inference Test")
    (description
     "This package provides a likelihood-based hypothesis testing approach is
implemented for assessing causal mediation.  Described in Millstein, Chen, and
Breton (2016), <DOI:10.1093/bioinformatics/btw135>, it could be used to test for
mediation of a known causal association between a DNA variant, the instrumental
variable', and a clinical outcome or phenotype by gene expression or DNA
methylation, the potential mediator.  Another example would be testing mediation
of the effect of a drug on a clinical outcome by the molecular target.  The
hypothesis test generates a p-value or permutation-based FDR value with
confidence intervals to quantify uncertainty in the causal inference.  The
outcome can be represented by either a continuous or binary variable, the
potential mediator is continuous, and the instrumental variable can be
continuous or binary and is not limited to a single variable but may be a design
matrix representing multiple variables.")
    (license license:artistic2.0)))

(define-public r-cis-dglm
  (package
    (name "r-cis-dglm")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CIS.DGLM" version))
       (sha256
        (base32 "0c7jxfb8gaklf6p83152wb2nszm2p806p3n523xajf4ha368d3kq"))))
    (properties `((upstream-name . "CIS.DGLM")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer r-ggplot2 r-dplyr r-dglm))
    (home-page "https://cran.r-project.org/package=CIS.DGLM")
    (synopsis "Covariates, Interaction, and Selection for DGLM")
    (description
     "An implementation of double generalized linear model (DGLM) building with
variable selection procedures and handling of interaction terms and other
complex situations.  We also provide a method of handling convergence issues
within the dglm() function.  The package offers a simulation function for
generating simulated data for testing purposes and utilizes the forward stepwise
variable selection procedure in model-building.  It also provides a new custom
bootstrap function for mean and standard deviation estimation and functions for
building crossplots and squareplots from a data set.")
    (license license:gpl2+)))

(define-public r-cirt
  (package
    (name "r-cirt")
    (version "1.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cIRT" version))
       (sha256
        (base32 "1iwgxc1jl118j9yjhjix9f7dm75sj82iz7ic58g5625fxzdgnw25"))))
    (properties `((upstream-name . "cIRT")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://tmsalab.github.io/cIRT/")
    (synopsis "Choice Item Response Theory")
    (description
     "Jointly model the accuracy of cognitive responses and item choices within a
Bayesian hierarchical framework as described by Culpepper and Balamuta (2015)
<doi:10.1007/s11336-015-9484-7>.  In addition, the package contains the datasets
used within the analysis of the paper.")
    (license license:gpl2+)))

(define-public r-cirls
  (package
    (name "r-cirls")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cirls" version))
       (sha256
        (base32 "0aw5cvn7841ayr2sb4qafjz2jy03i9k8nvpcls3zivjymynn2cx4"))))
    (properties `((upstream-name . "cirls")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncatednormal r-quadprog r-osqp r-coneproj))
    (home-page "https://github.com/PierreMasselot/cirls")
    (synopsis "Constrained Iteratively Reweighted Least Squares")
    (description
     "Routines to fit generalized linear models with constrained coefficients, along
with inference on the coefficients.  Designed to be used in conjunction with the
base glm() function.")
    (license license:gpl3+)))

(define-public r-circumplex
  (package
    (name "r-circumplex")
    (version "0.3.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "circumplex" version))
       (sha256
        (base32 "1g0r004c7y51mcv7iiymgzhdy9v8y9bk814bzaam4d8fxp7qzqlr"))))
    (properties `((upstream-name . "circumplex")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-scales
                             r-rlang
                             r-rcpparmadillo
                             r-rcpp
                             r-purrr
                             r-magrittr
                             r-htmltable
                             r-ggplot2
                             r-ggforce
                             r-dplyr
                             r-boot
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jmgirard/circumplex")
    (synopsis "Analysis and Visualization of Circular Data")
    (description
     "Circumplex models, which organize constructs in a circle around two underlying
dimensions, are popular for studying interpersonal functioning, mood/affect, and
vocational preferences/environments.  This package provides tools for analyzing
and visualizing circular data, including scoring functions for relevant
instruments and a generalization of the bootstrapped structural summary method
from Zimmermann & Wright (2017) <doi:10.1177/1073191115621795> and functions for
creating publication-ready tables and figures from the results.")
    (license license:gpl3)))

(define-public r-circularsilhouette
  (package
    (name "r-circularsilhouette")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CircularSilhouette" version))
       (sha256
        (base32 "03214kqpnfjr9swafy1yjwr2jjj3iafb6ikn2sd45k2cx4xvprr3"))))
    (properties `((upstream-name . "CircularSilhouette")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-rcpp r-optcirclust))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CircularSilhouette")
    (synopsis "Fast Silhouette on Circular or Linear Data Clusters")
    (description
     "Calculating silhouette information for clusters on circular or linear data using
fast algorithms.  These algorithms run in linear time on sorted data, in
contrast to quadratic time by the definition of silhouette.  When used together
with the fast and optimal circular clustering method FOCC (Debnath & Song 2021)
<doi:10.1109/TCBB.2021.3077573> implemented in R package @code{OptCirClust}',
circular silhouette can be maximized to find the optimal number of circular
clusters; it can also be used to estimate the period of noisy periodical data.")
    (license license:lgpl3+)))

(define-public r-circularev
  (package
    (name "r-circularev")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "circularEV" version))
       (sha256
        (base32 "0g499mn8knkfspk3wdgn8r9v4hpr6gy8wjwf0zrgf0j05xap6g7a"))))
    (properties `((upstream-name . "circularEV")))
    (build-system r-build-system)
    (propagated-inputs (list r-npcirc
                             r-mgcv
                             r-ggplot2
                             r-foreach
                             r-doparallel
                             r-circular))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=circularEV")
    (synopsis "Extreme Value Analysis for Circular Data")
    (description
     "General functions for performing extreme value analysis on a circular domain as
part of the statistical methodology in the paper by Konzen, E., Neves, C., and
Jonathan, P. (2021).  Modeling nonstationary extremes of storm severity:
Comparing parametric and semiparametric inference.  Environmetrics, 32(4),
e2667.")
    (license license:gpl3)))

(define-public r-circularddm
  (package
    (name "r-circularddm")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CircularDDM" version))
       (sha256
        (base32 "1wxdjj7dndvhvl00cykcrwmw9f7halsg3a0db56kp2mhf54rj37z"))))
    (properties `((upstream-name . "CircularDDM")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "https://cran.r-project.org/package=CircularDDM")
    (synopsis "Circular Drift-Diffusion Model")
    (description "Circular drift-diffusion model for continuous reports.")
    (license license:gpl2)))

(define-public r-circstats
  (package
    (name "r-circstats")
    (version "0.2-6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CircStats" version))
       (sha256
        (base32 "07bg4zrs2iqh0pmi44pybi8hlvnxwcaa5zpg85rmf55kflxxkzlf"))))
    (properties `((upstream-name . "CircStats")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-boot))
    (home-page "https://cran.r-project.org/package=CircStats")
    (synopsis
     "Circular Statistics, from \"Topics in Circular Statistics\" (2001)")
    (description
     "Circular Statistics, from \"Topics in Circular Statistics\" (2001) S. Rao
Jammalamadaka and A. @code{SenGupta}, World Scientific.")
    (license license:gpl2)))

(define-public r-circspacetime
  (package
    (name "r-circspacetime")
    (version "0.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CircSpaceTime" version))
       (sha256
        (base32 "0dplgm5x4c1xxnv6062n643mn5zh0najw3f41pv2qafc1lil4wx8"))))
    (properties `((upstream-name . "CircSpaceTime")))
    (build-system r-build-system)
    (propagated-inputs (list r-rinside
                             r-rcpparmadillo
                             r-rcpp
                             r-ggplot2
                             r-coda
                             r-circular))
    (home-page "https://github.com/santoroma/CircSpaceTime")
    (synopsis "Spatial and Spatio-Temporal Bayesian Model for Circular Data")
    (description
     "Implementation of Bayesian models for spatial and spatio-temporal interpolation
of circular data using Gaussian Wrapped and Gaussian Projected distributions.
We developed the methods described in Jona Lasinio G. et al. (2012) <doi:
10.1214/12-aoas576>, Wang F. et al. (2014) <doi: 10.1080/01621459.2014.934454>
and Mastrantonio G. et al. (2016) <doi: 10.1007/s11749-015-0458-y>.")
    (license license:gpl3)))

(define-public r-circoutlier
  (package
    (name "r-circoutlier")
    (version "3.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CircOutlier" version))
       (sha256
        (base32 "1vyac4mjkn6p4p9n5finqqak6g7m3hj04a66v3w797jn1wbd1xly"))))
    (properties `((upstream-name . "CircOutlier")))
    (build-system r-build-system)
    (propagated-inputs (list r-circular r-circstats))
    (home-page "https://cran.r-project.org/package=CircOutlier")
    (synopsis "Detection of Outliers in Circular-Circular Regression")
    (description
     "Detection of outliers in circular-circular regression models, modifying its and
estimating of models parameters.")
    (license license:gpl2+)))

(define-public r-circnntsrmult
  (package
    (name "r-circnntsrmult")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CircNNTSRmult" version))
       (sha256
        (base32 "1x5q8v33k67km0lclfs6dy408grq8yfvld7zx9y8zxm5qq3a576b"))))
    (properties `((upstream-name . "CircNNTSRmult")))
    (build-system r-build-system)
    (propagated-inputs (list r-psychtools r-circnntsr))
    (home-page "https://cran.r-project.org/package=CircNNTSRmult")
    (synopsis "Multivariate Circular Data using MNNTS Models")
    (description
     "This package provides a collection of utilities for the statistical analysis of
multivariate circular data using distributions based on Multivariate Nonnegative
Trigonometric Sums (MNNTS).  The package includes functions for calculation of
densities and distributions, for the estimation of parameters, and more.")
    (license license:gpl2+)))

(define-public r-circnntsr
  (package
    (name "r-circnntsr")
    (version "2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CircNNTSR" version))
       (sha256
        (base32 "0in6rwsqlmyza7gjh0q9vvbbiir0px90wnmnhlmzmm85iaxarmq6"))))
    (properties `((upstream-name . "CircNNTSR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CircNNTSR")
    (synopsis
     "Statistical Analysis of Circular Data using Nonnegative Trigonometric Sums (NNTS) Models")
    (description
     "Includes functions for the analysis of circular data using distributions based
on Nonnegative Trigonometric Sums (NNTS).  The package includes functions for
calculation of densities and distributions, for the estimation of parameters,
for plotting and more.")
    (license license:gpl2+)))

(define-public r-circmle
  (package
    (name "r-circmle")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CircMLE" version))
       (sha256
        (base32 "1nr6qicy5y247j970jw74pkbyhx4zjgajf2ygkxmdw6gfx5byn64"))))
    (properties `((upstream-name . "CircMLE")))
    (build-system r-build-system)
    (propagated-inputs (list r-energy r-circular))
    (home-page "https://www.r-project.org")
    (synopsis "Maximum Likelihood Analysis of Circular Data")
    (description
     "This package provides a series of wrapper functions to implement the 10 maximum
likelihood models of animal orientation described by Schnute and Groot (1992)
<DOI:10.1016/S0003-3472(05)80068-5>.  The functions also include the ability to
use different optimizer methods and calculate various model selection metrics
(i.e., AIC, AICc, BIC).  The ability to perform variants of the Hermans-Rasson
test and Pycke test is also included as described in Landler et al. (2019)
<DOI:10.1186/s12898-019-0246-8>.  The latest version also includes a new method
to calculate circular-circular and circular-linear distance correlations.")
    (license license:gpl2+)))

(define-public r-circlus
  (package
    (name "r-circlus")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "circlus" version))
       (sha256
        (base32 "0jwmsqm08crbmbbpbj0dn2vm33z1zsr18420cl09kjyz4yixwzb0"))))
    (properties `((upstream-name . "circlus")))
    (build-system r-build-system)
    (propagated-inputs (list r-torch r-tinflex r-rcpparmadillo r-rcpp
                             r-flexmix))
    (home-page "https://cran.r-project.org/package=circlus")
    (synopsis "Clustering and Simulation of Spherical Cauchy and PKBD Models")
    (description
     "This package provides tools for estimation and clustering of spherical data,
seamlessly integrated with the flexmix package.  Includes the necessary M-step
implementations for both Poisson Kernel-Based Distribution (PKBD) and spherical
Cauchy distribution.  Additionally, the package provides random number
generators for PKBD and spherical Cauchy distribution.  Methods are based on
Golzy M., Markatou M. (2020) <doi:10.1080/10618600.2020.1740713>, Kato S.,
@code{McCullagh} P. (2020) <doi:10.3150/20-bej1222> and Sablica L., Hornik K.,
Leydold J. (2023) <doi:10.1214/23-ejs2149>.")
    (license license:gpl3)))

(define-public r-circletyper
  (package
    (name "r-circletyper")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "circletyper" version))
       (sha256
        (base32 "0j2c369icz864fjgd393wbvv1shmrwgvcqfzwps778lzv59f869h"))))
    (properties `((upstream-name . "circletyper")))
    (build-system r-build-system)
    (arguments
     (list
      #:modules '((guix build r-build-system)
                  (guix build minify-build-system)
                  (guix build utils)
                  (ice-9 match))
      #:imported-modules `(,@%r-build-system-modules (guix build
                                                      minify-build-system))
      #:phases '(modify-phases %standard-phases
                  (add-after 'unpack 'process-javascript
                    (lambda* (#:key inputs #:allow-other-keys)
                      (with-directory-excursion "inst/"
                        (for-each (match-lambda
                                    ((source . target) (minify source
                                                               #:target target)))
                                  '())))))))
    (propagated-inputs (list r-shiny))
    (native-inputs (list esbuild))
    (home-page "https://github.com/etiennebacher/circletyper")
    (synopsis "Curve Text Elements in 'Shiny' Using 'CircleType.js'")
    (description "Enables curving text elements in Shiny apps.")
    (license license:expat)))

(define-public r-circlesplot
  (package
    (name "r-circlesplot")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "circlesplot" version))
       (sha256
        (base32 "0ghryi31g0ah24h6qznxx082n2g4hs70aplfzzil5fkwpsk5wx0b"))))
    (properties `((upstream-name . "circlesplot")))
    (build-system r-build-system)
    (propagated-inputs (list r-plotrix))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/BenSt099/circlesplot")
    (synopsis "Visualize Proportions with Circles in a Plot")
    (description
     "Method for visualizing proportions between objects of different sizes.  The
proportions are drawn as circles with different diameters, which makes them
ideal for visualizing proportions between planets.")
    (license license:expat)))

(define-public r-circlesintersections
  (package
    (name "r-circlesintersections")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CirclesIntersections" version))
       (sha256
        (base32 "0q7w3fl8qz5gknri217qq68wij355dljnpv538yqhf03h405xc3f"))))
    (properties `((upstream-name . "CirclesIntersections")))
    (build-system r-build-system)
    (home-page "https://github.com/hugosal/CirclesIntersections")
    (synopsis
     "Algorithm for Computation of the Intersection Areas of N Circles")
    (description
     "Implementation of Librino, Levorato, and Zorzi (2014) <doi:10.1002/wcm.2305>
algorithm for computation of the intersection areas of an arbitrary number of
circles.")
    (license license:expat)))

(define-public r-circle
  (package
    (name "r-circle")
    (version "0.7.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "circle" version))
       (sha256
        (base32 "1179gh3psicj5pcaqdhn4cfvj9dwwflwk0jz3lwd9yvgmbhcp2zs"))))
    (properties `((upstream-name . "circle")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr r-gh r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/circle/")
    (synopsis "R Client Package for Circle CI")
    (description
     "This package provides tools for interacting with the Circle CI API
(<https://circleci.com/docs/api/v2/>).  Besides executing common tasks such as
querying build logs and restarting builds, this package also helps setting up
permissions to deploy from builds.")
    (license license:gpl3)))

(define-public r-circhelp
  (package
    (name "r-circhelp")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "circhelp" version))
       (sha256
        (base32 "1w8m4dawq6hd9pjgmqydhf4c3f7gllzlwmxmbxirg61psk38x4wk"))))
    (properties `((upstream-name . "circhelp")))
    (build-system r-build-system)
    (propagated-inputs (list r-patchwork
                             r-mathjaxr
                             r-mass
                             r-ggplot2
                             r-gamlss
                             r-data-table))
    (native-inputs (list r-ragg
                         r-patchwork
                         r-mgcv
                         r-mass
                         r-knitr
                         r-ggplot2
                         r-gamlss))
    (home-page "https://achetverikov.github.io/circhelp/index.html")
    (synopsis "Circular Analyses Helper Functions")
    (description
     "Light-weight functions for computing descriptive statistics in different
circular spaces (e.g., 2pi, 180, or 360 degrees), to handle angle-dependent
biases, pad circular data, and more.  Specifically aimed for psychologists and
neuroscientists analyzing circular data.  Basic methods are based on
Jammalamadaka and @code{SenGupta} (2001) <doi:10.1142/4031>, removal of cardinal
biases is based on the approach introduced in van Bergen, Ma, Pratte, & Jehee
(2015) <doi:10.1038/nn.4150> and Chetverikov and Jehee (2023)
<doi:10.1038/s41467-023-43251-w>.")
    (license license:cc0)))

(define-public r-circer
  (package
    (name "r-circer")
    (version "1.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CirceR" version))
       (sha256
        (base32 "19pkj9qg6sfyxqvlwssfyr91024arbg74pl332g19917538n346q"))))
    (properties `((upstream-name . "CirceR")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (propagated-inputs (list r-rjsonio r-rjava))
    (home-page "https://ohdsi.github.io/CirceR/")
    (synopsis
     "Construct Cohort Inclusion and Restriction Criteria Expressions")
    (description
     "Wraps the CIRCE (<https://github.com/ohdsi/circe-be>) Java library allowing
cohort definition expressions to be edited and converted to Markdown or SQL'.")
    (license license:asl2.0)))

(define-public r-circacompare
  (package
    (name "r-circacompare")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "circacompare" version))
       (sha256
        (base32 "1j4zaivkxkd3kv7cgy17xwn4mrwx7mhhxf48ziz4bk5z0zykrb5w"))))
    (properties `((upstream-name . "circacompare")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://rwparsons.github.io/circacompare/")
    (synopsis "Analyses of Circadian Data")
    (description
     "Uses non-linear regression to statistically compare two circadian rhythms.
Groups are only compared if both are rhythmic (amplitude is non-zero).  Performs
analyses regarding mesor, phase, and amplitude, reporting on estimates and
statistical differences, for each, between groups.  Details can be found in
Parsons et al (2020) <doi:10.1093/bioinformatics/btz730>.")
    (license license:expat)))

(define-public r-cir
  (package
    (name "r-cir")
    (version "2.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cir" version))
       (sha256
        (base32 "0bgza663rynx2b2p00phfz806cwf2m30yjkqzk2s23hbc47hx9qs"))))
    (properties `((upstream-name . "cir")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cir")
    (synopsis "Centered Isotonic Regression and Dose-Response Utilities")
    (description
     "Isotonic regression (IR) and its improvement: centered isotonic regression
(CIR).  CIR is recommended in particular with small samples.  Also, interval
estimates for both, and additional utilities such as plotting dose-response
data.  For dev version and change history, see @code{GitHub} assaforon/cir.")
    (license license:gpl2)))

(define-public r-cipostselect
  (package
    (name "r-cipostselect")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CIpostSelect" version))
       (sha256
        (base32 "1yqdwb11bi4a7kg3xvh3liq0f77fyfri5sv7ksq71wwshzzr4f8q"))))
    (properties `((upstream-name . "CIpostSelect")))
    (build-system r-build-system)
    (propagated-inputs (list r-tictoc
                             r-mlbench
                             r-mass
                             r-magrittr
                             r-glmnet
                             r-ggplot2
                             r-foreach
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=CIpostSelect")
    (synopsis "Confidence Interval Post-Selection of Variable")
    (description
     "Calculates confidence intervals after variable selection using repeated data
splits.  The package offers methods to address the challenges of post-selection
inference, ensuring more accurate confidence intervals in models involving
variable selection.  The two main functions are lmps', which records the
different models selected across multiple data splits as well as the
corresponding coefficient estimates, and cips', which takes the lmps object as
input to select variables and perform inferences using two types of voting.")
    (license license:expat)))

(define-public r-ciplot
  (package
    (name "r-ciplot")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CIplot" version))
       (sha256
        (base32 "0hx3dn7d8hvsh75747d9046iqriy3bjnchph8xllnvlhkrm4di1f"))))
    (properties `((upstream-name . "CIplot")))
    (build-system r-build-system)
    (propagated-inputs (list r-multcomp r-mass))
    (home-page "https://github.com/toshi-ara/CIplot")
    (synopsis "Functions to Plot Confidence Interval")
    (description
     "Plot confidence interval from the objects of statistical tests such as t.test(),
var.test(), cor.test(), prop.test() and fisher.test() ('htest class), Tukey test
[@code{TukeyHSD}()], Dunnett test [glht() in multcomp package], logistic
regression [glm()], and Tukey or Games-Howell test [@code{posthocTGH}() in
userfriendlyscience package].  Users are able to set the styles of lines and
points.  This package contains the function to calculate odds ratios and their
confidence intervals from the result of logistic regression.")
    (license license:gpl2+)))

(define-public r-cipher
  (package
    (name "r-cipher")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cipheR" version))
       (sha256
        (base32 "01h8mh2xlz1kkwm3nbiw8lpjlkjc19x5x8dq1yxfwdkq5yjjkyaa"))))
    (properties `((upstream-name . "cipheR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cipheR")
    (synopsis "Encryption and Decryption with Text Ciphers")
    (description
     "Encrypts and decrypts using basic ciphers.  None of these should be used in
place of real encryption using state of the art tools.  The ciphers included use
methods described in the ciphers's Wikipedia and cryptography hobby websites.")
    (license license:gpl3+)))

(define-public r-ciperm
  (package
    (name "r-ciperm")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CIPerm" version))
       (sha256
        (base32 "1arb9jswnjmw8fgabwn3ap5wi57rwgh6dnq9c19v1qbcx8lhzs7c"))))
    (properties `((upstream-name . "CIPerm")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrixstats))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ColbyStatSvyRsch/CIPerm/")
    (synopsis
     "Computationally-Efficient Confidence Intervals for Mean Shift from Permutation Methods")
    (description
     "This package implements computationally-efficient construction of confidence
intervals from permutation or randomization tests for simple differences in
means, based on Nguyen (2009) <doi:10.15760/etd.7798>.")
    (license license:expat)))

(define-public r-cinterpolate
  (package
    (name "r-cinterpolate")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cinterpolate" version))
       (sha256
        (base32 "06l82lvwn706jx5c7wx629y5hihqivjvypjrkmwbpypi6adq24qj"))))
    (properties `((upstream-name . "cinterpolate")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mrc-ide/cinterpolate")
    (synopsis "Interpolation From C")
    (description
     "Simple interpolation methods designed to be used from C code.  Supports
constant, linear and spline interpolation.  An R wrapper is included but this
package is primarily designed to be used from C code using @code{LinkingTo}'.
The spline calculations are classical cubic interpolation, e.g., Forsythe,
Malcolm and Moler (1977) <ISBN: 9780131653320>.")
    (license license:expat)))

(define-public r-cinna
  (package
    (name "r-cinna")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CINNA" version))
       (sha256
        (base32 "18dyv8llqjjc679l815ahhsq552n5vkcfj9vkv47y9v3zx1g52yl"))))
    (properties `((upstream-name . "CINNA")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis
                             r-sna
                             r-rtsne
                             r-plyr
                             r-pheatmap
                             r-network
                             r-intergraph
                             r-igraph
                             r-ggplot2
                             r-ggally
                             r-factominer
                             r-factoextra
                             r-dendextend
                             r-corrplot
                             r-circlize
                             r-centiserve))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CINNA")
    (synopsis "Deciphering Central Informative Nodes in Network Analysis")
    (description
     "Computing, comparing, and demonstrating top informative centrality measures
within a network. \"CINNA: an R/CRAN package to decipher Central Informative
Nodes in Network Analysis\" provides a comprehensive overview of the package
functionality Ashtiani et al. (2018) <doi:10.1093/bioinformatics/bty819>.")
    (license license:gpl3)))

(define-public r-cinmetrics
  (package
    (name "r-cinmetrics")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CINmetrics" version))
       (sha256
        (base32 "1csh22b7ap7isnrjak7yp32hasxq8x4j094i9shrnzsz6sxcmc28"))))
    (properties `((upstream-name . "CINmetrics")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CINmetrics")
    (synopsis "Calculate Chromosomal Instability Metrics")
    (description
     "Implement various chromosomal instability metrics.  CINmetrics (Chromosomal
INstability metrics) provides functions to calculate various chromosomal
instability metrics on masked Copy Number Variation(CNV) data at individual
sample level.  The chromosomal instability metrics have been implemented as
described in the following studies: Baumbusch LO et al.  2013
<doi:10.1371/journal.pone.0054356>, Davidson JM et al.  2014
<doi:10.1371/journal.pone.0079079>, Chin SF et al.  2007
<doi:10.1186/gb-2007-8-10-r215>.")
    (license license:gpl3)))

(define-public r-cinid
  (package
    (name "r-cinid")
    (version "1.3-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CINID" version))
       (sha256
        (base32 "06n5bwjr44rx0m12xradzaca26rvh01mlimbn0gr3jfzkmyj2f1g"))))
    (properties `((upstream-name . "CINID")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CINID")
    (synopsis "Curculionidae INstar IDentification")
    (description
     "Method for identifying the instar of Curculionid larvae from the observed
distribution of the headcapsule size of mature larvae.")
    (license license:gpl2+)))

(define-public r-cine
  (package
    (name "r-cine")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CINE" version))
       (sha256
        (base32 "0y5xadsvmciv9cqx6sa8qs1ss7zm55l3304gzdaadmqbsnsq75j8"))))
    (properties `((upstream-name . "CINE")))
    (build-system r-build-system)
    (propagated-inputs (list r-tm r-tidytext r-tidyr r-dplyr))
    (home-page "https://github.com/musajajorge/CINE")
    (synopsis "Classification International Normalized of Education")
    (description
     "Function using lemmatization to classify educational programs according to the
CINE(Classification International Normalized of Education) for Peru.")
    (license license:gpl3)))

(define-public r-cinargenesets
  (package
    (name "r-cinargenesets")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cinaRgenesets" version))
       (sha256
        (base32 "0pz3iw559d8rsxmnwd1cqcpv8qnnh9bfvc9ydzwznx8jczbldls8"))))
    (properties `((upstream-name . "cinaRgenesets")))
    (build-system r-build-system)
    (home-page "https://github.com/eonurk/cinaR-genesets")
    (synopsis "Ready-to-Use Curated Gene Sets for 'cinaR'")
    (description
     "Immune related gene sets provided along with the @code{cinaR} package.")
    (license license:gpl3)))

(define-public r-cinar
  (package
    (name "r-cinar")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cinaR" version))
       (sha256
        (base32 "0kdf3xbhg7yhpr67fqbbwqm16fvv3dj9f7bvfqliy3xhpxpg23qi"))))
    (properties `((upstream-name . "cinaR")))
    (build-system r-build-system)
    (propagated-inputs (list r-writexl
                             r-txdb-mmusculus-ucsc-mm10-knowngene
                             r-txdb-hsapiens-ucsc-hg38-knowngene
                             r-txdb-hsapiens-ucsc-hg19-knowngene
                             r-sva
                             r-rcolorbrewer
                             r-preprocesscore
                             r-pheatmap
                             r-limma
                             r-ggrepel
                             r-ggplot2
                             r-genomicranges
                             r-fgsea
                             r-edger
                             r-dplyr
                             r-deseq2
                             r-chipseeker))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/eonurk/cinaR/")
    (synopsis "Computational Pipeline for Bulk 'ATAC-Seq' Profiles")
    (description
     "Differential analyses and Enrichment pipeline for bulk ATAC-seq data analyses.
This package combines different packages to have an ultimate package for both
data analyses and visualization of ATAC-seq data.  Methods are described in
Karakaslar et al. (2021) <doi:10.1101/2021.03.05.434143>.")
    (license license:gpl3)))

(define-public r-cimtx
  (package
    (name "r-cimtx")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CIMTx" version))
       (sha256
        (base32 "1jx99vh620zqwp7p4bjcxa3n0kg6w6q88kklv9f9x44894mrd56a"))))
    (properties `((upstream-name . "CIMTx")))
    (build-system r-build-system)
    (propagated-inputs (list r-weightit
                             r-twang
                             r-tmle
                             r-tidyr
                             r-superlearner
                             r-stringr
                             r-nnet
                             r-mgcv
                             r-metr
                             r-matching
                             r-magrittr
                             r-ggplot2
                             r-foreach
                             r-dplyr
                             r-doparallel
                             r-cowplot
                             r-bart
                             r-arm))
    (home-page "https://cran.r-project.org/package=CIMTx")
    (synopsis "Causal Inference for Multiple Treatments with a Binary Outcome")
    (description
     "Different methods to conduct causal inference for multiple treatments with a
binary outcome, including regression adjustment, vector matching, Bayesian
additive regression trees, targeted maximum likelihood and inverse probability
of treatment weighting using different generalized propensity score models such
as multinomial logistic regression, generalized boosted models and super
learner.  For more details, see the paper by Hu et al.
<doi:10.1177/0962280220921909>.")
    (license license:expat)))

(define-public r-cimir
  (package
    (name "r-cimir")
    (version "0.4-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cimir" version))
       (sha256
        (base32 "0r8fmvqcihxsj0w1g2xm02wwqcgrwadbl5n1dzksw8zpcjfw7fkn"))))
    (properties `((upstream-name . "cimir")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-rlang
                             r-purrr
                             r-jsonlite
                             r-glue
                             r-dplyr
                             r-curl))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mkoohafkan/cimir")
    (synopsis "Interface to the CIMIS Web API")
    (description
     "Connect to the California Irrigation Management Information System (CIMIS) Web
API. See the CIMIS main page <https://cimis.water.ca.gov> and web API
documentation <https://et.water.ca.gov> for more information.")
    (license license:gpl3+)))

(define-public r-cim
  (package
    (name "r-cim")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CIM" version))
       (sha256
        (base32 "02l8rspiiv6vj6k0q6wpiazny3f2s4dsivsm7zb9cm90qh1rv2d7"))))
    (properties `((upstream-name . "CIM")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CIM")
    (synopsis "Compositional Impact of Migration")
    (description
     "This package produces statistical indicators of the impact of migration on the
socio-demographic composition of an area.  Three measures can be used: ratios,
percentages and the Duncan index of dissimilarity.  The input data files are
assumed to be in an origin-destination matrix format, with each cell
representing a flow count between an origin and a destination area.  Columns are
expected to represent origins, and rows are expected to represent destinations.
The first row and column are assumed to contain labels for each area.  See
Rodriguez-Vignoli and Rowe (2018) <doi:10.1080/00324728.2017.1416155> for
technical details.")
    (license license:gpl2)))

(define-public r-ciftitools
  (package
    (name "r-ciftitools")
    (version "0.16.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ciftiTools" version))
       (sha256
        (base32 "07d7iws9d8r9ir37q8h1k2yl13sy4p9xnnlqlxhlyyfsz7pb23l3"))))
    (properties `((upstream-name . "ciftiTools")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-viridislite
                             r-rnifti
                             r-rgl
                             r-rcolorbrewer
                             r-oro-nifti
                             r-gifti
                             r-fields))
    (home-page "https://github.com/mandymejia/ciftiTools")
    (synopsis
     "Tools for Reading, Writing, Viewing and Manipulating CIFTI Files")
    (description
     "CIFTI files contain brain imaging data in \"grayordinates,\" which represent the
gray matter as cortical surface vertices (left and right) and subcortical voxels
(cerebellum, basal ganglia, and other deep gray matter). @code{ciftiTools}
provides a unified environment for reading, writing, visualizing and
manipulating CIFTI-format data.  It supports the \"dscalar,\" \"dlabel,\" and
\"dtseries\" intents.  Grayordinate data is read in as a \"xifti\" object, which is
structured for convenient access to the data and metadata, and includes support
for surface geometry files to enable spatially-dependent functionality such as
static or interactive visualizations and smoothing.")
    (license license:gpl3)))

(define-public r-cifti
  (package
    (name "r-cifti")
    (version "0.4.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cifti" version))
       (sha256
        (base32 "092334lcpkzv52bg53hzx64dnrwq67f3p9fzwchmafx1l46xrqx9"))))
    (properties `((upstream-name . "cifti")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2 r-r-utils r-oro-nifti r-gifti))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cifti")
    (synopsis
     "Toolbox for Connectivity Informatics Technology Initiative ('CIFTI') Files")
    (description
     "This package provides functions for the input/output and visualization of
medical imaging data in the form of CIFTI files
<https://www.nitrc.org/projects/cifti/>.")
    (license license:gpl2)))

(define-public r-cifinder
  (package
    (name "r-cifinder")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CIfinder" version))
       (sha256
        (base32 "1kgcf82ixv2pic31msxzzaapnas88skk033pifa0sip8pya1by4q"))))
    (properties `((upstream-name . "CIfinder")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-ratesci r-kableextra r-boot))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CIfinder")
    (synopsis "Estimate the Confidence Intervals for Predictive Values")
    (description
     "Computes confidence intervals for the positive predictive value (PPV) and
negative predictive value (NPV) based on varied scenarios.  In situations where
the proportion of diseased subjects does not correspond to the disease
prevalence (e.g. case-control studies), this package provides two types of
solutions: 1) five methods for estimating confidence intervals for PPV and NPV
via ratio of two binomial proportions including Gart & Nam (1988), Walter
(1975), MOVER-J (Laud, 2017), Fieller (1954), and Bootstrap (Efron, 1979); 2)
three direct methods that compute the confidence intervals including Pepe
(2003), Zhou (2007), and Delta.  In prospective studies where the proportion of
diseased subjects is an unbiased estimate of the disease prevalence, this
package provides several methods for calculating the confidence intervals for
PPV and NPV including Clopper-Pearson, Wald, Wilson, Agresti-Coull, and Beta.
See the Details and References sections in the corresponding functions.")
    (license license:gpl3+)))

(define-public r-cif
  (package
    (name "r-cif")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cif" version))
       (sha256
        (base32 "0z0dpq5vyv8s4cn4y8ph8y4b8nb63bkqsjmlixa1kr29l132gj1l"))))
    (properties `((upstream-name . "cif")))
    (build-system r-build-system)
    (propagated-inputs (list r-lubridate))
    (home-page "https://cran.r-project.org/package=cif")
    (synopsis "Cointegrated ICU Forecasting")
    (description
     "Set of forecasting tools to predict ICU beds using a Vector Error Correction
model with a single cointegrating vector.  Method described in Berta, P.
Lovaglio, P.G. Paruolo, P. Verzillo, S., 2020. \"Real Time Forecasting of
Covid-19 Intensive Care Units demand\" Health, Econometrics and Data Group (HEDG)
Working Papers 20/16, HEDG, Department of Economics, University of York,
<https://www.york.ac.uk/media/economics/documents/hedg/workingpapers/2020/2016.pdf>.")
    (license license:gpl3)))

(define-public r-ciee
  (package
    (name "r-ciee")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CIEE" version))
       (sha256
        (base32 "03kq9cp0v41y0r2l9j5imcrsail2xsvlzhhhsrw454d4s9gqdql9"))))
    (properties `((upstream-name . "CIEE")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CIEE")
    (synopsis
     "Estimating and Testing Direct Effects in Directed Acyclic Graphs using Estimating Equations")
    (description
     "In many studies across different disciplines, detailed measures of the variables
of interest are available.  If assumptions can be made regarding the direction
of effects between the assessed variables, this has to be considered in the
analysis.  The functions in this package implement the novel approach CIEE
(causal inference using estimating equations; Konigorski et al., 2018,
<DOI:10.1002/gepi.22107>) for estimating and testing the direct effect of an
exposure variable on a primary outcome, while adjusting for indirect effects of
the exposure on the primary outcome through a secondary intermediate outcome and
potential factors influencing the secondary outcome.  The underlying directed
acyclic graph (DAG) of this considered model is described in the vignette.  CIEE
can be applied to studies in many different fields, and it is implemented here
for the analysis of a continuous primary outcome and a time-to-event primary
outcome subject to censoring.  CIEE uses estimating equations to obtain
estimates of the direct effect and robust sandwich standard error estimates.
Then, a large-sample Wald-type test statistic is computed for testing the
absence of the direct effect.  Additionally, standard multiple regression,
regression of residuals, and the structural equation modeling approach are
implemented for comparison.")
    (license license:gpl2)))

(define-public r-cici
  (package
    (name "r-cici")
    (version "0.9.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CICI" version))
       (sha256
        (base32 "0dd152f3ffasmwrhjgkd4i480cp2jkp2qy7w22xbzjm3c22mpbvz"))))
    (properties `((upstream-name . "CICI")))
    (build-system r-build-system)
    (propagated-inputs (list r-rngtools
                             r-mgcv
                             r-glmnet
                             r-ggplot2
                             r-foreach
                             r-dorng
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=CICI")
    (synopsis
     "Causal Inference with Continuous (Multiple Time Point) Interventions")
    (description
     "Estimation of counterfactual outcomes for multiple values of continuous
interventions at different time points, and plotting of causal dose-response
curves.  Details are given in Schomaker, @code{McIlleron}, Denti, Diaz (2023)
<@code{arXiv:2305.06645>}.")
    (license license:gpl2)))

(define-public r-cicerone
  (package
    (name "r-cicerone")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cicerone" version))
       (sha256
        (base32 "1z3i720970kmczg01wxwbyqwd9zby69lchw3pgqwpn2bjr66jimh"))))
    (properties `((upstream-name . "cicerone")))
    (build-system r-build-system)
    (arguments
     (list
      #:modules '((guix build r-build-system)
                  (guix build minify-build-system)
                  (guix build utils)
                  (ice-9 match))
      #:imported-modules `(,@%r-build-system-modules (guix build
                                                      minify-build-system))
      #:phases '(modify-phases %standard-phases
                  (add-after 'unpack 'process-javascript
                    (lambda* (#:key inputs #:allow-other-keys)
                      (with-directory-excursion "inst/"
                        (for-each (match-lambda
                                    ((source . target) (minify source
                                                               #:target target)))
                                  '())))))))
    (propagated-inputs (list r-shiny r-r6 r-assertthat))
    (native-inputs (list esbuild))
    (home-page "https://cicerone.john-coene.com/")
    (synopsis "Provide Tours of 'Shiny' Applications")
    (description "Provide step by step guided tours of Shiny applications.")
    (license license:expat)))

(define-public r-ciccr
  (package
    (name "r-ciccr")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ciccr" version))
       (sha256
        (base32 "0zhhb6dq9js2wx18hq41pdqawc4pccg7wpxii1447c5sj0lmgahf"))))
    (properties `((upstream-name . "ciccr")))
    (build-system r-build-system)
    (propagated-inputs (list r-glmnet))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/sokbae/ciccr/")
    (synopsis "Causal Inference in Case-Control and Case-Population Studies")
    (description
     "Estimation and inference methods for causal relative and attributable risk in
case-control and case-population studies under the monotone treatment response
and monotone treatment selection assumptions.  For more details, see the paper
by Jun and Lee (2023), \"Causal Inference under Outcome-Based Sampling with
Monotonicity Assumptions,\" <@code{arXiv:2004.08318} [econ.EM]>, accepted for
publication in Journal of Business & Economic Statistics.")
    (license license:gpl3)))

(define-public r-cicalibrate
  (package
    (name "r-cicalibrate")
    (version "0.42.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ciCalibrate" version))
       (sha256
        (base32 "1pgfc63w50isqmzdpzbind8qdj9h2q3njiwchxb0a95zgycgyydi"))))
    (properties `((upstream-name . "ciCalibrate")))
    (build-system r-build-system)
    (propagated-inputs (list r-lamw))
    (home-page "https://github.com/SamCH93/ciCalibrate")
    (synopsis "Calibration of Confidence Intervals to Support Intervals")
    (description
     "This package provides functionality for computing support intervals for
univariate parameters based on confidence intervals or parameter estimates with
standard errors (Pawel et al., 2022) <doi:10.48550/@code{arXiv.2206.12290>}.")
    (license license:gpl3)))

(define-public r-cica
  (package
    (name "r-cica")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CICA" version))
       (sha256
        (base32 "0kl6hg2vn8w6imvrimwscj2qpgjg3fbvcjv06ax17ilci87zahx6"))))
    (properties `((upstream-name . "CICA")))
    (build-system r-build-system)
    (propagated-inputs (list r-servr
                             r-rnifti
                             r-rfast
                             r-plotly
                             r-oro-nifti
                             r-neurobase
                             r-multiway
                             r-mclust
                             r-magrittr
                             r-ica
                             r-htmltools))
    (home-page
     "https://www.sciencedirect.com/science/article/pii/S0165027022002448")
    (synopsis "Clusterwise Independent Component Analysis")
    (description
     "Clustering multi-subject resting state functional Magnetic Resonance Imaging
data.  This methods enables the clustering of subjects based on multi-subject
resting state functional Magnetic Resonance Imaging data.  Objects are clustered
based on similarities and differences in cluster-specific estimated components
obtained by Independent Component Analysis.")
    (license license:gpl3)))

(define-public r-ciaawconsensus
  (package
    (name "r-ciaawconsensus")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CIAAWconsensus" version))
       (sha256
        (base32 "0yhay4fp5lyf0sdcf807yvys17qz9cr5f5ikim25mq336p7fp03x"))))
    (properties `((upstream-name . "CIAAWconsensus")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-numderiv r-mvtnorm r-matrix))
    (home-page "https://cran.r-project.org/package=CIAAWconsensus")
    (synopsis "Isotope Ratio Meta-Analysis")
    (description
     "Calculation of consensus values for atomic weights, isotope amount ratios, and
isotopic abundances with the associated uncertainties using multivariate
meta-regression approach for consensus building.")
    (license (license:fsdg-compatible "Unlimited"))))

(define-public r-chyper
  (package
    (name "r-chyper")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chyper" version))
       (sha256
        (base32 "0ps66gqngi38lz8sq4zsvdbmj0qn4pz8aax9dgmngmwb8hdd503r"))))
    (properties `((upstream-name . "chyper")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=chyper")
    (synopsis "Functions for Conditional Hypergeometric Distributions")
    (description
     "An implementation of the probability mass function, cumulative density function,
quantile function, random number generator, maximum likelihood estimator, and
p-value generator from a conditional hypergeometric distribution: the
distribution of how many items are in the overlap of all samples when samples of
arbitrary size are each taken without replacement from populations of arbitrary
size.")
    (license license:expat)))

(define-public r-chunkr
  (package
    (name "r-chunkr")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chunkR" version))
       (sha256
        (base32 "1kw3hsx5k4cdicx0hc1v0mf2nzvqg95shx2xv05vb2pass48qw48"))))
    (properties `((upstream-name . "chunkR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://cran.r-project.org/package=chunkR")
    (synopsis "Read Tables in Chunks")
    (description
     "Read tables chunk by chunk using a C++ backend and a simple R interface.")
    (license license:gpl2+)))

(define-public r-chunkhooks
  (package
    (name "r-chunkhooks")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chunkhooks" version))
       (sha256
        (base32 "1kps7widb9ql01njy8xl03lplrybl2ci5fvx5vzzwnwps6s4y3fm"))))
    (properties `((upstream-name . "chunkhooks")))
    (build-system r-build-system)
    (propagated-inputs (list r-prettyunits r-measurements r-knitr))
    (native-inputs (list r-knitr))
    (home-page "https://chunkhooks.atusy.net")
    (synopsis "Chunk Hooks for 'R Markdown'")
    (description
     "Set chunk hooks for R Markdown documents <https://rmarkdown.rstudio.com/>, and
improve user experience.  For example, change units of figure sizes, benchmark
chunks, and number lines on code blocks.")
    (license license:expat)))

(define-public r-chunked
  (package
    (name "r-chunked")
    (version "0.6.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chunked" version))
       (sha256
        (base32 "1j16am4nzwy2ckisksl5mk8h05ala6lpdd5qrb1gwyrhli4lx45a"))))
    (properties `((upstream-name . "chunked")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-progress r-laf r-dplyr r-dbi))
    (home-page "https://github.com/edwindj/chunked")
    (synopsis "Chunkwise Text-File Processing for 'dplyr'")
    (description
     "Data stored in text file can be processed chunkwise using dplyr commands.  These
are recorded and executed per data chunk, so large files can be processed with
limited memory using the @code{LaF} package.")
    (license license:gpl2)))

(define-public r-chronosphere
  (package
    (name "r-chronosphere")
    (version "0.6.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chronosphere" version))
       (sha256
        (base32 "1simv75zr3x448sbyig5nyg40q9p3gibxjzi1d1gdyiaqncp1n6w"))))
    (properties `((upstream-name . "chronosphere")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=chronosphere")
    (synopsis "Evolving Earth System Variables")
    (description
     "The implemented functions allow the query, download, and import of
remotely-stored and version-controlled data items.  The inherent meta-database
maps data files and import code to programming classes and allows access to
these items via files deposited in public repositories.  The purpose of the
project is to increase reproducibility and establish version tracking of results
from (paleo)environmental/ecological research.")
    (license (license:fsdg-compatible "CC BY 4.0"))))

(define-public r-chronochrt
  (package
    (name "r-chronochrt")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chronochrt" version))
       (sha256
        (base32 "1qk380jqbddin0kxaf7dgzh658vikchx5snza1bgqbn11xx662wc"))))
    (properties `((upstream-name . "chronochrt")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-rlang
                             r-readr
                             r-magrittr
                             r-magick
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://gitlab.com/archaeothommy/chronochrt")
    (synopsis "Creating Chronological Charts")
    (description
     "Easy way to draw chronological charts from tables, aiming to include an
intuitive environment for anyone new to R. Includes ggplot2 geoms and theme for
chronological charts.")
    (license license:gpl3)))

(define-public r-chronicler
  (package
    (name "r-chronicler")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chronicler" version))
       (sha256
        (base32 "024y9n21zr9pzblnr3ixhvd7hcar24xh0xwch7cp7kab1nw90p84"))))
    (properties `((upstream-name . "chronicler")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-rlang
                             r-maybe
                             r-dplyr
                             r-diffobj
                             r-clipr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=chronicler")
    (synopsis "Add Logging to Functions")
    (description
     "Decorate functions to make them return enhanced output.  The enhanced output
consists in an object of type chronicle containing the result of the function
applied to its arguments, as well as a log detailing when the function was run,
what were its inputs, what were the errors (if the function failed to run) and
other useful information.  Tools to handle decorated functions are included,
such as a forward pipe operator that makes chaining decorated functions
possible.")
    (license license:gpl3+)))

(define-public r-chronicle
  (package
    (name "r-chronicle")
    (version "0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chronicle" version))
       (sha256
        (base32 "0yfrxr93fbxgpxjs1gb56pdx1kk4nn9xvy2csgl1rhzrgbl343m3"))))
    (properties `((upstream-name . "chronicle")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-viridis
                             r-skimr
                             r-scales
                             r-rmdformats
                             r-rmarkdown
                             r-rlang
                             r-readr
                             r-purrr
                             r-prettydoc
                             r-plotly
                             r-magrittr
                             r-knitr
                             r-glue
                             r-ggplot2
                             r-dygraphs
                             r-dt
                             r-dplyr
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=chronicle")
    (synopsis "Grammar for Creating R Markdown Reports")
    (description
     "This package provides a system for creating R Markdown reports with a sequential
syntax.")
    (license license:gpl3+)))

(define-public r-chromseq
  (package
    (name "r-chromseq")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chromseq" version))
       (sha256
        (base32 "0m9dnm50iw176ffn6syd3538hxmjhkrxfzaf13210q100wk0lgz2"))))
    (properties `((upstream-name . "chromseq")))
    (build-system r-build-system)
    (home-page "https://github.com/MSQ-123/chromseq")
    (synopsis "Split Chromosome 'Fasta' File")
    (description
     "Chromosome files in the Fasta format usually contain large sequences like human
genome.  Sometimes users have to split these chromosomes into different files
according to their chromosome number.  The chromseq can help to handle this.  So
the selected chromosome sequence can be used for downstream analysis like motif
finding.  Howard Y. Chang(2019) <doi:10.1038/s41587-019-0206-z>.")
    (license license:artistic2.0)))

(define-public r-chromote
  (package
    (name "r-chromote")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chromote" version))
       (sha256
        (base32 "0iwxrw3sbdanqzd49p809hvw839fmv93g7a862s2rf8m00x5ccx2"))))
    (properties `((upstream-name . "chromote")))
    (build-system r-build-system)
    (propagated-inputs (list r-websocket
                             r-rlang
                             r-r6
                             r-promises
                             r-processx
                             r-magrittr
                             r-later
                             r-jsonlite
                             r-fastmap
                             r-curl))
    (home-page "https://rstudio.github.io/chromote/")
    (synopsis "Headless Chrome Web Browser Interface")
    (description
     "An implementation of the Chrome @code{DevTools} Protocol', for controlling a
headless Chrome web browser.")
    (license license:gpl2)))

(define-public r-chromer
  (package
    (name "r-chromer")
    (version "0.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chromer" version))
       (sha256
        (base32 "0x9xhih0a19mqwiqs7bljcdgki874ii653v91frkwsr2y2yd9j7c"))))
    (properties `((upstream-name . "chromer")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-httr r-dplyr))
    (home-page "https://docs.ropensci.org/chromer/")
    (synopsis "Interface to Chromosome Counts Database API")
    (description
     "This package provides a programmatic interface to the Chromosome Counts Database
(<https://taux.evolseq.net/CCDB_web/>), Rice et al. (2014)
<doi:10.1111/nph.13191>.  This package is part of the R@code{OpenSci} suite
(<https://ropensci.org>).")
    (license license:expat)))

(define-public r-chromconverter
  (package
    (name "r-chromconverter")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chromConverter" version))
       (sha256
        (base32 "0mpakgcqmpw0s7vcndqfmd2n2imn35nh5nkps07aj0vgd7z9ib8w"))))
    (properties `((upstream-name . "chromConverter")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-tidyr
                             r-stringr
                             r-reticulate
                             r-readxl
                             r-readr
                             r-purrr
                             r-magrittr))
    (home-page "https://github.com/ethanbass/chromConverter")
    (synopsis "Chromatographic File Converter")
    (description
     "Reads chromatograms from binary formats into R objects.  Currently supports
conversion of Agilent @code{ChemStation}', Agilent @code{MassHunter}', and
@code{ThermoRaw} files as well as various text-based formats.  Utilizes file
parsers from external libraries, such as Aston <https://github.com/bovee/aston>,
Entab <https://github.com/bovee/entab>, and @code{ThermoRawFileParser}
<https://github.com/compomics/@code{ThermoRawFileParser>}.")
    (license license:gpl3+)))

(define-public r-christmas
  (package
    (name "r-christmas")
    (version "1.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "christmas" version))
       (sha256
        (base32 "0gqyxvhx8nvcrjxqrybvxyc3dgwvd3z9ln4fig6q3zamfpdmljb7"))))
    (properties `((upstream-name . "christmas")))
    (build-system r-build-system)
    (propagated-inputs (list r-animation))
    (home-page "https://sites.google.com/view/josebarrera/")
    (synopsis "Generation of Different Animated Christmas Cards")
    (description
     "Generation of different Christmas cards, most of them being animated.  Most of
the cards can be generated in three languages (English, Catalan and Spanish).
The collection started in 2009.")
    (license license:gpl2)))

(define-public r-chouca
  (package
    (name "r-chouca")
    (version "0.1.99")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chouca" version))
       (sha256
        (base32 "1gnilv8ww106mz5wnry826gysgsaq7mvd83ms0j5jhkkqmsqy2dd"))))
    (properties `((upstream-name . "chouca")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-plyr r-digest))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/alexgenin/chouca")
    (synopsis "Stochastic Cellular Automaton Engine")
    (description
     "An engine for stochastic cellular automata.  It provides a high-level interface
to declare a model, which can then be simulated by various backends (Genin et
al. (2023) <doi:10.1101/2023.11.08.566206>).")
    (license license:gpl3+)))

(define-public r-choroplethrmaps
  (package
    (name "r-choroplethrmaps")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "choroplethrMaps" version))
       (sha256
        (base32 "0ghqb2d1h0qkbcsll6ck2qk5sfvdwsrlh3phlbsjbak30832j7fr"))))
    (properties `((upstream-name . "choroplethrMaps")))
    (build-system r-build-system)
    (home-page "http://www.arilamstein.com/open-source")
    (synopsis "Contains Maps Used by the 'choroplethr' Package")
    (description
     "This package contains 3 maps.  1) US States 2) US Counties 3) Countries of the
world.")
    (license license:bsd-3)))

(define-public r-choroplethradmin1
  (package
    (name "r-choroplethradmin1")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "choroplethrAdmin1" version))
       (sha256
        (base32 "13ljs21hdhiv6n4napmk1gjnjhpll6j5wyijzv4xnnbi1y3ns7a9"))))
    (properties `((upstream-name . "choroplethrAdmin1")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2))
    (home-page "http://www.arilamstein.com/open-source")
    (synopsis "Contains an Administrative-Level-1 Map of the World")
    (description
     "This package contains an administrative-level-1 map of the world.
Administrative-level-1 is the generic term for the largest sub-national
subdivision of a country.  This package was created for use with the choroplethr
package.")
    (license license:bsd-3)))

(define-public r-choroplethr
  (package
    (name "r-choroplethr")
    (version "3.7.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "choroplethr" version))
       (sha256
        (base32 "053zs3bxr38izdkm1mhwqnrg7j5mb1dwjdx0dvsbv9l3nrb39par"))))
    (properties `((upstream-name . "choroplethr")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-wdi
                             r-tigris
                             r-tidyr
                             r-tidycensus
                             r-stringr
                             r-rvest
                             r-rgooglemaps
                             r-r6
                             r-hmisc
                             r-gridextra
                             r-ggplot2
                             r-ggmap
                             r-dplyr
                             r-acs))
    (home-page "www.choroplethr.com")
    (synopsis "Simplify the Creation of Choropleth Maps in R")
    (description
     "Choropleths are thematic maps where geographic regions, such as states, are
colored according to some metric, such as the number of people who live in that
state.  This package simplifies this process by 1.  Providing ready-made
functions for creating choropleths of common maps.  2.  Providing data and API
connections to interesting data sources for making choropleths.  3.  Providing a
framework for creating choropleths from arbitrary shapefiles.  4.  Overlaying
those maps over reference maps from Google Maps.")
    (license license:bsd-3)))

(define-public r-chords
  (package
    (name "r-chords")
    (version "0.95.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chords" version))
       (sha256
        (base32 "1v6zvl1mv9fyf6hx1fpbj3i7s893n4y1w4j9rw1arps006qz2jqn"))))
    (properties `((upstream-name . "chords")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-mass))
    (home-page "https://cran.r-project.org/package=chords")
    (synopsis "Estimation in Respondent Driven Samples")
    (description "Maximum likelihood estimation in respondent driven samples.")
    (license license:gpl2)))

(define-public r-chor
  (package
    (name "r-chor")
    (version "0.0-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ChoR" version))
       (sha256
        (base32 "08mildsx542zfm0kcdakcv7c71hb4jgbcq1lhidf0fz76zj1pzk1"))))
    (properties `((upstream-name . "ChoR")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (propagated-inputs (list r-rjava r-commonsmath))
    (home-page "https://cran.r-project.org/package=ChoR")
    (synopsis "Chordalysis R Package")
    (description
     "Learning the structure of graphical models from datasets with thousands of
variables.  More information about the research papers detailing the theory
behind Chordalysis is available at <http://www.francois-petitjean.com/Research>
(KDD 2016, SDM 2015, ICDM 2014, ICDM 2013).  The R package development site is
<https://github.com/@code{HerrmannM/Monash-ChoR>}.")
    (license license:gpl3)))

(define-public r-chopthin
  (package
    (name "r-chopthin")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chopthin" version))
       (sha256
        (base32 "1ixmgq6igd2ji88qba7scny1j8rrizcf76dk4ymk3hah5dln97fz"))))
    (properties `((upstream-name . "chopthin")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://cran.r-project.org/package=chopthin")
    (synopsis "The Chopthin Resampler")
    (description
     "Resampling is a standard step in particle filtering and in sequential Monte
Carlo.  This package implements the chopthin resampler, which keeps a bound on
the ratio between the largest and the smallest weights after resampling.")
    (license license:gpl3)))

(define-public r-choplump
  (package
    (name "r-choplump")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "choplump" version))
       (sha256
        (base32 "16a6qwnh08qdx3n5abgjrnmyiqqf3i1pap3y965ikb2r1jfr9b3f"))))
    (properties `((upstream-name . "choplump")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=choplump")
    (synopsis "Permutation Test for Some Positive and Many Zero Responses")
    (description
     "Calculates permutation tests that can be powerful for comparing two groups with
some positive but many zero responses (see Follmann, Fay, and Proschan
<DOI:10.1111/j.1541-0420.2008.01131.x>).")
    (license license:gpl3)))

(define-public r-choosepc
  (package
    (name "r-choosepc")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "choosepc" version))
       (sha256
        (base32 "0a8xvgpgaxxlb102ix5j98zd8wvi1xzs0cg7im8g2ly1h0mv1rxy"))))
    (properties `((upstream-name . "choosepc")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfast2))
    (home-page "https://cran.r-project.org/package=choosepc")
    (synopsis
     "Choose the Number of Principal Components via Recistruction Error")
    (description
     "One way to choose the number of principal components is via the reconstruction
error.  This package is designed mainly for this purpose.  Graphical
representation is also supported, plus some other principal component analysis
related functions.  References include: Jolliffe I.T. (2002).  Principal
Component Analysis. <doi:10.1007/b98835> and Mardia K.V., Kent J.T. and Bibby
J.M. (1979).  Multivariate Analysis.  ISBN: 978-0124712522.  London: Academic
Press.")
    (license license:gpl2+)))

(define-public r-cholwishart
  (package
    (name "r-cholwishart")
    (version "1.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CholWishart" version))
       (sha256
        (base32 "1rnd0f2vx43fi6x4xqgaxlyl64s8l474zv1wj1wqvkfg0njglzb2"))))
    (properties `((upstream-name . "CholWishart")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://gzt.github.io/CholWishart/")
    (synopsis "Cholesky Decomposition of the Wishart Distribution")
    (description
     "Sampling from the Cholesky factorization of a Wishart random variable, sampling
from the inverse Wishart distribution, sampling from the Cholesky factorization
of an inverse Wishart random variable, sampling from the pseudo Wishart
distribution, sampling from the generalized inverse Wishart distribution,
computing densities for the Wishart and inverse Wishart distributions, and
computing the multivariate gamma and digamma functions.  Provides a header file
so the C functions can be called directly from other programs.")
    (license license:gpl3+)))

(define-public r-cholera
  (package
    (name "r-cholera")
    (version "0.8.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cholera" version))
       (sha256
        (base32 "0qfy7xqkihn8jfxnhg0l5y0mii52lbfwmg663bqsjapylqc9bjcd"))))
    (properties `((upstream-name . "cholera")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridislite
                             r-tsp
                             r-threejs
                             r-terra
                             r-tanaka
                             r-sp
                             r-rcolorbrewer
                             r-pracma
                             r-kernsmooth
                             r-igraph
                             r-histdata
                             r-ggplot2
                             r-geosphere
                             r-elevatr
                             r-deldir))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/lindbrook/cholera")
    (synopsis "Amend, Augment and Aid Analysis of John Snow's Cholera Map")
    (description
     "Amends errors, augments data and aids analysis of John Snow's map of the 1854
London cholera outbreak.")
    (license license:gpl2+)))

(define-public r-choirbm
  (package
    (name "r-choirbm")
    (version "0.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CHOIRBM" version))
       (sha256
        (base32 "1ak9swfnc0i23pv6mg5bav09pb7v0afdr7h08s1pyd77wyzf95df"))))
    (properties `((upstream-name . "CHOIRBM")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-rlang r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/emcramer/CHOIRBM")
    (synopsis "Plots the CHOIR Body Map")
    (description
     "Collection of utility functions for visualizing body map data collected with the
Collaborative Health Outcomes Information Registry.")
    (license license:expat)))

(define-public r-choicemodelr
  (package
    (name "r-choicemodelr")
    (version "1.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ChoiceModelR" version))
       (sha256
        (base32 "0kn64wa2da0kimg92nn9hw96yr6li69k309b7kh5g1dsz9p30bki"))))
    (properties `((upstream-name . "ChoiceModelR")))
    (build-system r-build-system)
    (home-page "https://www.decisionanalyst.com/")
    (synopsis "Choice Modeling in R")
    (description
     "This package implements an MCMC algorithm to estimate a hierarchical multinomial
logit model with a normal heterogeneity distribution.  The algorithm uses a
hybrid Gibbs Sampler with a random walk metropolis step for the MNL coefficients
for each unit.  Dependent variable may be discrete or continuous.  Independent
variables may be discrete or continuous with optional order constraints.  Means
of the distribution of heterogeneity can optionally be modeled as a linear
function of unit characteristics variables.")
    (license license:gpl3+)))

(define-public r-choicedes
  (package
    (name "r-choicedes")
    (version "0.9-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "choiceDes" version))
       (sha256
        (base32 "1nsc8p4svfc6z7ckffl24c0acnaxi6cnpz7jq03vzn6spxvpjcmw"))))
    (properties `((upstream-name . "choiceDes")))
    (build-system r-build-system)
    (propagated-inputs (list r-algdesign))
    (home-page "https://cran.r-project.org/package=choiceDes")
    (synopsis "Design Functions for Choice Studies")
    (description
     "Design functions for DCMs and other types of choice studies (including
@code{MaxDiff} and other tradeoffs).")
    (license license:gpl2+)))

(define-public r-chnosz
  (package
    (name "r-chnosz")
    (version "2.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CHNOSZ" version))
       (sha256
        (base32 "1iwg6pfnkq5ap0p3nscadfx6fyakvvjgmgx2wkva65bgkbhs6x9v"))))
    (properties `((upstream-name . "CHNOSZ")))
    (build-system r-build-system)
    (native-inputs (list r-knitr gfortran))
    (home-page "https://www.chnosz.net/")
    (synopsis "Thermodynamic Calculations and Diagrams for Geochemistry")
    (description
     "An integrated set of tools for thermodynamic calculations in aqueous
geochemistry and geobiochemistry.  Functions are provided for writing balanced
reactions to form species from user-selected basis species and for calculating
the standard molal properties of species and reactions, including the standard
Gibbs energy and equilibrium constant.  Calculations of the non-equilibrium
chemical affinity and equilibrium chemical activity of species can be portrayed
on diagrams as a function of temperature, pressure, or activity of basis
species; in two dimensions, this gives a maximum affinity or predominance
diagram.  The diagrams have formatted chemical formulas and axis labels, and
water stability limits can be added to Eh-@code{pH}, oxygen fugacity-
temperature, and other diagrams with a redox variable.  The package has been
developed to handle common calculations in aqueous geochemistry, such as
solubility due to complexation of metal ions, mineral buffers of redox or
@code{pH}, and changing the basis species across a diagram (\"mosaic diagrams\").
CHNOSZ also implements a group additivity algorithm for the standard
thermodynamic properties of proteins.")
    (license license:gpl3)))

(define-public r-chngpt
  (package
    (name "r-chngpt")
    (version "2023.11-29")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chngpt" version))
       (sha256
        (base32 "1zz0wgard6a1y36r78pfp5gqfjm12xlvh5cmdq3297m4d7jvrn34"))))
    (properties `((upstream-name . "chngpt")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-rhpcblasctl
                             r-mass
                             r-lme4
                             r-kyotil
                             r-boot))
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=chngpt")
    (synopsis "Estimation and Hypothesis Testing for Threshold Regression")
    (description
     "Threshold regression models are also called two-phase regression, broken-stick
regression, split-point regression, structural change models, and regression
kink models, with and without interaction terms.  Methods for both continuous
and discontinuous threshold models are included, but the support for the former
is much greater.  This package is described in Fong, Huang, Gilbert and Permar
(2017) <DOI:10.1186/s12859-017-1863-x> and the package vignette.")
    (license license:gpl2+)))

(define-public r-chncapitalstock
  (package
    (name "r-chncapitalstock")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CHNCapitalStock" version))
       (sha256
        (base32 "0hldv4mbsr0y9r34f7b5zpdr2bl77vnsd2d9lfajd2bqnjqzv38d"))))
    (properties `((upstream-name . "CHNCapitalStock")))
    (build-system r-build-system)
    (propagated-inputs (list r-dplyr))
    (home-page "https://github.com/common2016/CapitalStock")
    (synopsis "Compute Chinese Capital Stocks")
    (description
     "Compute Chinese capital stocks in provinces level, based on Zhang (2008)
<DOI:10.1080/14765280802028302>.")
    (license license:gpl2)))

(define-public r-chmm
  (package
    (name "r-chmm")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CHMM" version))
       (sha256
        (base32 "07fdvnwhblwvljbl2z0vs42nwki67yl5ly3fj40p50k3rnqqmavj"))))
    (properties `((upstream-name . "CHMM")))
    (build-system r-build-system)
    (propagated-inputs (list r-mclust))
    (home-page "http://github.com/julieaubert/CHMM")
    (synopsis "Coupled Hidden Markov Models")
    (description
     "An exact and a variational inference for coupled Hidden Markov Models applied to
the joint detection of copy number variations.")
    (license license:gpl2)))

(define-public r-chlorpromaziner
  (package
    (name "r-chlorpromaziner")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chlorpromazineR" version))
       (sha256
        (base32 "0w7v6xk3vyf9dyf9bh5v9516v78yhcdvy7h1140pg2yw8xmfyr0r"))))
    (properties `((upstream-name . "chlorpromazineR")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/chlorpromazineR/")
    (synopsis "Convert Antipsychotic Doses to Chlorpromazine Equivalents")
    (description
     "As different antipsychotic medications have different potencies, the doses of
different medications cannot be directly compared.  Various strategies are used
to convert doses into a common reference so that comparison is meaningful.
Chlorpromazine (CPZ) has historically been used as a reference medication into
which other antipsychotic doses can be converted, as \"chlorpromazine-equivalent
doses\".  Using conversion keys generated from widely-cited scientific papers,
e.g. Gardner et.  al 2010 <doi:10.1176/appi.ajp.2009.09060802> and Leucht et al.
 2016 <doi:10.1093/schbul/sbv167>, antipsychotic doses are converted to CPZ (or
any specified antipsychotic) equivalents.  The use of the package is described
in the included vignette.  Not for clinical use.")
    (license license:gpl3)))

(define-public r-chkptstanr
  (package
    (name "r-chkptstanr")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chkptstanr" version))
       (sha256
        (base32 "0p0pzpzyg3sw4gnvzdx34f96yxidpykq49v5xlhnrsnpjzajjfs3"))))
    (properties `((upstream-name . "chkptstanr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rstan r-rdpack r-brms r-abind))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=chkptstanr")
    (synopsis "Checkpoint MCMC Sampling with 'Stan'")
    (description
     "Fit Bayesian models in Stan <doi: 10.18637/jss.v076.i01> with checkpointing,
that is, the ability to stop the MCMC sampler at will, and then pick right back
up where the MCMC sampler left off.  Custom Stan models can be fitted, or the
popular package brms <doi: 10.18637/jss.v080.i01> can be used to generate the
Stan code.  This package is fully compatible with the R packages brms',
posterior', cmdstanr', and bayesplot'.")
    (license (list license:asl2.0
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-chisquare
  (package
    (name "r-chisquare")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chisquare" version))
       (sha256
        (base32 "1vjhsi520p9m46xay9dh0la5ypyhi19gyg5i568d2ywka4g2ssac"))))
    (properties `((upstream-name . "chisquare")))
    (build-system r-build-system)
    (propagated-inputs (list r-gt))
    (home-page "https://cran.r-project.org/package=chisquare")
    (synopsis
     "Chi-Square and G-Square Test of Independence, Power and Residual Analysis, Measures of Categorical Association")
    (description
     "This package provides the facility to perform the chi-square and G-square test
of independence, calculates the power of the traditional chi-square test,
compute permutation and Monte Carlo p-value, and provides measures of
association for tables of any size such as Phi, Phi corrected, odds ratio with
95 percent CI and p-value, Yule Q and Y, adjusted contingency coefficient,
Cramer's V, V corrected, V standardised, bias-corrected V, W, Cohen's w,
Goodman-Kruskal's lambda, gamma, tau, Cohen's k.  It also calculates
standardised, moment-corrected standardised, and adjusted standardised
residuals, and their significance, as well as the Quetelet Index, IJ association
factor, and adjusted standardised counts.  It also computes the
chi-square-maximising version of the input table.  Different outputs are
returned in nicely formatted tables.")
    (license license:gpl2+)))

(define-public r-chisq-posthoc-test
  (package
    (name "r-chisq-posthoc-test")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chisq.posthoc.test" version))
       (sha256
        (base32 "0lvj3jqhaj1ijjpzvpq3fn3a1y3fgv69pxh91j6k958pn6vmp40i"))))
    (properties `((upstream-name . "chisq.posthoc.test")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "http://chisq-posthoc-test.ebbert.nrw/")
    (synopsis
     "Post Hoc Analysis for Pearson's Chi-Squared Test for Count Data")
    (description
     "Perform post hoc analysis based on residuals of Pearson's Chi-squared Test for
Count Data based on T. Mark Beasley & Randall E. Schumacker (1995) <doi:
10.1080/00220973.1995.9943797>.")
    (license license:gpl3)))

(define-public r-chirps
  (package
    (name "r-chirps")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chirps" version))
       (sha256
        (base32 "1yj91rvcsfsr2nmvk7qnxwfkbiblm4bdazs2p83g8ax4fwkrp39c"))))
    (properties `((upstream-name . "chirps")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra r-sf r-jsonlite r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/chirps/")
    (synopsis "API Client for CHIRPS and CHIRTS")
    (description
     "API Client for the Climate Hazards Center CHIRPS and CHIRTS'.  The CHIRPS data
is a quasi-global (50Â°S â 50Â°N) high-resolution (0.05 arc-degrees) rainfall
data set, which incorporates satellite imagery and in-situ station data to
create gridded rainfall time series for trend analysis and seasonal drought
monitoring.  CHIRTS is a quasi-global (60Â°S â 70Â°N), high-resolution data
set of daily maximum and minimum temperatures.  For more details on CHIRPS and
CHIRTS data please visit its official home page <https://www.chc.ucsb.edu/data>.")
    (license license:expat)))

(define-public r-chippcr
  (package
    (name "r-chippcr")
    (version "1.0-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chipPCR" version))
       (sha256
        (base32 "0q30ncnvbipvqbpxrx2yb68i2ybdfl1fbzj3f12dd2wmjjl72q1x"))))
    (properties `((upstream-name . "chipPCR")))
    (build-system r-build-system)
    (propagated-inputs (list r-signal
                             r-shiny
                             r-robustbase
                             r-rfit
                             r-quantreg
                             r-ptw
                             r-outliers
                             r-mass
                             r-lmtest))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://github.com/PCRuniversum/chipPCR")
    (synopsis "Toolkit of Helper Functions to Pre-Process Amplification Data")
    (description
     "This package provides a collection of functions to pre-process amplification
curve data from polymerase chain reaction (PCR) or isothermal amplification
reactions.  Contains functions to normalize and baseline amplification curves,
to detect both the start and end of an amplification reaction, several smoothers
(e.g., LOWESS, moving average, cubic splines, Savitzky-Golay), a function to
detect false positive amplification reactions and a function to determine the
amplification efficiency.  Quantification point (Cq) methods include the first
(FDM) and second approximate derivative maximum (SDM) methods (calculated by a
5-point-stencil) and the cycle threshold method.  Data sets of experimental
nucleic acid amplification systems ('@code{VideoScan} HCU', capillary convective
PCR (@code{ccPCR})) and commercial systems are included.  Amplification curves
were generated by helicase dependent amplification (HDA), @code{ccPCR} or PCR.
As detection system intercalating dyes (@code{EvaGreen}, SYBR Green) and
hydrolysis probes (@code{TaqMan}) were used.  For more information see: Roediger
et al. (2015) <doi:10.1093/bioinformatics/btv205>.")
    (license license:gpl3)))

(define-public r-chinesenames
  (package
    (name "r-chinesenames")
    (version "2023.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ChineseNames" version))
       (sha256
        (base32 "10y5b1ca4xcdp6czdp21mwg07f2346wr8sm6czlj8bb475xp8bjs"))))
    (properties `((upstream-name . "ChineseNames")))
    (build-system r-build-system)
    (propagated-inputs (list r-data-table r-brucer))
    (home-page "https://psychbruce.github.io/ChineseNames/")
    (synopsis "Chinese Name Database 1930-2008")
    (description
     "This package provides a database of Chinese surnames and Chinese given names
(1930-2008).  This database contains nationwide frequency statistics of 1,806
Chinese surnames and 2,614 Chinese characters used in given names, covering
about 1.2 billion Han Chinese population (96.8% of the Han Chinese
household-registered population born from 1930 to 2008 and still alive in 2008).
 This package also contains a function for computing multiple features of
Chinese surnames and Chinese given names for scientific research (e.g., name
uniqueness, name gender, name valence, and name warmth/competence).")
    (license license:gpl3)))

(define-public r-chinese-misc
  (package
    (name "r-chinese-misc")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chinese.misc" version))
       (sha256
        (base32 "0hlna52g00nh3908wgpb9ldgghff3gfjx24vmk5gikkazdqk9zrh"))))
    (properties `((upstream-name . "chinese.misc")))
    (build-system r-build-system)
    (propagated-inputs (list r-tm
                             r-stringi
                             r-slam
                             r-purrr
                             r-nlp
                             r-matrix
                             r-jiebar))
    (home-page
     "https://github.com/githubwwwjjj/chinese.misc/blob/master/README.md")
    (synopsis "Miscellaneous Tools for Chinese Text Mining and More")
    (description
     "Efforts are made to make Chinese text mining easier, faster, and robust to
errors.  Document term matrix can be generated by only one line of code;
detecting encoding, segmenting and removing stop words are done automatically.
Some convenient tools are also supplied.")
    (license license:gpl3)))

(define-public r-chillr
  (package
    (name "r-chillr")
    (version "0.75")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chillR" version))
       (sha256
        (base32 "0b8r8s7vqgpb6jjbqaf24yig2adagfl6rnnppx15mdhz8bmjc5aq"))))
    (properties `((upstream-name . "chillR")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml
                             r-tidyr
                             r-stringr
                             r-scales
                             r-rmawgen
                             r-rlang
                             r-reshape2
                             r-readxl
                             r-rcurl
                             r-rcpp
                             r-raster
                             r-r-utils
                             r-purrr
                             r-progress
                             r-plyr
                             r-pls
                             r-patchwork
                             r-metr
                             r-magrittr
                             r-lubridate
                             r-kendall
                             r-jsonlite
                             r-httr
                             r-ggplot2
                             r-gensa
                             r-fields
                             r-ecmwfr
                             r-dplyr
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=chillR")
    (synopsis
     "Statistical Methods for Phenology Analysis in Temperate Fruit Trees")
    (description
     "The phenology of plants (i.e.  the timing of their annual life phases) depends
on climatic cues.  For temperate trees and many other plants, spring phases,
such as leaf emergence and flowering, have been found to result from the effects
of both cool (chilling) conditions and heat.  Fruit tree scientists
(pomologists) have developed some metrics to quantify chilling and heat (e.g.
see Luedeling (2012) <doi:10.1016/j.scienta.2012.07.011>). @code{chillR}
contains functions for processing temperature records into chilling (Chilling
Hours, Utah Chill Units and Chill Portions) and heat units (Growing Degree
Hours).  Regarding chilling metrics, Chill Portions are often considered the
most promising, but they are difficult to calculate.  This package makes it
easy. @code{chillR} also contains procedures for conducting a PLS analysis
relating phenological dates (e.g. bloom dates) to either mean temperatures or
mean chill and heat accumulation rates, based on long-term weather and phenology
records (Luedeling and Gassner (2012) <doi:10.1016/j.agrformet.2011.10.020>).
As of version 0.65, it also includes functions for generating weather scenarios
with a weather generator, for conducting climate change analyses for
temperature-based climatic metrics and for plotting results from such analyses.
Since version 0.70, @code{chillR} contains a function for interpolating hourly
temperature records.")
    (license license:gpl3)))

(define-public r-chillmodels
  (package
    (name "r-chillmodels")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ChillModels" version))
       (sha256
        (base32 "06hgg893anh5z8an4l1xl4liz7d0m79n21h116vkdlymayccydbr"))))
    (properties `((upstream-name . "ChillModels")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ChillModels")
    (synopsis "Processing Chill and Heat Models for Temperate Fruit Trees")
    (description
     "Calculates the chilling and heat accumulation for studies of the temperate fruit
trees.  The models in this package are: Utah (Richardson et al., 1974,
ISSN:0018-5345), Positive Chill Units - PCU (Linsley-Noaks et al., 1995,
ISSN:1017-0316), GDH-A - Growing Degree Hours by Anderson et al.(1986,
ISSN:0567-7572), GDH-R - Growing Degree Hours by Richardson et al.(1975,
ISSN:0018-5345), North Carolina (Shaltout e Unrath, 1983, ISSN:0003-1062),
Landsberg Model (Landsberg, 1974, ISSN:0305-7364), Q10 Model (Bidabe, 1967,
ISSN:0031-9368), Jones Model (Jones et al., 2013
<DOI:10.1111/j.1438-8677.2012.00590.x>), Low-Chill Model (Gilreath and Buchanan,
1981, ISSN:0003-1062), Model for Cherry \"Sweetheart\" (Guak and Nielsen, 2013
<DOI:10.1007/s13580-013-0140-9>), Model for apple \"Gala\" (Guak and Nielsen, 2013
<DOI:10.1007/s13580-013-0140-9>), Taiwan Model (Lu et al., 2012
<DOI:10.17660/@code{ActaHortic.2012.962.35>}), Dynamic Model (Fishman et al.,
1987, ISSN:0022-5193) adapted from the function Dynamic_Model() of the
@code{chillR} package (Luedeling, 2018), Unified Model (Chuine et al., 2016
<DOI:10.1111/gcb.13383>) and Heat Restriction model.")
    (license license:gpl3)))

(define-public r-chilemapas
  (package
    (name "r-chilemapas")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chilemapas" version))
       (sha256
        (base32 "00v99y02fnxzn2ysbc2fbkdfirfl1276q8d7csi18kbym3vwqmq9"))))
    (properties `((upstream-name . "chilemapas")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-sf
                             r-rmapshaper
                             r-rlang
                             r-magrittr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://pacha.dev/chilemapas/")
    (synopsis
     "Mapas de las Divisiones Politicas y Administrativas de Chile (Maps of the Political and Administrative Divisions of Chile)")
    (description
     "Mapas terrestres con topologias simplificadas.  Estos mapas no tienen precision
geodesica, por lo que aplica el DFL-83 de 1979 de la Republica de Chile y se
consideran referenciales sin validez legal.  No se incluyen los territorios
antarticos y bajo ningun evento estos mapas significan que exista una cesion u
ocupacion de territorios soberanos en contra del Derecho Internacional por parte
de Chile.  Esta paquete esta documentado intencionalmente en castellano
asciificado para que funcione sin problema en diferentes plataformas.
(Terrestrial maps with simplified toplogies.  These maps lack geodesic
precision, therefore DFL-83 1979 of the Republic of Chile applies and are
considered to have no legal validity.  Antartic territories are excluded and
under no event these maps mean there is a cession or occupation of sovereign
territories against International Laws from Chile.  This package was
intentionally documented in asciified spanish to make it work without problem on
different platforms.).")
    (license license:gpl3)))

(define-public r-childsds
  (package
    (name "r-childsds")
    (version "0.8.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "childsds" version))
       (sha256
        (base32 "1vv02kbw17b8zva2yc1qgi750z9yhyfv5xbig29dhyzvj8k00yvb"))))
    (properties `((upstream-name . "childsds")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam
                             r-tidyr
                             r-tibble
                             r-reshape2
                             r-purrrlyr
                             r-purrr
                             r-magrittr
                             r-gamlss-dist
                             r-gamlss
                             r-dplyr
                             r-class
                             r-boot))
    (home-page "https://cran.r-project.org/package=childsds")
    (synopsis "Data and Methods Around Reference Values in Pediatrics")
    (description
     "Calculation of standard deviation scores and percentiles adduced from different
standards (WHO, UK, Germany, Italy, China, etc).  Also, references for
laboratory values in children and adults are available, e.g., serum lipids,
iron-related blood parameters, IGF, liver enzymes.  See package documentation
for full list.")
    (license license:gpl3)))

(define-public r-childfree
  (package
    (name "r-childfree")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "childfree" version))
       (sha256
        (base32 "1lqwn7b0mc5v5lqqx2bhh5j110zl119whi7qwgzj0y05fdri98z2"))))
    (properties `((upstream-name . "childfree")))
    (build-system r-build-system)
    (propagated-inputs (list r-survey r-rio r-rcurl))
    (native-inputs (list r-knitr))
    (home-page "https://www.zacharyneal.com/childfree")
    (synopsis "Access and Harmonize Childfree Demographic Data")
    (description
     "Reads demographic data from a variety of public data sources, extracting and
harmonizing variables useful for the study of childfree individuals.  The
identification of childfree individuals and those with other family statuses
uses Neal & Neal's (2024) \"A Framework for Studying Adults who Neither have Nor
Want Children\" <doi:10.1177/10664807231198869>; A pre-print is available at
<doi:10.31234/osf.io/fa89m>.")
    (license license:gpl3)))

(define-public r-childesr
  (package
    (name "r-childesr")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "childesr" version))
       (sha256
        (base32 "1a58s0zph4mfmh9sdfbv7yaa20lx5gi0mca0ikzarfwxjl5knp39"))))
    (properties `((upstream-name . "childesr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmysql
                             r-purrr
                             r-magrittr
                             r-jsonlite
                             r-dplyr
                             r-dbplyr
                             r-dbi))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/langcog/childesr")
    (synopsis "Accessing the 'CHILDES' Database")
    (description
     "This package provides tools for connecting to CHILDES', an open repository for
transcripts of parent-child interaction.  For more information on the underlying
data, see <https://langcog.github.io/childes-db-website/>.")
    (license license:gpl3)))

(define-public r-childdevdata
  (package
    (name "r-childdevdata")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "childdevdata" version))
       (sha256
        (base32 "016x6xhqq1mfqlj9m5qv63k639xnqnrf5h6rdcyaa8sxn7nv34zm"))))
    (properties `((upstream-name . "childdevdata")))
    (build-system r-build-system)
    (home-page "https://github.com/d-score/childdevdata")
    (synopsis "Child Development Data")
    (description
     "Measuring child development starts by collecting responses to developmental
milestones, such as \"able to sit\" or \"says two words\".  There are many ways to
combine such responses into summaries.  The package bundles publicly available
datasets with individual milestone data for children aged 0-5 years, with the
aim of supporting the construction, evaluation, validation and interpretation of
methodologies that aggregate milestone data into informative measures of child
development.")
    (license (license:fsdg-compatible "CC BY 4.0"))))

(define-public r-chicane
  (package
    (name "r-chicane")
    (version "0.1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chicane" version))
       (sha256
        (base32 "0963r5jzyjihidh18ny9nqkim00bys3psdgrxhbah43bbl0kx43r"))))
    (properties `((upstream-name . "chicane")))
    (build-system r-build-system)
    (inputs (list bedtools))
    (propagated-inputs (list r-rmarkdown
                             r-mass
                             r-knitr
                             r-iterators
                             r-gamlss-tr
                             r-gamlss
                             r-foreach
                             r-doparallel
                             r-data-table
                             r-bedr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=chicane")
    (synopsis "Capture Hi-C Analysis Engine")
    (description
     "Toolkit for processing and calling interactions in capture Hi-C data.  Converts
BAM files into counts of reads linking restriction fragments, and identifies
pairs of fragments that interact more than expected by chance.  Significant
interactions are identified by comparing the observed read count to the expected
background rate from a count regression model.")
    (license license:gpl2)))

(define-public r-chi
  (package
    (name "r-chi")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chi" version))
       (sha256
        (base32 "1y91mwahj4j2wz0y5k5vdpq7ygq834h8jkn37n74lqnwvv1968rr"))))
    (properties `((upstream-name . "chi")))
    (build-system r-build-system)
    (home-page "https://github.com/dkahle/chi")
    (synopsis "The Chi Distribution")
    (description
     "Light weight implementation of the standard distribution functions for the chi
distribution, wrapping those for the chi-squared distribution in the stats
package.")
    (license license:gpl2)))

(define-public r-chff
  (package
    (name "r-chff")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CHFF" version))
       (sha256
        (base32 "0jv75p1bnwsad2vpxf1zwq97al9xxhk2hpnpsilf0jn0w7g9b2d3"))))
    (properties `((upstream-name . "CHFF")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CHFF")
    (synopsis
     "Closest History Flow Field Forecasting for Bivariate Time Series")
    (description
     "The software matches the current history to the closest history in a time series
to build a forecast.")
    (license license:gpl3)))

(define-public r-chevron
  (package
    (name "r-chevron")
    (version "0.2.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chevron" version))
       (sha256
        (base32 "15kqs0lcsfka159s1divhnji571dgrqc0n32h3mk9l05gznclsnk"))))
    (properties `((upstream-name . "chevron")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-tern
                             r-stringr
                             r-rtables
                             r-rlistings
                             r-rlang
                             r-purrr
                             r-nestcolor
                             r-magrittr
                             r-lubridate
                             r-lifecycle
                             r-glue
                             r-ggplot2
                             r-formatters
                             r-forcats
                             r-dunlin
                             r-dplyr
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://insightsengineering.github.io/chevron/")
    (synopsis "Standard TLGs for Clinical Trials Reporting")
    (description
     "Provide standard tables, listings, and graphs (TLGs) libraries used in clinical
trials.  This package implements a structure to reformat the data with dunlin',
create reporting tables using rtables and tern with standardized input arguments
to enable quick generation of standard outputs.  In addition, it also provides
comprehensive data checks and script generation functionality.")
    (license license:asl2.0)))

(define-public r-chestvolume
  (package
    (name "r-chestvolume")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ChestVolume" version))
       (sha256
        (base32 "01mg1a3cbsajdp5qnlswx89skq036p76racz5lmjpd5s9bwlclax"))))
    (properties `((upstream-name . "ChestVolume")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-readxl
                             r-plotly
                             r-ggplot2
                             r-geometry
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ChestVolume")
    (synopsis "Estimate the Chest Volume with Markers Data")
    (description
     "This package provides tools to process and analyze chest expansion using 3D
marker data from motion capture systems.  Includes functions for data
processing, marker position adjustment, volume calculation using convex hulls,
and visualization in 2D and 3D. Barber et al. (1996)
<doi:10.1145/235815.235821>.  TAMIYA Hiroyuki et al. (2021)
<doi:10.1038/s41598-021-01033-8>.")
    (license license:expat)))

(define-public r-chest
  (package
    (name "r-chest")
    (version "0.3.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chest" version))
       (sha256
        (base32 "0905xl1vqn8icvf44vydhd00wvz5cdnl2igr7m0jmrsv564zdj5a"))))
    (properties `((upstream-name . "chest")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-survival
                             r-mass
                             r-ggplot2
                             r-forestplot
                             r-dplyr
                             r-broom))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=chest")
    (synopsis "Change-in-Estimate Approach to Assess Confounding Effects")
    (description
     "Applies the change-in-effect estimate method to assess confounding effects in
medical and epidemiological research (Greenland & Pearce (2016)
<doi:10.1146/annurev-publhealth-031914-122559> ).  It starts with a crude model
including only the outcome and exposure variables.  At each of the subsequent
steps, one variable which creates the largest change among the remaining
variables is selected.  This process is repeated until all variables have been
entered into the model (Wang Z. Stata Journal 2007; 7, Number 2, pp.
183â196).  Currently, the chest package has functions for linear regression,
logistic regression, negative binomial regression, Cox proportional hazards
model and conditional logistic regression.")
    (license license:gpl2)))

(define-public r-chessgmoog
  (package
    (name "r-chessgmoog")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ChessGmooG" version))
       (sha256
        (base32 "00szz48avd3cnis5xbvgqj3fkvcy5w0v57i8pbd8ga4jl59308zg"))))
    (properties `((upstream-name . "ChessGmooG")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ChessGmooG")
    (synopsis "FIDE Chess Players Ratings for 2015 and 2020")
    (description
     "Datasets of the International Chess Federation's player ratings and country
information analysed in the book Antony Unwin (2024, ISBN:978-0367674007)
\"Getting (more out of) Graphics\".")
    (license license:gpl2+)))

(define-public r-chessboard
  (package
    (name "r-chessboard")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chessboard" version))
       (sha256
        (base32 "0w58zbiz9gw18ixcp3j23ys52xx5i4wrjhixiy4brc5b5h1i8mdi"))))
    (properties `((upstream-name . "chessboard")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-sf
                             r-rlang
                             r-magrittr
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/frbcesab/chessboard")
    (synopsis "Create Network Connections Based on Chess Moves")
    (description
     "This package provides functions to work with directed (asymmetric) and
undirected (symmetric) spatial networks.  It makes the creation of connectivity
matrices easier, i.e.  a binary matrix of dimension n x n, where n is the number
of nodes (sampling units) indicating the presence (1) or the absence (0) of an
edge (link) between pairs of nodes.  Different network objects can be produced
by chessboard': node list, neighbor list, edge list, connectivity matrix.  It
can also produce objects that will be used later in Moran's Eigenvector Maps
(Dray et al. (2006) <doi:10.1016/j.ecolmodel.2006.02.015>) and Asymetric
Eigenvector Maps (Blanchet et al. (2008) <doi:10.1016/j.ecolmodel.2008.04.001>),
methods available in the package adespatial (Dray et al. (2023)
<https://CRAN.R-project.org/package=adespatial>).  This work is part of the
FRB-CESAB working group Bridge
<https://www.fondationbiodiversite.fr/en/the-frb-in-action/programs-and-projects/le-cesab/bridge/>.")
    (license license:gpl2+)))

(define-public r-chess
  (package
    (name "r-chess")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chess" version))
       (sha256
        (base32 "0b0lz8r48bvksjnh385p1ni22hw1yvs6255pjbpj49ga9dwziin0"))))
    (properties `((upstream-name . "chess")))
    (build-system r-build-system)
    (propagated-inputs (list r-rsvg r-reticulate r-purrr r-magrittr r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/curso-r/chess")
    (synopsis "Read, Write, Create and Explore Chess Games")
    (description
     "This is an opinionated wrapper around the python-chess package.  It allows users
to read and write PGN files as well as create and explore game trees such as the
ones seen in chess books.")
    (license license:gpl3)))

(define-public r-cherryblossom
  (package
    (name "r-cherryblossom")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cherryblossom" version))
       (sha256
        (base32 "1fn0xi65y0w1gmyrjlh8lb2is34r2dc5bym0ynrgjv8h595nzhwp"))))
    (properties `((upstream-name . "cherryblossom")))
    (build-system r-build-system)
    (home-page "https://github.com/OpenIntroStat/cherryblossom")
    (synopsis "Cherry Blossom Run Race Results")
    (description
     "Race results of the Cherry Blossom Run, which is an annual road race that takes
place in Washington, DC.")
    (license license:gpl3)))

(define-public r-cherry
  (package
    (name "r-cherry")
    (version "0.6-14")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cherry" version))
       (sha256
        (base32 "03ipvd2ldzk7xsalkgcx0cyp9cp9b8qqjvz8nl0am412j3z9i5wg"))))
    (properties `((upstream-name . "cherry")))
    (build-system r-build-system)
    (propagated-inputs (list r-lpsolve r-hommel r-bitops))
    (home-page "https://cran.r-project.org/package=cherry")
    (synopsis "Multiple Testing Methods for Exploratory Research")
    (description
     "This package provides an alternative approach to multiple testing by calculating
a simultaneous upper confidence bounds for the number of true null hypotheses
among any subset of the hypotheses of interest, using the methods of Goeman and
Solari (2011) <doi:10.1214/11-STS356>.")
    (license license:gpl2+)))

(define-public r-chernoffdist
  (package
    (name "r-chernoffdist")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ChernoffDist" version))
       (sha256
        (base32 "0jyi0l29wqzrzgdlp3cbp8sdvi70rqzicy1wvb73anxa5r9pvjlf"))))
    (properties `((upstream-name . "ChernoffDist")))
    (build-system r-build-system)
    (propagated-inputs (list r-gsl))
    (home-page "https://cran.r-project.org/package=ChernoffDist")
    (synopsis "Chernoff's Distribution")
    (description
     "Computes Chernoff's distribution based on the method in Piet Groeneboom & Jon A
Wellner (2001) Computing Chernoff's Distribution, Journal of Computational and
Graphical Statistics, 10:2, 388-400, <doi:10.1198/10618600152627997>.
Chernoff's distribution is defined as the distribution of the maximizer of the
two-sided Brownian motion minus quadratic drift.  That is, Z = argmax
(B(t)-t^2).")
    (license license:gpl3)))

(define-public r-chemospecutils
  (package
    (name "r-chemospecutils")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ChemoSpecUtils" version))
       (sha256
        (base32 "1s62xf621prln3pv748kmif38fzxqh9vih63fpz783n7nzm94ka9"))))
    (properties `((upstream-name . "ChemoSpecUtils")))
    (build-system r-build-system)
    (propagated-inputs (list r-plotly r-magrittr r-ggrepel r-ggplot2
                             r-data-table))
    (home-page "https://github.com/bryanhanson/ChemoSpecUtils")
    (synopsis "Functions Supporting Packages ChemoSpec and ChemoSpec2D")
    (description
     "This package provides functions supporting the common needs of packages
@code{ChemoSpec} and @code{ChemoSpec2D}'.")
    (license license:gpl3)))

(define-public r-chemospec2d
  (package
    (name "r-chemospec2d")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ChemoSpec2D" version))
       (sha256
        (base32 "05k46fn2i0ipn14zignxvykr8018wxql26x2r5b479hbkg1rk5s4"))))
    (properties `((upstream-name . "ChemoSpec2D")))
    (build-system r-build-system)
    (propagated-inputs (list r-readjdx r-ggplot2 r-colorspace r-chemospecutils))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/bryanhanson/ChemoSpec2D")
    (synopsis "Exploratory Chemometrics for 2D Spectroscopy")
    (description
     "This package provides a collection of functions for exploratory chemometrics of
2D spectroscopic data sets such as COSY (correlated spectroscopy) and HSQC
(heteronuclear single quantum coherence) 2D NMR (nuclear magnetic resonance)
spectra. @code{ChemoSpec2D} deploys methods aimed primarily at classification of
samples and the identification of spectral features which are important in
distinguishing samples from each other.  Each 2D spectrum (a matrix) is treated
as the unit of observation, and thus the physical sample in the spectrometer
corresponds to the sample from a statistical perspective.  In addition to
chemometric tools, a few tools are provided for plotting 2D spectra, but these
are not intended to replace the functionality typically available on the
spectrometer. @code{ChemoSpec2D} takes many of its cues from @code{ChemoSpec}
and tries to create consistent graphical output and to be very user friendly.")
    (license license:gpl3)))

(define-public r-chemospec
  (package
    (name "r-chemospec")
    (version "6.1.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ChemoSpec" version))
       (sha256
        (base32 "0yxjhnbmvjf5kr0l3vq5j5s46c0498gfmrxm9czl7k082ibkznmg"))))
    (properties `((upstream-name . "ChemoSpec")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2
                             r-readjdx
                             r-plotly
                             r-patchwork
                             r-magrittr
                             r-ggplot2
                             r-chemospecutils))
    (native-inputs (list r-knitr))
    (home-page "https://bryanhanson.github.io/ChemoSpec/")
    (synopsis "Exploratory Chemometrics for Spectroscopy")
    (description
     "This package provides a collection of functions for top-down exploratory data
analysis of spectral data including nuclear magnetic resonance (NMR), infrared
(IR), Raman, X-ray fluorescence (XRF) and other similar types of spectroscopy.
Includes functions for plotting and inspecting spectra, peak alignment,
hierarchical cluster analysis (HCA), principal components analysis (PCA) and
model-based clustering.  Robust methods appropriate for this type of
high-dimensional data are available. @code{ChemoSpec} is designed for structured
experiments, such as metabolomics investigations, where the samples fall into
treatment and control groups.  Graphical output is formatted consistently for
publication quality plots. @code{ChemoSpec} is intended to be very user friendly
and to help you get usable results quickly.  A vignette covering typical
operations is available.")
    (license license:gpl3)))

(define-public r-chemodiv
  (package
    (name "r-chemodiv")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chemodiv" version))
       (sha256
        (base32 "07y8wvi5vh5apvg57pd2q5rqvpxm0h3v899n12r76gwvj8z1a28s"))))
    (properties `((upstream-name . "chemodiv")))
    (build-system r-build-system)
    (propagated-inputs (list r-webchem
                             r-vegan
                             r-tidyr
                             r-tidygraph
                             r-rlang
                             r-jsonlite
                             r-igraph
                             r-httr
                             r-hillr
                             r-gunifrac
                             r-gridextra
                             r-ggraph
                             r-ggplot2
                             r-ggdendro
                             r-fmcsr
                             r-curl
                             r-chemminer
                             r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/hpetren/chemodiv")
    (synopsis "Analysing Chemodiversity of Phytochemical Data")
    (description
     "Quantify and visualise various measures of chemical diversity and dissimilarity,
for phytochemical compounds and other sets of chemical composition data.
Importantly, these measures can incorporate biosynthetic and/or structural
properties of the chemical compounds, resulting in a more comprehensive
quantification of diversity and dissimilarity.  For details, see PetrÃ©n,
KÃ¶llner and Junker (2023) <doi:10.1111/nph.18685>.")
    (license license:gpl3+)))

(define-public r-chemist
  (package
    (name "r-chemist")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CHEMIST" version))
       (sha256
        (base32 "00alby5x01a2izmzk0ilkx5jgkwavsaj18w3kra444pib0ncrl92"))))
    (properties `((upstream-name . "CHEMIST")))
    (build-system r-build-system)
    (propagated-inputs (list r-xicor r-mass r-laplacesdemon))
    (home-page "https://cran.r-project.org/package=CHEMIST")
    (synopsis
     "Causal Inference with High-Dimensional Error-Prone Covariates and Misclassified Treatments")
    (description
     "We aim to deal with the average treatment effect (ATE), where the data are
subject to high-dimensionality and measurement error.  This package primarily
contains two functions, which are used to generate artificial data and estimate
ATE with high-dimensional and error-prone data accommodated.")
    (license license:gpl3)))

(define-public r-chemdeg
  (package
    (name "r-chemdeg")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chemdeg" version))
       (sha256
        (base32 "092d3nfkhgwy1wg5aqp6p1kd36q2s82vw6ymz0h10rqxsj84mx3f"))))
    (properties `((upstream-name . "chemdeg")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/migliomatte/chemdeg")
    (synopsis "Analysis of Chemical Degradation Kinetic Data")
    (description
     "This package provides a collection of functions that have been developed to
assist experimenter in modeling chemical degradation kinetic data.  The
selection of the appropriate degradation model and parameter estimation is
carried out automatically as far as possible and is driven by a rigorous
statistical interpretation of the results.  The package integrates already
available goodness-of-fit statistics for nonlinear models.  In addition it
allows data fitting with the nonlinear first-order multi-target (FOMT) model.")
    (license license:gpl3+)))

(define-public r-chemcal
  (package
    (name "r-chemcal")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chemCal" version))
       (sha256
        (base32 "0f0d0ljym745scnfdx0n0jp86g4r51gylcab3h7ykpaizgpah24r"))))
    (properties `((upstream-name . "chemCal")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://pkgdown.jrwb.de/chemCal/")
    (synopsis "Calibration Functions for Analytical Chemistry")
    (description
     "Simple functions for plotting linear calibration functions and estimating
standard errors for measurements according to the Handbook of Chemometrics and
Qualimetrics: Part A by Massart et al. (1997) There are also functions
estimating the limit of detection (LOD) and limit of quantification (LOQ).  The
functions work on model objects from - optionally weighted - linear regression
(lm) or robust linear regression ('rlm from the MASS package).")
    (license license:gpl2+)))

(define-public r-chem16s
  (package
    (name "r-chem16s")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chem16S" version))
       (sha256
        (base32 "0jjxirnjg966rbjv1lv889xpzjlspp0a3d41f90x8hqys6bbkln7"))))
    (properties `((upstream-name . "chem16S")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-reshape2
                             r-plyr
                             r-phyloseq
                             r-ggplot2
                             r-canprot))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jedick/chem16S")
    (synopsis "Chemical Metrics for Microbial Communities")
    (description
     "Combines taxonomic classifications of high-throughput 16S @code{rRNA} gene
sequences with reference proteomes of archaeal and bacterial taxa to generate
amino acid compositions of community reference proteomes.  Calculates chemical
metrics including carbon oxidation state ('Zc'), stoichiometric oxidation and
hydration state ('@code{nO2} and @code{nH2O}'), H/C, N/C, O/C, and S/C ratios,
grand average of hydropathicity ('GRAVY'), isoelectric point ('@code{pI}'),
protein length, and average molecular weight of amino acid residues.  Uses
precomputed reference proteomes for archaea and bacteria derived from the Genome
Taxonomy Database ('GTDB').  Also includes reference proteomes derived from the
NCBI Reference Sequence ('@code{RefSeq}') database and manual mapping from the
RDP Classifier training set to @code{RefSeq} taxonomy as described by Dick and
Tan (2023) <doi:10.1007/s00248-022-01988-9>.  Processes taxonomic
classifications in RDP Classifier format or OTU tables in phyloseq-class objects
from the Bioconductor package phyloseq'.")
    (license license:gpl3)))

(define-public r-chem-databases
  (package
    (name "r-chem-databases")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chem.databases" version))
       (sha256
        (base32 "1xficpzs0v85irkp9hsfbng4jdvlmmynpjkqj93r1hw702vg325x"))))
    (properties `((upstream-name . "chem.databases")))
    (build-system r-build-system)
    (home-page "https://gitlab.com/iembry/chem.databases")
    (synopsis "Collection of 3 Chemical Databases from Public Sources")
    (description
     "This package contains the Multi-Species Acute Toxicity Database (CAS & SMILES
columns only) [United States (US) Department of Health and Human Services (DHHS)
National Institutes of Health (NIH) National Cancer Institute (NCI),
\"Multi-Species Acute Toxicity Database\",
<https://cactus.nci.nih.gov/download/acute-toxicity-db/>] combined with the
Toxic Substances Control Act (TSCA) Inventory [United States Environmental
Protection Agency (US EPA), \"Toxic Substances Control Act (TSCA) Chemical
Substance Inventory\",
<https://www.epa.gov/tsca-inventory/how-access-tsca-inventory} and
<https://cdxapps.epa.gov/oms-substance-registry-services/substance-list-details/169>]
and the Agency for Toxic Substances and Disease Registry (ATSDR) Database
[United States (US) Department of Health and Human Services (DHHS) Centers for
Disease Control and Prevention (CDC)/Agency for Toxic Substances and Disease
Registry (ATSDR), \"Agency for Toxic Substances and Disease Registry (ATSDR)
Database\",
<https://cdxapps.epa.gov/oms-substance-registry-services/substance-list-details/105>]
in 2 data sets.  One data set has a focus on the latter 2 databases and one data
set focuses on the former database.  Also contains the collection of chemical
data from Wikipedia compiled in the US EPA @code{CompTox} Chemicals Dashboard
[United States Environmental Protection Agency (US EPA) / Wikimedia Foundation,
Inc. \"@code{CompTox} Chemicals Dashboard v2.2.1\",
<https://comptox.epa.gov/dashboard/chemical-lists/WIKIPEDIA>].")
    (license license:cc0)))

(define-public r-cheese
  (package
    (name "r-cheese")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cheese" version))
       (sha256
        (base32 "0g935mlf2hkbhd8cif8nmvg477if8sv7ga50ddb0cvghdaqjd183"))))
    (properties `((upstream-name . "cheese")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-knitr
                             r-kableextra
                             r-forcats
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://zajichek.github.io/cheese/")
    (synopsis "Tools for Working with Data During Statistical Analysis")
    (description
     "This package contains tools for working with data during statistical analysis,
promoting flexible, intuitive, and reproducible workflows.  There are functions
designated for specific statistical tasks such building a custom univariate
descriptive table, computing pairwise association statistics, etc.  These are
built on a collection of data manipulation tools designed for general use that
are motivated by the functional programming concept.")
    (license license:expat)))

(define-public r-cheem
  (package
    (name "r-cheem")
    (version "0.4.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cheem" version))
       (sha256
        (base32 "1b6gf2ax30rhpkmawvpar4cria4gkrcrzgyrvlrhcaialx40sjlz"))))
    (properties `((upstream-name . "cheem")))
    (build-system r-build-system)
    (propagated-inputs (list r-spinifex
                             r-shinythemes
                             r-shinycssloaders
                             r-shiny
                             r-plotly
                             r-magrittr
                             r-ggplot2
                             r-dt
                             r-conflicted))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/nspyrison/cheem/")
    (synopsis "Interactively Explore Local Explanations with the Radial Tour")
    (description
     "Given a non-linear model, calculate the local explanation.  We purpose view the
data space, explanation space, and model residuals as ensemble graphic
interactive on a shiny application.  After an observation of interest is
identified, the normalized variable importance of the local explanation is used
as a 1D projection basis.  The support of the local explanation is then explored
by changing the basis with the use of the radial tour
<doi:10.32614/RJ-2020-027>; <doi:10.1080/10618600.1997.10474754>.")
    (license license:expat)))

(define-public r-cheddar
  (package
    (name "r-cheddar")
    (version "0.1-639")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cheddar" version))
       (sha256
        (base32 "0fiq03irgi1niqlc45vkqvn8dlqg6354i6f4gv70pzjn6l74a7nf"))))
    (properties `((upstream-name . "cheddar")))
    (build-system r-build-system)
    (home-page "https://github.com/quicklizard99/cheddar/")
    (synopsis "Analysis and Visualisation of Ecological Communities")
    (description
     "This package provides a flexible, extendable representation of an ecological
community and a range of functions for analysis and visualisation, focusing on
food web, body mass and numerical abundance data.  Allows inter-web comparisons
such as examining changes in community structure over environmental, temporal or
spatial gradients.")
    (license license:bsd-2)))

(define-public r-checkthat
  (package
    (name "r-checkthat")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "checkthat" version))
       (sha256
        (base32 "1l88cn4q0475fizblypxjhrdrkqmc4a7ln3agz0cmsmp8z6j4gjd"))))
    (properties `((upstream-name . "checkthat")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-purrr r-lifecycle r-glue r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/iancero/checkthat")
    (synopsis "Intuitive Unit Testing Tools for Data Manipulation")
    (description
     "This package provides a lightweight data validation and testing toolkit for R.
Its guiding philosophy is that adding code-based data checks to users existing
workflow should be both quick and intuitive.  The suite of functions included
therefore mirror the common data checks many users already perform by hand or by
eye.  Additionally, the checkthat package is optimized to work within tidyverse
data manipulation pipelines.")
    (license license:expat)))

(define-public r-checkpoint
  (package
    (name "r-checkpoint")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "checkpoint" version))
       (sha256
        (base32 "1987vn13b5j914vkzwbn7q1138b0xsjs55x5b2090kjk6kc900x8"))))
    (properties `((upstream-name . "checkpoint")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml r-withr r-pkgdepends r-jsonlite))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/RevolutionAnalytics/checkpoint")
    (synopsis
     "Install Packages from Snapshots on the Checkpoint Server for Reproducibility")
    (description
     "The goal of checkpoint is to solve the problem of package reproducibility in R.
Specifically, checkpoint allows you to install packages as they existed on CRAN
on a specific snapshot date as if you had a CRAN time machine.  To achieve
reproducibility, the checkpoint() function installs the packages required or
called by your project and scripts to a local library exactly as they existed at
the specified point in time.  Only those packages are available to your project,
thereby avoiding any package updates that came later and may have altered your
results.  In this way, anyone using checkpoint's checkpoint() can ensure the
reproducibility of your scripts or projects at any time.  To create the snapshot
archives, once a day (at midnight UTC) Microsoft refreshes the Austria CRAN
mirror on the \"Microsoft R Archived Network\" server
(<https://mran.microsoft.com/>).  Immediately after completion of the rsync
mirror process, the process takes a snapshot, thus creating the archive.
Snapshot archives exist starting from 2014-09-17.")
    (license license:gpl2)))

(define-public r-checkluhn
  (package
    (name "r-checkluhn")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "checkLuhn" version))
       (sha256
        (base32 "1s1ix5n98bcbzcvrz5h19sk9pchdvrhpy3ppmw96ys8vylzm58mv"))))
    (properties `((upstream-name . "checkLuhn")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-dplyr))
    (home-page "https://github.com/adamjdeacon/checkLuhn")
    (synopsis "Checks if a Number is Valid Using the Luhn Algorithm")
    (description
     "Confirms if the number is Luhn compliant.  Can check if credit card, IMEI number
or any other Luhn based number is correct.  For more info see:
<https://en.wikipedia.org/wiki/Luhn_algorithm>.")
    (license license:gpl2)))

(define-public r-checkhelper
  (package
    (name "r-checkhelper")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "checkhelper" version))
       (sha256
        (base32 "0lhrhygma1n98f2k7ly29ildxl5zg5qwrlflrhf19xdi9qmzzvmz"))))
    (properties `((upstream-name . "checkhelper")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr
                             r-whisker
                             r-stringr
                             r-roxygen2
                             r-rcmdcheck
                             r-purrr
                             r-pkgbuild
                             r-magrittr
                             r-lifecycle
                             r-glue
                             r-dplyr
                             r-devtools
                             r-desc
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://thinkr-open.github.io/checkhelper/")
    (synopsis "Deal with Check Outputs")
    (description
     "Deal with packages check outputs and reduce the risk of rejection by CRAN by
following policies.")
    (license license:expat)))

(define-public r-checkglobals
  (package
    (name "r-checkglobals")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "checkglobals" version))
       (sha256
        (base32 "1jcpga1bx8cx6fdf1ddjkfk7ap5dvm03g5xkni7as5bisggsp4jv"))))
    (properties `((upstream-name . "checkglobals")))
    (build-system r-build-system)
    (home-page "https://jorischau.github.io/checkglobals/")
    (synopsis "Static Analysis of R-Code Dependencies")
    (description
     "This package provides a minimal R-package to approximately detect global and
imported functions or variables from R-source code or R-packages by static code
analysis.")
    (license license:expat)))

(define-public r-checker
  (package
    (name "r-checker")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "checker" version))
       (sha256
        (base32 "1n9gwgbkr2h6gna7nj18nv8bj2f9i2zyp407f4c4vj6f1pzj00ik"))))
    (properties `((upstream-name . "checker")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml r-rstudioapi r-cli))
    (home-page "https://github.com/richardjtelford/checker/")
    (synopsis "Checks 'R' Configuration Set Up Correctly Before Class")
    (description
     "Checks that students have the correct version of R', R packages, RStudio and
other dependencies installed, and that the recommended RStudio configuration has
been applied.")
    (license license:expat)))

(define-public r-checked
  (package
    (name "r-checked")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "checked" version))
       (sha256
        (base32 "0yzg8y236w72694raz0x7ic70a0fzn9c3pl2x868rfyvq3ivsv7d"))))
    (properties `((upstream-name . "checked")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcmdcheck
                             r-r6
                             r-jsonlite
                             r-igraph
                             r-cli
                             r-callr))
    (home-page "https://github.com/Genentech/checked")
    (synopsis "Systematically Run R CMD Checks")
    (description
     "Systematically Run R checks against multiple packages.  Checks are run in
parallel with strategies to minimize dependency installation.  Provides out of
the box interface for running reverse dependency check.")
    (license license:expat)))

(define-public r-checkdown
  (package
    (name "r-checkdown")
    (version "0.0.12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "checkdown" version))
       (sha256
        (base32 "0yn7casmsqcrc31b9g06sjdrwxjyw5cbg3pwwdn5s7gaal881rh1"))))
    (properties `((upstream-name . "checkdown")))
    (build-system r-build-system)
    (propagated-inputs (list r-markdown r-htmltools r-glue))
    (native-inputs (list r-knitr))
    (home-page "https://agricolamz.github.io/checkdown/")
    (synopsis "Check-Fields and Check-Boxes for 'rmarkdown'")
    (description
     "This package creates auto-grading check-fields and check-boxes for rmarkdown or
quarto HTML. It can be used in class, when teacher share materials and tasks, so
students can solve some problems and check their work.  In contrast to the
learnr package, the checkdown package works serverlessly without shiny'.")
    (license license:gpl2+)))

(define-public r-checkdigit
  (package
    (name "r-checkdigit")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CheckDigit" version))
       (sha256
        (base32 "19apm7hr1k693w2ybv7vmaw5mxnhdjggpnr4m8phyvv8by345rxs"))))
    (properties `((upstream-name . "CheckDigit")))
    (build-system r-build-system)
    (home-page "https://fascinatingfingers.gitlab.io/checkdigit")
    (synopsis "Calculate and Verify Check Digits")
    (description
     "Check digits are used like file hashes to verify that a number has been
transcribed accurately.  The functions provided by this package help to
calculate and verify check digits according to various algorithms.")
    (license license:gpl3+)))

(define-public r-checkarg
  (package
    (name "r-checkarg")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "checkarg" version))
       (sha256
        (base32 "0rkdjs2c4yx9laqgayxz57bwxhwgdh6ndrr4i3b1kh31lcmk1xc6"))))
    (properties `((upstream-name . "checkarg")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=checkarg")
    (synopsis "Check the Basic Validity of a (Function) Argument")
    (description
     "Utility functions that allow checking the basic validity of a function argument
or any other value, including generating an error and assigning a default in a
single line of code.  The main purpose of the package is to provide simple and
easily readable argument checking to improve code robustness.")
    (license license:gpl2+)))

(define-public r-cheatsheet
  (package
    (name "r-cheatsheet")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cheatsheet" version))
       (sha256
        (base32 "0nhyz354hxnqbs3iwvaisssr4ciq6vary3ldkm8yanpdyw0p1k27"))))
    (properties `((upstream-name . "cheatsheet")))
    (build-system r-build-system)
    (propagated-inputs (list r-rstudioapi
                             r-purrr
                             r-magrittr
                             r-git2r
                             r-fs
                             r-crayon
                             r-cli))
    (home-page "https://bradlindblad.github.io/cheatsheet/")
    (synopsis "Download R Cheat Sheets Locally")
    (description
     "This package provides a simple package to grab cheat sheets and save them to
your local computer.")
    (license license:expat)))

(define-public r-cheapr
  (package
    (name "r-cheapr")
    (version "0.9.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cheapr" version))
       (sha256
        (base32 "0354a3yn56a6m4f0zf9hxv0cany3aivh4d265jh7b6zyk498h26y"))))
    (properties `((upstream-name . "cheapr")))
    (build-system r-build-system)
    (propagated-inputs (list r-cpp11 r-collapse))
    (home-page "https://cran.r-project.org/package=cheapr")
    (synopsis "Simple Functions to Save Time and Memory")
    (description
     "Fast and memory-efficient (or cheap') tools to facilitate efficient programming,
saving time and memory.  It aims to provide cheaper alternatives to common base
R functions, as well as some additional functions.")
    (license license:expat)))

(define-public r-chattr
  (package
    (name "r-chattr")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chattr" version))
       (sha256
        (base32 "1jvzk62h5dgshqadin3n55600yy965xgssb6akywixyik8qipscl"))))
    (properties `((upstream-name . "chattr")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-shiny
                             r-rstudioapi
                             r-rlang
                             r-purrr
                             r-processx
                             r-lifecycle
                             r-jsonlite
                             r-httr2
                             r-glue
                             r-fs
                             r-config
                             r-clipr
                             r-cli
                             r-callr
                             r-bslib))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mlverse/chattr")
    (synopsis "Interact with Large Language Models in 'RStudio'")
    (description
     "Enables user interactivity with large-language models ('LLM') inside the RStudio
integrated development environment (IDE).  The user can interact with the model
using the shiny app included in this package, or directly in the R console.  It
comes with back-ends for @code{OpenAI}', @code{GitHub} Copilot', and
@code{LlamaGPT}'.")
    (license license:expat)))

(define-public r-chatgpt
  (package
    (name "r-chatgpt")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chatgpt" version))
       (sha256
        (base32 "1a71rzim5x40lnb7pc5n0b9j56kg96cjw7x4liqkbn84n61db6ff"))))
    (properties `((upstream-name . "chatgpt")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny
                             r-rstudioapi
                             r-miniui
                             r-jsonlite
                             r-httr
                             r-clipr))
    (home-page "https://github.com/jcrodriguez1989/chatgpt")
    (synopsis "Interface to 'ChatGPT' from R")
    (description
     "@code{OpenAI's} @code{ChatGPT} <https://chat.openai.com/> coding assistant for
RStudio'.  A set of functions and RStudio addins that aim to help the R
developer in tedious coding tasks.")
    (license license:gpl3+)))

(define-public r-chatai4r
  (package
    (name "r-chatai4r")
    (version "0.2.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chatAI4R" version))
       (sha256
        (base32 "0iil1bl6l89lckxh4bdxjnjnww2h8q4gd83b29rbw4xfa1mlb8rb"))))
    (properties `((upstream-name . "chatAI4R")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-rvest
                             r-rstudioapi
                             r-pdftools
                             r-jsonlite
                             r-igraph
                             r-httr
                             r-future
                             r-deeprstudio
                             r-crayon
                             r-clipr
                             r-assertthat))
    (home-page "https://kumes.github.io/chatAI4R/")
    (synopsis "Chat-Based Interactive Artificial Intelligence for R")
    (description
     "The Large Language Model (LLM) represents a groundbreaking advancement in data
science and programming, and also allows us to extend the world of R. A seamless
interface for integrating the @code{OpenAI} Web APIs into R is provided in this
package.  This package leverages LLM-based AI techniques, enabling efficient
knowledge discovery and data analysis (see @code{OpenAI} Web APIs details
<https://openai.com/blog/openai-api>).  The previous functions such as seamless
translation and image generation have been moved to other packages
@code{deepRstudio} and @code{stableDiffusion4R}'.")
    (license license:artistic2.0)))

(define-public r-chartql
  (package
    (name "r-chartql")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chartql" version))
       (sha256
        (base32 "108csn7q8qrjhiss54f5bliv3av7psq7kfryspajbdb6wm9ciz3p"))))
    (properties `((upstream-name . "chartql")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-ggplot2))
    (home-page "https://github.com/rmsyed/chartql")
    (synopsis "Simplified Language for Plots and Charts")
    (description
     "This package provides a very simple syntax for the user to generate custom
plot(s) without having to remember complicated ggplot2 syntax.  The chartql
package uses ggplot2 and manages all the syntax complexities internally.  As an
example, to generate a bar chart of company sales faceted by product category
further faceted by season of the year, we simply write: \"CHART bar X category,
season Y sales\".")
    (license license:gpl3)))

(define-public r-charlesschwabapi
  (package
    (name "r-charlesschwabapi")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "charlesschwabapi" version))
       (sha256
        (base32 "1qqii54np02df2livqr9ajj71zrws9njfbx7ad8b0wh9zbz2kdy4"))))
    (properties `((upstream-name . "charlesschwabapi")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-purrr
                             r-openssl
                             r-lubridate
                             r-httr
                             r-dplyr
                             r-anytime))
    (home-page "https://cran.r-project.org/package=charlesschwabapi")
    (synopsis
     "Wrapper Functions Around 'Charles Schwab Individual Trader API'")
    (description
     "For those wishing to interact with the Charles Schwab Individual Trader API
(<https://developer.schwab.com/products/trader-api--individual>) with R in a
simplified manner, this package offers wrapper functions around authentication
and the available API calls to streamline the process.")
    (license license:expat)))

(define-public r-charlatan
  (package
    (name "r-charlatan")
    (version "0.6.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "charlatan" version))
       (sha256
        (base32 "19vrav1yhbfag2j2fc9hbrjhv79w0gxfzaml66b374q76cjji1nz"))))
    (properties `((upstream-name . "charlatan")))
    (build-system r-build-system)
    (propagated-inputs (list r-whisker r-tibble r-r6))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/charlatan/")
    (synopsis "Make Fake Data")
    (description
     "Make fake data that looks realistic, supporting addresses, person names, dates,
times, colors, coordinates, currencies, digital object identifiers ('DOIs'),
jobs, phone numbers, DNA sequences, doubles and integers from distributions and
within a range.")
    (license license:expat)))

(define-public r-charcuterie
  (package
    (name "r-charcuterie")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "charcuterie" version))
       (sha256
        (base32 "12yw4p3ffdl7pzyxqyg1gmwd387m5wxaj9vq4ix6b2cmfvmzsc1c"))))
    (properties `((upstream-name . "charcuterie")))
    (build-system r-build-system)
    (propagated-inputs (list r-generics))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jonocarroll/charcuterie")
    (synopsis "Handle Strings as Vectors of Characters")
    (description
     "This package creates a new chars class which looks like a string but is actually
a vector of individual characters, making strings iterable.  This class enables
vector operations on strings such as reverse, sort, head, and set operations.")
    (license license:expat)))

(define-public r-chaosgame
  (package
    (name "r-chaosgame")
    (version "1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ChaosGame" version))
       (sha256
        (base32 "06d2jm8b3l242yqgbfsr1cclph0l8xdxqfq7xvbghsavzk3lf367"))))
    (properties `((upstream-name . "ChaosGame")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgl
                             r-rcolorbrewer
                             r-plot3d
                             r-gridextra
                             r-ggplot2
                             r-colorramps))
    (home-page "https://cran.r-project.org/package=ChaosGame")
    (synopsis "Chaos Game")
    (description
     "The main objective of the package is to enter a word of at least two letters
based on which an Iterated Function System with Probabilities is constructed,
and a two-dimensional fractal containing the chosen word infinitely often is
generated via the Chaos Game.  Additionally, the package allows to project the
two-dimensional fractal on several three-dimensional surfaces and to transform
the fractal into another fractal with uniform marginals.")
    (license license:gpl2)))

(define-public r-chaos01
  (package
    (name "r-chaos01")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Chaos01" version))
       (sha256
        (base32 "1wk70l1y0yzbjcjp0r334l1q3hzki0vzn6wbza97mq9pz8wp050r"))))
    (properties `((upstream-name . "Chaos01")))
    (build-system r-build-system)
    (home-page "https://code.it4i.cz/ADAS/Chaos01")
    (synopsis "0-1 Test for Chaos")
    (description
     "Computes and visualize the results of the 0-1 test for chaos proposed by
Gottwald and Melbourne (2004) <DOI:10.1137/080718851>.  The algorithm is
available in parallel for the independent values of parameter c.  Additionally,
fast RQA is added to distinguish chaos from noise.")
    (license license:gpl3)))

(define-public r-chantrics
  (package
    (name "r-chantrics")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chantrics" version))
       (sha256
        (base32 "0123mbdr4bkkp8w9w15bg9qxkbpd6nyp602fw690zsy1dyimm78k"))))
    (properties `((upstream-name . "chantrics")))
    (build-system r-build-system)
    (propagated-inputs (list r-sandwich
                             r-rlang
                             r-purrr
                             r-progress
                             r-lmtest
                             r-chandwich
                             r-aer))
    (native-inputs (list r-knitr))
    (home-page "https://chantrics.theobruckbauer.eu")
    (synopsis "Loglikelihood Adjustments for Econometric Models")
    (description
     "Adjusts the loglikelihood of common econometric models for clustered data based
on the estimation process suggested in Chandler and Bate (2007)
<doi:10.1093/biomet/asm015>, using the chandwich package
<https://cran.r-project.org/package=chandwich>, and provides convenience
functions for inference on the adjusted models.")
    (license (license:fsdg-compatible "EUPL (>= 1.2)"))))

(define-public r-channelattributionapp
  (package
    (name "r-channelattributionapp")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ChannelAttributionApp" version))
       (sha256
        (base32 "0n9g8wwvc8p5clypl7z23w8fs6d0c47bblijwd4pjwy26bcb4m8h"))))
    (properties `((upstream-name . "ChannelAttributionApp")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-ggplot2 r-data-table
                             r-channelattribution))
    (home-page "http://www.channelattribution.net")
    (synopsis "Shiny Web Application for the Multichannel Attribution Problem")
    (description
     "Shiny Web Application for the Multichannel Attribution Problem.  It is a
user-friendly graphical interface for package @code{ChannelAttribution}'.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-channelattribution
  (package
    (name "r-channelattribution")
    (version "2.0.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ChannelAttribution" version))
       (sha256
        (base32 "0ak7s5l990kfkf5bzggqplss5pd06rfalghk1rzy92js1n1qxrs7"))))
    (properties `((upstream-name . "ChannelAttribution")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "https://channelattribution.io")
    (synopsis "Markov Model for Online Multi-Channel Attribution")
    (description
     "Advertisers use a variety of online marketing channels to reach consumers and
they want to know the degree each channel contributes to their marketing
success.  This is called online multi-channel attribution problem.  This package
contains a probabilistic algorithm for the attribution problem.  The model uses
a k-order Markov representation to identify structural correlations in the
customer journey data.  The package also contains three heuristic algorithms
(first-touch, last-touch and linear-touch approach) for the same problem.  The
algorithms are implemented in C++.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-changes
  (package
    (name "r-changes")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "changeS" version))
       (sha256
        (base32 "1igd2qvs5y2g63byvwn0djbgc5lqi9zx7a0g2dkda1q6snl65yi7"))))
    (properties `((upstream-name . "changeS")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-nls-multstart r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/matloff/changeS")
    (synopsis "S-Curve Fit for Changepoint Analysis")
    (description
     "Estimation of changepoints using an \"S-curve\" approximation.  Formation of
confidence intervals for changepoint locations and magnitudes.  Both abrupt and
gradual changes can be modeled.")
    (license license:gpl2+)))

(define-public r-changer
  (package
    (name "r-changer")
    (version "0.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "changer" version))
       (sha256
        (base32 "02pn96gx98h00kl08zfza9mdxq1ra6f9l5mgfnrvyrjhz3a5d2kh"))))
    (properties `((upstream-name . "changer")))
    (build-system r-build-system)
    (propagated-inputs (list r-git2r r-devtools r-available))
    (home-page "https://github.com/helske/changer")
    (synopsis "Change R Package Name")
    (description
     "Changing the name of an existing R package is annoying but common task
especially in the early stages of package development.  This package (mostly)
automates this task.")
    (license license:gpl2+)))

(define-public r-changepointtests
  (package
    (name "r-changepointtests")
    (version "0.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "changepointTests" version))
       (sha256
        (base32 "0pq689xwkaqx8kqpdhfxxr9jwy3kdj82sg5182w8kmpd7x405k56"))))
    (properties `((upstream-name . "changepointTests")))
    (build-system r-build-system)
    (propagated-inputs (list r-foreach r-doparallel))
    (home-page "https://cran.r-project.org/package=changepointTests")
    (synopsis "Change Point Tests for Joint Distributions and Copulas")
    (description
     "Change point tests for joint distributions and copulas using pseudo-observations
with multipliers or bootstrap.  The processes used here have been defined in
Bucher, Kojadinovic, Rohmer & Segers <doi:10.1016/j.jmva.2014.07.012> and Nasri
& Remillard <doi:10.1016/j.jmva.2019.03.002>.")
    (license license:gpl3)))

(define-public r-changepointtesting
  (package
    (name "r-changepointtesting")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ChangepointTesting" version))
       (sha256
        (base32 "0gasqf39hhrd2pg2rq4a2aaxwi3syjvmgdiss42wdwb47dww8wil"))))
    (properties `((upstream-name . "ChangepointTesting")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ChangepointTesting")
    (synopsis "Change Point Estimation for Clustered Signals")
    (description
     "This package provides a multiple testing procedure for clustered alternative
hypotheses.  It is assumed that the p-values under the null hypotheses follow
U(0,1) and that the distributions of p-values from the alternative hypotheses
are stochastically smaller than U(0,1).  By aggregating information, this method
is more sensitive to detecting signals of low magnitude than standard methods.
Additionally, sporadic small p-values appearing within a null hypotheses
sequence are avoided by averaging on the neighboring p-values.")
    (license license:gpl2)))

(define-public r-changepointtaylor
  (package
    (name "r-changepointtaylor")
    (version "0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ChangePointTaylor" version))
       (sha256
        (base32 "17gyiwvg41zc31kmhv55037dm416vwlkrmrwswilbqksqq1fzk06"))))
    (properties `((upstream-name . "ChangePointTaylor")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rlang
                             r-rcpp
                             r-purrr
                             r-magrittr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ChangePointTaylor")
    (synopsis "Identify Changes in Mean")
    (description
     "This package provides a basic implementation of the change in mean detection
method outlined in: Taylor, Wayne A. (2000)
<https://variation.com/wp-content/uploads/change-point-analyzer/change-point-analysis-a-powerful-new-tool-for-detecting-changes.pdf>.
 The package recursively uses the mean-squared error change point calculation to
identify candidate change points.  The candidate change points are then
re-estimated and Taylor's backwards elimination process is then employed to come
up with a final set of change points.  Many of the underlying functions are
written in C++ for improved performance.")
    (license license:gpl2+)))

(define-public r-changepointsvar
  (package
    (name "r-changepointsvar")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "changepointsVar" version))
       (sha256
        (base32 "0a5g0bafvb1rbw31y8b8plwhxw5svlh4qfjwvdzafbcrp3rn1cs4"))))
    (properties `((upstream-name . "changepointsVar")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-lars))
    (home-page "https://cran.r-project.org/package=changepointsVar")
    (synopsis "Change-Points Detections for Changes in Variance")
    (description
     "Detection of change-points for variance of heteroscedastic Gaussian variables
with piecewise constant variance function.  Adelfio, G. (2012), Change-point
detection for variance piecewise constant models, Communications in Statistics,
Simulation and Computation, 41:4, 437-448, <doi:10.1080/03610918.2011.592248>.")
    (license license:gpl2)))

(define-public r-changepoints
  (package
    (name "r-changepoints")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "changepoints" version))
       (sha256
        (base32 "1wckqnwvjl56ajz09niiyb4v61gnh1xzasdkxj8hsnfmv24y7dvk"))))
    (properties `((upstream-name . "changepoints")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo
                             r-rcpp
                             r-mass
                             r-ks
                             r-glmnet
                             r-gglasso
                             r-data-tree))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/HaotianXu/changepoints")
    (synopsis "Collection of Change-Point Detection Methods")
    (description
     "This package performs a series of offline and/or online change-point detection
algorithms for 1) univariate mean: <doi:10.1214/20-EJS1710>,
<@code{arXiv:2006.03283>}; 2) univariate polynomials: <doi:10.1214/21-EJS1963>;
3) univariate and multivariate nonparametric settings: <doi:10.1214/21-EJS1809>,
<doi:10.1109/TIT.2021.3130330>; 4) high-dimensional covariances:
<doi:10.3150/20-BEJ1249>; 5) high-dimensional networks with and without missing
values: <doi:10.1214/20-AOS1953>, <@code{arXiv:2101.05477>},
<@code{arXiv:2110.06450>}; 6) high-dimensional linear regression models:
<@code{arXiv:2010.10410>}, <@code{arXiv:2207.12453>}; 7) high-dimensional vector
autoregressive models: <@code{arXiv:1909.06359>}; 8) high-dimensional self
exciting point processes: <@code{arXiv:2006.03572>}; 9) dependent dynamic
nonparametric random dot product graphs: <@code{arXiv:1911.07494>}; 10)
univariate mean against adversarial attacks: <@code{arXiv:2105.10417>}.")
    (license license:gpl3+)))

(define-public r-changepoint-np
  (package
    (name "r-changepoint-np")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "changepoint.np" version))
       (sha256
        (base32 "1kyj1z0mmbk1i71d5xxw8h3468afvwlqma659yjck3y5dszb1vn9"))))
    (properties `((upstream-name . "changepoint.np")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-rdpack r-changepoint))
    (home-page "https://cran.r-project.org/package=changepoint.np")
    (synopsis "Methods for Nonparametric Changepoint Detection")
    (description
     "This package implements the multiple changepoint algorithm PELT with a
nonparametric cost function based on the empirical distribution of the data.
This package extends the changepoint package (see Killick, R and Eckley, I
(2014) <doi:10.18637/jss.v058.i03> ).")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-changepoint-influence
  (package
    (name "r-changepoint-influence")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "changepoint.influence" version))
       (sha256
        (base32 "0mlr1k7mbi2v4vd0ry4if5j6x638znj0kbfvwr20p6m6wmd0ln0a"))))
    (properties `((upstream-name . "changepoint.influence")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape r-gridextra r-ggplot2 r-data-table
                             r-changepoint))
    (home-page "https://github.com/rkillick/changepoint.influence/")
    (synopsis
     "Package to Calculate the Influence of the Data on a Changepoint Segmentation")
    (description
     "Allows users to input their data, segmentation and function used for the
segmentation (and additional arguments) and the package calculates the influence
of the data on the changepoint locations, see Wilms et al. (2022)
<doi:10.1080/10618600.2021.2000873>.  Currently this can only be used with the
changepoint package functions to identify changes, but we plan to extend this.
There are options for different types of graphics to assess the influence.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-changepoint-geo
  (package
    (name "r-changepoint-geo")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "changepoint.geo" version))
       (sha256
        (base32 "0zwj4wwwh99diz0vn5f06ygs93afahnn5glvab2k7wgk2qyf5jgq"))))
    (properties `((upstream-name . "changepoint.geo")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-ggplot2 r-changepoint-np r-changepoint))
    (home-page "https://github.com/grundy95/changepoint.geo/")
    (synopsis "Geometrically Inspired Multivariate Changepoint Detection")
    (description
     "This package implements the high-dimensional changepoint detection method
@code{GeomCP} and the related mappings used for changepoint detection.  These
methods view the changepoint problem from a geometrical viewpoint and aim to
extract relevant geometrical features in order to detect changepoints.  The
geomcp() function should be your first point of call.  References: Grundy et al.
(2020) <doi:10.1007/s11222-020-09940-y>.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-chandwich
  (package
    (name "r-chandwich")
    (version "1.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chandwich" version))
       (sha256
        (base32 "03qcqw9xx8mw7hymjl3ym6l1adgw5ssv0pmcmdv2hk230mx2fsld"))))
    (properties `((upstream-name . "chandwich")))
    (build-system r-build-system)
    (propagated-inputs (list r-numderiv))
    (native-inputs (list r-knitr))
    (home-page "https://paulnorthrop.github.io/chandwich/")
    (synopsis "Chandler-Bate Sandwich Loglikelihood Adjustment")
    (description
     "This package performs adjustments of a user-supplied independence loglikelihood
function using a robust sandwich estimator of the parameter covariance matrix,
based on the methodology in Chandler and Bate (2007)
<doi:10.1093/biomet/asm015>.  This can be used for cluster correlated data when
interest lies in the parameters of the marginal distributions or for performing
inferences that are robust to certain types of model misspecification.
Functions for profiling the adjusted loglikelihoods are also provided, as are
functions for calculating and plotting confidence intervals, for single model
parameters, and confidence regions, for pairs of model parameters.  Nested
models can be compared using an adjusted likelihood ratio test.")
    (license license:gpl2+)))

(define-public r-chainladder
  (package
    (name "r-chainladder")
    (version "0.2.19")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ChainLadder" version))
       (sha256
        (base32 "0i5mif26m4kdii7rx7dvsk98d53qyrzdd2x7x9idqsrs7cl5srm9"))))
    (properties `((upstream-name . "ChainLadder")))
    (build-system r-build-system)
    (propagated-inputs (list r-tweedie
                             r-systemfit
                             r-statmod
                             r-matrix
                             r-mass
                             r-lattice
                             r-ggplot2
                             r-cplm
                             r-actuar))
    (native-inputs (list r-knitr))
    (home-page "https://mages.github.io/ChainLadder/")
    (synopsis
     "Statistical Methods and Models for Claims Reserving in General Insurance")
    (description
     "Various statistical methods and models which are typically used for the
estimation of outstanding claims reserves in general insurance, including those
to estimate the claims development result as required under Solvency II.")
    (license license:gpl2+)))

(define-public r-chainbinomial
  (package
    (name "r-chainbinomial")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "chainbinomial" version))
       (sha256
        (base32 "1qs1bcql1xcb1qh35spr4j0vk6gwwjc3c0sb1y6vy0vh9z5mz6p8"))))
    (properties `((upstream-name . "chainbinomial")))
    (build-system r-build-system)
    (propagated-inputs (list r-generics))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=chainbinomial")
    (synopsis "Chain Binomial Models for Analysis of Infectious Disease Data")
    (description
     "This package implements the chain binomial model for analysis of infectious
disease data.  Contains functions for calculating probabilities of the final
size of infectious disease outbreaks using the method from D. Ludwig (1975)
<doi:10.1016/0025-5564(75)90119-4> and for outbreaks that are not concluded,
from LindstrÃ¸m et al. (2024) <doi:10.48550/@code{arXiv.2403.03948>}.  The
package also contains methods for estimation and regression analysis of
secondary attack rates.")
    (license license:gpl3)))

(define-public r-ch
  (package
    (name "r-ch")
    (version "0.1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ch" version))
       (sha256
        (base32 "1ryh2xr1ix4qznq1svi4gdr4qy6v6rg597z2zl6zw32s2xq6ssx6"))))
    (properties `((upstream-name . "ch")))
    (build-system r-build-system)
    (propagated-inputs (list r-ryacas
                             r-pracma
                             r-polynom
                             r-mass
                             r-magrittr
                             r-ggplot2
                             r-crayon
                             r-clipr))
    (home-page "https://github.com/tsiamut/ch")
    (synopsis "About some Small Functions")
    (description
     "The solution to some common problems is proposed, as well as a summary of some
small functions.  In particular, it provides a useful function for some problems
in chemistry.  For example, monoa(), monob() and mono() function can be used to
calculate The @code{pH} of weak acid/base.  The ggpng() function can save the
PNG format with transparent background.  The period_table() function will show
the periodic table.  Also the show_ruler() function will show the ruler.  The
show_color() function is funny and easier to show colors.  I also provide the
symb() function to generate multiple symbols at once.  The csv2vcf() function
provides an easy method to generate a file.  The sym2poly() and sym2coef()
function can extract coefficients from polynomials.")
    (license license:artistic2.0)))

(define-public r-cgwtools
  (package
    (name "r-cgwtools")
    (version "4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cgwtools" version))
       (sha256
        (base32 "0nw9zmbx3d7jqvw0yjqnqxnk16fay5pg4hws6qk341ipixwfmcbf"))))
    (properties `((upstream-name . "cgwtools")))
    (build-system r-build-system)
    (propagated-inputs (list r-gmp))
    (home-page "https://cran.r-project.org/package=cgwtools")
    (synopsis "Miscellaneous Tools")
    (description
     "This package provides functions for performing quick observations or evaluations
of data, including a variety of ways to list objects by size, class, etc.  The
functions seqle and reverse.seqle mimic the base rle but can search for linear
sequences.  The function splatnd allows the user to generate zero-argument
commands without the need for @code{makeActiveBinding} .  Functions provided to
convert from any base to any other base, and to find the n-th greatest max or
n-th least min.  In addition, functions which mimic Unix shell commands,
including head', tail ,'pushd ,and popd'.  Various other goodies included as
well.")
    (license license:lgpl3)))

(define-public r-cgr
  (package
    (name "r-cgr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CGR" version))
       (sha256
        (base32 "03kgbhxjcsid5s61kq4zc4612ammd17k1w4m8f2p1xq2ib1mykqd"))))
    (properties `((upstream-name . "CGR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CGR")
    (synopsis
     "Compound Growth Rate for Capturing the Growth Rate Over the Period")
    (description
     "The compound growth rate indicates the percentage change of a specific variable
over a defined period.  It is calculated using non-linear models, particularly
the exponential model.  To estimate the compound growth rates, the growth model
is first converted to semilog form and then analyzed using Ordinary Least
Squares (OLS) regression.  This package has been developed using concept of
Shankar et al. (2022)<doi:10.3389/fsufs.2023.1208898>.")
    (license license:gpl3)))

(define-public r-cgpfunctions
  (package
    (name "r-cgpfunctions")
    (version "0.6.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CGPfunctions" version))
       (sha256
        (base32 "12l3ww9wfrk8i0a63wv5h4ayqj6fj5fz5yvkiskvaaida32vds2m"))))
    (properties `((upstream-name . "CGPfunctions")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-sjstats
                             r-scales
                             r-rlang
                             r-purrr
                             r-partykit
                             r-paletteer
                             r-ggrepel
                             r-ggplot2
                             r-ggmosaic
                             r-forcats
                             r-dplyr
                             r-desctools
                             r-bayesfactor))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ibecav/CGPfunctions")
    (synopsis
     "Powell Miscellaneous Functions for Teaching and Learning Statistics")
    (description
     "Miscellaneous functions useful for teaching statistics as well as actually
practicing the art.  They typically are not new methods but rather wrappers
around either base R or other packages.")
    (license license:expat)))

(define-public r-cgp
  (package
    (name "r-cgp")
    (version "2.1-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CGP" version))
       (sha256
        (base32 "05a6gydlb99yk2jpy2hyg4c30hqyp8dg2i9dmbjc1n5cmgpg3im9"))))
    (properties `((upstream-name . "CGP")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CGP")
    (synopsis "Composite Gaussian Process Models")
    (description
     "Fit composite Gaussian process (CGP) models as described in Ba and Joseph (2012)
\"Composite Gaussian Process Models for Emulating Expensive Functions\", Annals of
Applied Statistics.  The CGP model is capable of approximating complex surfaces
that are not second-order stationary.  Important functions in this package are
CGP, print.CGP, summary.CGP, predict.CGP and @code{plotCGP}.")
    (license license:lgpl2.1)))

(define-public r-cgnm
  (package
    (name "r-cgnm")
    (version "0.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CGNM" version))
       (sha256
        (base32 "1m2cqwb8q2lirf09d5pmqjan4r1w8m9pkg2wzyr8jp7sg1dqaaw7"))))
    (properties `((upstream-name . "CGNM")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-mass r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CGNM")
    (synopsis "Cluster Gauss-Newton Method")
    (description
     "Find multiple solutions of a nonlinear least squares problem.  Cluster
Gauss-Newton method does not assume uniqueness of the solution of the nonlinear
least squares problem and compute multiple minimizers.  Please cite the
following paper when this software is used in your research: Aoki et al. (2020)
<doi:10.1007/s11081-020-09571-2>.  Cluster GaussâNewton method.  Optimization
and Engineering, 1-31.  Please cite the following paper when profile likelihood
plot is drawn with this software and used in your research: Aoki and Sugiyama
(2024) <doi:10.1002/psp4.13055>.  Cluster Gauss-Newton method for a quick
approximation of profile likelihood: With application to physiologically-based
pharmacokinetic models.  CPT Pharmacometrics Syst Pharmacol.13(1):54-67.")
    (license license:expat)))

(define-public r-cgmquantify
  (package
    (name "r-cgmquantify")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cgmquantify" version))
       (sha256
        (base32 "11pw1layzx9a8qy7n06nyc59mi5r07krhxw6hhybbqkdglzp511w"))))
    (properties `((upstream-name . "cgmquantify")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyverse r-magrittr r-hms r-ggplot2 r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cgmquantify")
    (synopsis "Analyzing Glucose and Glucose Variability")
    (description
     "Continuous glucose monitoring (CGM) systems provide real-time, dynamic glucose
information by tracking interstitial glucose values throughout the day.
Glycemic variability, also known as glucose variability, is an established risk
factor for hypoglycemia (Kovatchev) and has been shown to be a risk factor in
diabetes complications.  Over 20 metrics of glycemic variability have been
identified.  Here, we provide functions to calculate glucose summary metrics,
glucose variability metrics (as defined in clinical publications), and
visualizations to visualize trends in CGM data.  Cho P, Bent B, Wittmann A, et
al. (2020)
<https://diabetes.diabetesjournals.org/content/69/Supplement_1/73-LB.abstract>
American Diabetes Association (2020)
<https://professional.diabetes.org/diapro/glucose_calc> Kovatchev B (2019)
<doi:10.1177/1932296819826111> Kovdeatchev BP (2017) <doi:10.1038/nrendo.2017.3>
Tamborlane W V., Beck RW, Bode BW, et al. (2008) <doi:10.1056/NEJMoa0805017>
Umpierrez GE, P. Kovatchev B (2018) <doi:10.1016/j.amjms.2018.09.010>.")
    (license (license:fsdg-compatible "MIT License + file LICENSE"))))

(define-public r-cgmanalyzer
  (package
    (name "r-cgmanalyzer")
    (version "1.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CGManalyzer" version))
       (sha256
        (base32 "1hg8svdqq0xgdxvry5agwvz2jlx6d0vazny9kdxwxlg4wnydai2f"))))
    (properties `((upstream-name . "CGManalyzer")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CGManalyzer")
    (synopsis "Continuous Glucose Monitoring Data Analyzer")
    (description
     "This package contains all of the functions necessary for the complete analysis
of a continuous glucose monitoring study and can be applied to data measured by
various existing CGM devices such as @code{FreeStyle} Libre', Glutalor', Dexcom
and Medtronic CGM'.  It reads a series of data files, is able to convert various
formats of time stamps, can deal with missing values, calculates both regular
statistics and nonlinear statistics, and conducts group comparison.  It also
displays results in a concise format.  Also contains two unique features new to
CGM analysis: one is the implementation of strictly standard mean difference and
the class of effect size; the other is the development of a new type of plot
called antenna plot.  It corresponds to Zhang
XD'(2018)<doi:10.1093/bioinformatics/btx826>'s article CGManalyzer: an R package
for analyzing continuous glucose monitoring studies'.")
    (license license:expat)))

(define-public r-cgmanalysis
  (package
    (name "r-cgmanalysis")
    (version "2.7.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cgmanalysis" version))
       (sha256
        (base32 "19kvxbg4vs7bfs3y1bfvhklwr22kba46aiwsns58g7h9b88m4kw7"))))
    (properties `((upstream-name . "cgmanalysis")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-xml
                             r-readxl
                             r-readr
                             r-pracma
                             r-pastecs
                             r-parsedate
                             r-lubridate
                             r-ggplot2))
    (home-page "https://cran.r-project.org/package=cgmanalysis")
    (synopsis "Clean and Analyze Continuous Glucose Monitor Data")
    (description
     "This code provides several different functions for cleaning and analyzing
continuous glucose monitor data.  Currently it works with Dexcom', @code{iPro}
2', Diasend', Libre', or Carelink data.  The cleandata() function takes a
directory of CGM data files and prepares them for analysis.  cgmvariables()
iterates through a directory of cleaned CGM data files and produces a single
spreadsheet with data for each file in either rows or columns.  The column
format of this spreadsheet is compatible with REDCap data upload.  cgmreport()
also iterates through a directory of cleaned data, and produces PDFs of
individual and aggregate AGP plots.  Please visit
<https://github.com/childhealthbiostatscore/R-Packages/> to download the
new-user guide.")
    (license license:cc0)))

(define-public r-cglm
  (package
    (name "r-cglm")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cglm" version))
       (sha256
        (base32 "1r3wrds5lbirzzqsi12prwykxa5361jb95pq7j95nlp6y8kcb94j"))))
    (properties `((upstream-name . "cglm")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-nleqslv r-data-table))
    (home-page "https://cran.r-project.org/package=cglm")
    (synopsis "Fits Conditional Generalized Linear Models")
    (description
     "Estimates the ratio of the regression coefficients and the dispersion parameter
in conditional generalized linear models for clustered data.")
    (license license:gpl2+)))

(define-public r-cglasso
  (package
    (name "r-cglasso")
    (version "2.0.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cglasso" version))
       (sha256
        (base32 "18j50f6ghk7vjr3xfw8j1nh42l6rm8kd5c6jcvll2rjbvq5vn571"))))
    (properties `((upstream-name . "cglasso")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-igraph))
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=cglasso")
    (synopsis
     "Conditional Graphical LASSO for Gaussian Graphical Models with Censored and Missing Values")
    (description
     "Conditional graphical lasso estimator is an extension of the graphical lasso
proposed to estimate the conditional dependence structure of a set of p response
variables given q predictors.  This package provides suitable extensions
developed to study datasets with censored and/or missing values.  Standard
conditional graphical lasso is available as a special case.  Furthermore, the
package provides an integrated set of core routines for visualization, analysis,
and simulation of datasets with censored and/or missing values drawn from a
Gaussian graphical model.  Details about the implemented models can be found in
Augugliaro et al. (2023) <doi: 10.18637/jss.v105.i01>, Augugliaro et al. (2020b)
<doi: 10.1007/s11222-020-09945-7>, Augugliaro et al. (2020a) <doi:
10.1093/biostatistics/kxy043>, Yin et al. (2001) <doi: 10.1214/11-AOAS494> and
Stadler et al. (2012) <doi: 10.1007/s11222-010-9219-7>.")
    (license license:gpl2+)))

(define-public r-cggp
  (package
    (name "r-cggp")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CGGP" version))
       (sha256
        (base32 "01jnq0bxacz5vlacmizanc54ms0fdbs9whapqlzdw4jrjlxnwnxa"))))
    (properties `((upstream-name . "CGGP")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/CollinErickson/CGGP")
    (synopsis "Composite Grid Gaussian Processes")
    (description
     "Run computer experiments using the adaptive composite grid algorithm with a
Gaussian process model.  The algorithm works best when running an experiment
that can evaluate thousands of points from a deterministic computer simulation.
This package is an implementation of a forthcoming paper by Plumlee, Erickson,
Ankenman, et al.  For a preprint of the paper, contact the maintainer of this
package.")
    (license license:gpl3)))

(define-public r-cge
  (package
    (name "r-cge")
    (version "0.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CGE" version))
       (sha256
        (base32 "0q1fv62159cx9z25488fxf6a6fi1m59hdh60ldypsjwil77q0s3i"))))
    (properties `((upstream-name . "CGE")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CGE")
    (synopsis "Computing General Equilibrium")
    (description
     "Developing general equilibrium models, computing general equilibrium and
simulating economic dynamics with structural dynamic models in LI (2019, ISBN:
9787521804225) \"General Equilibrium and Structural Dynamics: Perspectives of New
Structural Economics.  Beijing: Economic Science Press\".  When developing
complex general equilibrium models, GE package should be used in addition to
this package.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-cgauc
  (package
    (name "r-cgauc")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cgAUC" version))
       (sha256
        (base32 "172f9rkfhv4xzwpw8izsnsdbcw9p3hvxhh0fd8hzlkil7vskr3k8"))))
    (properties `((upstream-name . "cgAUC")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://cran.r-project.org/package=cgAUC")
    (synopsis
     "Calculate AUC-type measure when gold standard is continuous and the corresponding optimal linear combination of variables with respect to it")
    (description
     "The @code{cgAUC} can calculate the AUC-type measure of Obuchowski(2006) when
gold standard is continuous, and find the optimal linear combination of
variables with respect to this measure.")
    (license license:gpl2+)))

(define-public r-cgam
  (package
    (name "r-cgam")
    (version "1.21")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cgam" version))
       (sha256
        (base32 "0dsiwam9fgvri14hznnplxcjj0f8ibi8vf64wryq3pcvi41di082"))))
    (properties `((upstream-name . "cgam")))
    (build-system r-build-system)
    (propagated-inputs (list r-svdialogs r-statmod r-matrix r-lme4 r-coneproj))
    (home-page "https://cran.r-project.org/package=cgam")
    (synopsis "Constrained Generalized Additive Model")
    (description
     "This package provides a constrained generalized additive model is fitted by the
cgam routine.  Given a set of predictors, each of which may have a shape or
order restrictions, the maximum likelihood estimator for the constrained
generalized additive model is found using an iteratively re-weighted cone
projection algorithm.  The @code{ShapeSelect} routine chooses a subset of
predictor variables and describes the component relationships with the response.
 For each predictor, the user needs only specify a set of possible shape or
order restrictions.  A model selection method chooses the shapes and orderings
of the relationships as well as the variables.  The cone information criterion
(CIC) is used to select the best combination of variables and shapes.  A genetic
algorithm may be used when the set of possible models is large.  In addition,
the cgam routine implements a two-dimensional isotonic regression using
warped-plane splines without additivity assumptions.  It can also fit a convex
or concave regression surface with triangle splines without additivity
assumptions.  See Liao X, Meyer MC (2019)<doi:10.18637/jss.v089.i05> for more
details.")
    (license license:gpl2+)))

(define-public r-cgal4h
  (package
    (name "r-cgal4h")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cgal4h" version))
       (sha256
        (base32 "0ghcwjfqlhqysnl8mgz6zp7dyqh8pvnpvphwjwk6zqi24n3nhac2"))))
    (properties `((upstream-name . "cgal4h")))
    (build-system r-build-system)
    (home-page "https://gitlab.com/dickoa/cgal4h")
    (synopsis "'CGAL' Version 4 C++ Header Files")
    (description
     "CGAL is a C++ library that aims to provide easy access to efficient and reliable
algorithms in computational geometry.  Since its version 4, CGAL can be used as
standalone header-only library and is available under a double GPL-3|LGPL
license. <https://www.cgal.org/>.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-cgaim
  (package
    (name "r-cgaim")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cgaim" version))
       (sha256
        (base32 "1krs61rbnz7v4pncbjlil4728x5xyz5vzbyj487njbmqgymq10wl"))))
    (properties `((upstream-name . "cgaim")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncatednormal
                             r-scar
                             r-scam
                             r-quadprog
                             r-osqp
                             r-mgcv
                             r-matrix
                             r-mass
                             r-limsolve
                             r-gratia
                             r-foreach
                             r-doparallel
                             r-coneproj
                             r-cgam))
    (home-page "https://cran.r-project.org/package=cgaim")
    (synopsis "Constrained Groupwise Additive Index Models")
    (description
     "Fits constrained groupwise additive index models and provides functions for
inference and interpretation of these models.  The method is described in
Masselot, Chebana, Campagna, Lavigne, Ouarda, Gosselin (2022) \"Constrained
groupwise additive index models\" <doi:10.1093/biostatistics/kxac023>.")
    (license license:gpl3)))

(define-public r-cg
  (package
    (name "r-cg")
    (version "1.0-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cg" version))
       (sha256
        (base32 "1kbyal1sicbr10yvxpwgcij710kqpi23vmndp9kyfzn3k8zfird3"))))
    (properties `((upstream-name . "cg")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam
                             r-survival
                             r-rms
                             r-nlme
                             r-multcomp
                             r-mass
                             r-lattice
                             r-hmisc))
    (home-page "https://cran.r-project.org/package=cg")
    (synopsis "Compare Groups, Analytically and Graphically")
    (description
     "Comprehensive data analysis software, and the name \"cg\" stands for \"compare
groups.\" Its genesis and evolution are driven by common needs to compare
administrations, conditions, etc.  in medicine research and development.  The
current version provides comparisons of unpaired samples, i.e.  a linear model
with one factor of at least two levels.  It also provides comparisons of two
paired samples.  Good data graphs, modern statistical methods, and useful
displays of results are emphasized.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-cftime
  (package
    (name "r-cftime")
    (version "1.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CFtime" version))
       (sha256
        (base32 "171xbi6jb2d88i15gian5p4lfjhrsyp3j99mbcrg3196dw1dfrjq"))))
    (properties `((upstream-name . "CFtime")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/pvanlaake/CFtime")
    (synopsis "Using CF-Compliant Calendars with Climate Projection Data")
    (description
     "Support for all calendars as specified in the Climate and Forecast (CF) Metadata
Conventions for climate and forecasting data.  The CF Metadata Conventions is
widely used for distributing files with climate observations or projections,
including the Coupled Model Intercomparison Project (CMIP) data used by climate
change scientists and the Intergovernmental Panel on Climate Change (IPCC).
This package specifically allows the user to work with any of the CF-compliant
calendars (many of which are not compliant with POSIXt).  The CF time coordinate
is formally defined in the CF Metadata Conventions document available at
<https://cfconventions.org/Data/cf-conventions/cf-conventions-1.11/cf-conventions.html#time-coordinate>.")
    (license license:expat)))

(define-public r-cft
  (package
    (name "r-cft")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cft" version))
       (sha256
        (base32 "1jfp1dx15bs9c8c11ja80ga99m2d9q9j5sgdjkwvs23vjqdwi13a"))))
    (properties `((upstream-name . "cft")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tidync
                             r-sf
                             r-rlist
                             r-rlang
                             r-plyr
                             r-piper
                             r-osmdata
                             r-magrittr
                             r-future
                             r-furrr
                             r-epitools
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/earthlab/cft-CRAN")
    (synopsis "Climate Futures Toolbox")
    (description
     "Developed as a collaboration between Earth lab and the North Central Climate
Adaptation Science Center to help users gain insights from available climate
data.  Includes tools and instructions for downloading climate data via a USGS
API and then organizing those data for visualization and analysis that drive
insight.  Web interface for USGS API can be found at
<http://thredds.northwestknowledge.net:8080/thredds/reacch_climate_CMIP5_aggregated_macav2_catalog.html>.")
    (license license:gpl3+)))

(define-public r-cfr
  (package
    (name "r-cfr")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cfr" version))
       (sha256
        (base32 "0sgjdapsiqn436xswl06p3m84j9z1savbyibxqzs2zc9x3imjfqr"))))
    (properties `((upstream-name . "cfr")))
    (build-system r-build-system)
    (propagated-inputs (list r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/epiverse-trace/cfr")
    (synopsis "Estimate Disease Severity and Case Ascertainment")
    (description
     "Estimate the severity of a disease and ascertainment of cases, as discussed in
Nishiura et al. (2009) <doi:10.1371/journal.pone.0006852>.")
    (license license:expat)))

(define-public r-cforward
  (package
    (name "r-cforward")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cforward" version))
       (sha256
        (base32 "1vhac0669f20ckx7qi5v8rnbmscb87gw8rfn555xazdfbvri6m0w"))))
    (properties `((upstream-name . "cforward")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-survival r-magrittr r-dplyr))
    (home-page "https://github.com/muschellij2/cforward")
    (synopsis "Forward Selection using Concordance/C-Index")
    (description
     "This package performs forward model selection, using the C-index/concordance in
survival analysis models.")
    (license license:gpl3)))

(define-public r-cfo
  (package
    (name "r-cfo")
    (version "2.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CFO" version))
       (sha256
        (base32 "1dixm7xg341yw8qpbdz5gx0d8lnil02fcpz4n37pkgx42qd3qxmh"))))
    (properties `((upstream-name . "CFO")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-scales
                             r-rcolorbrewer
                             r-pbapply
                             r-iso
                             r-ggplot2
                             r-dplyr))
    (home-page "https://clinicaltrialdesign.shinyapps.io/cfoapp")
    (synopsis "CFO-Type Designs in Phase I/II Clinical Trials")
    (description
     "In phase I clinical trials, the primary objective is to ascertain the maximum
tolerated dose (MTD) corresponding to a specified target toxicity rate.  The
subsequent phase II trials are designed to examine the potential efficacy of the
drug based on the MTD obtained from the phase I trials, with the aim of
identifying the optimal biological dose (OBD).  The CFO package facilitates the
implementation of dose-finding trials by utilizing calibration-free odds type
(CFO-type) designs.  Specifically, it encompasses the calibration-free odds
(CFO) (Jin and Yin (2022) <doi:10.1177/09622802221079353>), randomized CFO
(@code{rCFO}), two-dimensional CFO (2@code{dCFO}) (Wang et al. (2023)
<doi:10.3389/fonc.2023.1294258>), time-to-event CFO (TITE-CFO) (Jin and Yin
(2023) <doi:10.1002/pst.2304>), fractional CFO (@code{fCFO}), accumulative CFO
(@code{aCFO}), TITE-@code{aCFO}, and f-@code{aCFO} designs (Fang and Yin (2024)
<doi: 10.1002/sim.10127>).  It supports phase I/II trials for the CFO design and
only phase I trials for the other CFO-type designs.  The âCFO package
accommodates diverse CFO-type designs, allowing users to tailor the approach
based on factors such as dose information inclusion, handling of late-onset
toxicity, and the nature of the target drug (single-drug or drug-combination).
The functionalities embedded in CFO package include the determination of the
dose level for the next cohort, the selection of the MTD for a real trial, and
the execution of single or multiple simulations to obtain operating
characteristics.  Moreover, these functions are equipped with early stopping and
dose elimination rules to address safety considerations.  Users have the
flexibility to choose different distributions, thresholds, and cohort sizes
among others for their specific needs.  The output of the CFO package can be
summary statistics as well as various plots for better visualization.  An
interactive web application for CFO is available at the provided URL.")
    (license license:gpl2)))

(define-public r-cfmortality
  (package
    (name "r-cfmortality")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cfmortality" version))
       (sha256
        (base32 "0dgwv89fzylznc6jr41ixzfs1gfs3np4gf46bk6pcd09l1kbx3lc"))))
    (properties `((upstream-name . "cfmortality")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cfmortality")
    (synopsis
     "Cystic Fibrosis Survival Prediction Model Based on Stanojevic Model")
    (description
     "Allows clinicians to predict survival probabilities over the next two years for
cystic fibrosis patients, based on the clinical prediction models published in
Stanojevic et al. (2019) <doi:10.1183/13993003.00224-2019>.")
    (license license:gpl3)))

(define-public r-cfma
  (package
    (name "r-cfma")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cfma" version))
       (sha256
        (base32 "006z5g3rqpg44jqdf6ivyxr47sxm5cd9cqhayfi8qk73xx5w4lv9"))))
    (properties `((upstream-name . "cfma")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cfma")
    (synopsis "Causal Functional Mediation Analysis")
    (description
     "This package performs causal functional mediation analysis (CFMA) for functional
treatment, functional mediator, and functional outcome.  This package includes
two functional mediation model types: (1) a concurrent mediation model and (2) a
historical influence mediation model.  See Zhao et al. (2018), Functional
Mediation Analysis with an Application to Functional Magnetic Resonance Imaging
Data, <@code{arXiv:1805.06923>} for details.")
    (license license:gpl2+)))

(define-public r-cfilt
  (package
    (name "r-cfilt")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CFilt" version))
       (sha256
        (base32 "0gngc6z9ssrniycn1p2apjdhlz78ykbv51nxxr85rvqiiz1lx515"))))
    (properties `((upstream-name . "CFilt")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CFilt")
    (synopsis "Recommendation by Collaborative Filtering")
    (description
     "This package provides methods and functions to implement a Recommendation System
based on Collaborative Filtering Methodology.  See Aggarwal (2016)
<doi:10.1007/978-3-319-29659-3> for an overview.")
    (license license:gpl3)))

(define-public r-cfid
  (package
    (name "r-cfid")
    (version "0.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cfid" version))
       (sha256
        (base32 "03wfzilxgia12hacwkay2ki94mha8b42g62cx66x1rkqqxgcp6n9"))))
    (properties `((upstream-name . "cfid")))
    (build-system r-build-system)
    (home-page "https://github.com/santikka/cfid")
    (synopsis "Identification of Counterfactual Queries in Causal Models")
    (description
     "Facilitates the identification of counterfactual queries in structural causal
models via the ID* and IDC* algorithms by Shpitser, I. and Pearl, J. (2007,
2008) <@code{arXiv:1206.5294>}, <https://jmlr.org/papers/v9/shpitser08a.html>.
Provides a simple interface for defining causal diagrams and counterfactual
conjunctions.  Construction of parallel worlds graphs and counterfactual graphs
is carried out automatically based on the counterfactual query and the causal
diagram.  See Tikka, S. (2023) <doi:10.32614/RJ-2023-053> for a tutorial of the
package.")
    (license license:gpl3+)))

(define-public r-cffr
  (package
    (name "r-cffr")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cffr" version))
       (sha256
        (base32 "1aja12kn1f6h3zydfichiq2l2qd0qd7fl794v6ypp433hh54yvxg"))))
    (properties `((upstream-name . "cffr")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml r-jsonvalidate r-jsonlite r-desc r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/cffr/")
    (synopsis "Generate Citation File Format ('cff') Metadata for R Packages")
    (description
     "The Citation File Format version 1.2.0 <doi:10.5281/zenodo.5171937> is a human
and machine readable file format which provides citation metadata for software.
This package provides core utilities to generate and validate this metadata.")
    (license license:gpl3+)))

(define-public r-cffdrs
  (package
    (name "r-cffdrs")
    (version "1.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cffdrs" version))
       (sha256
        (base32 "0y4w045fgn1q63w9bk4qwzzxij34agjsg396vmydljz3w86insib"))))
    (properties `((upstream-name . "cffdrs")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra
                             r-sf
                             r-geosphere
                             r-foreach
                             r-doparallel
                             r-data-table))
    (home-page "https://r-forge.r-project.org/projects/cffdrs/")
    (synopsis "Canadian Forest Fire Danger Rating System")
    (description
     "This project provides a group of new functions to calculate the outputs of the
two main components of the Canadian Forest Fire Danger Rating System (CFFDRS)
Van Wagner and Pickett (1985) <https://cfs.nrcan.gc.ca/publications?id=19973>)
at various time scales: the Fire Weather Index (FWI) System Wan Wagner (1985)
<https://cfs.nrcan.gc.ca/publications?id=19927> and the Fire Behaviour
Prediction (FBP) System Forestry Canada Fire Danger Group (1992)
<https://cfs.nrcan.gc.ca/pubwarehouse/pdfs/10068.pdf>.  Some functions have two
versions, table and raster based.")
    (license license:gpl2)))

(define-public r-cff
  (package
    (name "r-cff")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CFF" version))
       (sha256
        (base32 "04z3q0s4b1yns5l7lplw8qrcdjzsdy9crnhakyzd6r449hjfsvnz"))))
    (properties `((upstream-name . "CFF")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CFF")
    (synopsis
     "Simple Similarity for User-Based Collaborative Filtering Systems")
    (description
     "This package provides a simple, fast algorithm to find the neighbors and
similarities of users in user-based filtering systems, to break free from the
complex computation of existing similarity formulas and the ability to solve big
data.")
    (license license:gpl2+)))

(define-public r-cfdecomp
  (package
    (name "r-cfdecomp")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cfdecomp" version))
       (sha256
        (base32 "0g61gpihk5kbbrqzn15fqjv3bawsq1vq3sdssbzs5j96afmf2aq8"))))
    (properties `((upstream-name . "cfdecomp")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cfdecomp")
    (synopsis "Counterfactual Decomposition: MC Integration of the G-Formula")
    (description
     "This package provides a set of functions for counterfactual decomposition
(cfdecomp).  The functions available in this package decompose differences in an
outcome attributable to a mediating variable (or sets of mediating variables)
between groups based on counterfactual (causal inference) theory.  By using
Monte Carlo (MC) integration (simulations based on empirical estimates from
multivariable models) we provide added flexibility compared to existing
(analytical) approaches, at the cost of computational power or time.  The added
flexibility means that we can decompose difference between groups in any outcome
or and with any mediator (any variable type and distribution).  See Sudharsanan
& Bijlsma (2019) <doi:10.4054/MPIDR-WP-2019-004> for more information.")
    (license license:gpl3)))

(define-public r-cfda
  (package
    (name "r-cfda")
    (version "0.11.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cfda" version))
       (sha256
        (base32 "03w2vfgjf29qn40slqfpd54dmvzql53lc9j7n51ggg7bjchrg2x0"))))
    (properties `((upstream-name . "cfda")))
    (build-system r-build-system)
    (propagated-inputs (list r-pbapply
                             r-msm
                             r-mgcv
                             r-ggplot2
                             r-fda
                             r-diagram))
    (native-inputs (list r-knitr))
    (home-page "https://modal-inria.github.io/cfda/")
    (synopsis "Categorical Functional Data Analysis")
    (description
     "Package for the analysis of categorical functional data.  The main purpose is to
compute an encoding (real functional variable) for each state
<doi:10.3390/math9233074>.  It also provides functions to perform basic
statistical analysis on categorical functional data.")
    (license license:agpl3)))

(define-public r-cfc
  (package
    (name "r-cfc")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CFC" version))
       (sha256
        (base32 "16abn3ydixb819qyyrs351d8v6qaaaz1gif0yfd8gdh7xnr2qzpy"))))
    (properties `((upstream-name . "CFC")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-rcppprogress
                             r-rcpparmadillo
                             r-rcpp
                             r-foreach
                             r-doparallel
                             r-abind))
    (home-page "https://cran.r-project.org/package=CFC")
    (synopsis "Cause-Specific Framework for Competing-Risk Analysis")
    (description
     "Numerical integration of cause-specific survival curves to arrive at
cause-specific cumulative incidence functions, with three usage modes: 1)
Convenient API for parametric survival regression followed by competing-risk
analysis, 2) API for CFC, accepting user-specified survival functions in R, and
3) Same as 2, but accepting survival functions in C++.  For mathematical details
and software tutorial, see Mahani and Sharabiani (2019)
<DOI:10.18637/jss.v089.i09>.")
    (license license:gpl2+)))

(define-public r-cfacoop
  (package
    (name "r-cfacoop")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CFAcoop" version))
       (sha256
        (base32 "1qnqbqh3p8grp6mxhqrwfm1nf1sxhqa6pjxkpf7vk9nx40g815gn"))))
    (properties `((upstream-name . "CFAcoop")))
    (build-system r-build-system)
    (propagated-inputs (list r-hmisc))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ZytoHMGU/CFAcoop")
    (synopsis
     "Colony Formation Assay: Taking into Account Cellular Cooperation")
    (description
     "Cellular cooperation compromises the plating efficiency-based analysis of
clonogenic survival data.  This tool provides functions that enable a robust
analysis of colony formation assay (CFA) data in presence or absence of cellular
cooperation.  The implemented method has been described in Brix et al. (2020).
(Brix, N., Samaga, D., Hennel, R. et al. \"The clonogenic assay: robustness of
plating efficiency-based analysis is strongly compromised by cellular
cooperation.\" Radiat Oncol 15, 248 (2020). <doi:10.1186/s13014-020-01697-y>)
Power regression for parameter estimation, calculation of survival fractions,
uncertainty analysis and plotting functions are provided.")
    (license license:gpl3)))

(define-public r-cfa
  (package
    (name "r-cfa")
    (version "0.10-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cfa" version))
       (sha256
        (base32 "1hmahwi60qiwf4g50d3cnhgvdbnv0q0shfalzxisv87xxr586mlj"))))
    (properties `((upstream-name . "cfa")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cfa")
    (synopsis "Configural Frequency Analysis (CFA)")
    (description
     "Analysis of configuration frequencies for simple and repeated measures,
multiple-samples CFA, hierarchical CFA, bootstrap CFA, functional CFA,
Kieser-Victor CFA, and Lindner's test using a conventional and an accelerated
algorithm.")
    (license license:gpl2+)))

(define-public r-ceterisparibus
  (package
    (name "r-ceterisparibus")
    (version "0.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ceterisParibus" version))
       (sha256
        (base32 "0hxklydsqb69y5sv2hanp5ja9k0063swf5si1j6gcj15lp7phpif"))))
    (properties `((upstream-name . "ceterisParibus")))
    (build-system r-build-system)
    (propagated-inputs (list r-knitr r-gower r-ggplot2 r-dalex))
    (home-page "https://pbiecek.github.io/ceterisParibus/")
    (synopsis "Ceteris Paribus Profiles")
    (description
     "Ceteris Paribus Profiles (What-If Plots) are designed to present model responses
around selected points in a feature space.  For example around a single
prediction for an interesting observation.  Plots are designed to work in a
model-agnostic fashion, they are working for any predictive Machine Learning
model and allow for model comparisons.  Ceteris Paribus Plots supplement the
Break Down Plots from @code{breakDown} package.")
    (license license:gpl2)))

(define-public r-cesr
  (package
    (name "r-cesr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cesR" version))
       (sha256
        (base32 "1sw5is461mrylmd8f9qzps368wilrgy41k6cmig445261zzqkikr"))))
    (properties `((upstream-name . "cesR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-readr r-labelled r-haven r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://hodgettsp.github.io/cesR/")
    (synopsis "Access the Canadian Election Study Datasets")
    (description
     "Makes accessing and loading the Canadian Election Study
(<http://www.ces-eec.ca/>, <https://ces-eec.arts.ubc.ca/>,
<https://search1.odesi.ca/#/>) surveys into the R workspace more efficient by
downloading a requested survey and loading it as a data object.  This removes
the need to locate, download, load, and change working directories when working
with the Canadian Election Study surveys.")
    (license license:expat)))

(define-public r-ceser
  (package
    (name "r-ceser")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ceser" version))
       (sha256
        (base32 "1k2k2gykyajlahl7xvpxdla0ghapdxl24yi575pgq2421fpxq2i4"))))
    (properties `((upstream-name . "ceser")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-purrr r-magrittr r-lmtest r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/DiogoFerrari/ceser")
    (synopsis "Cluster Estimated Standard Errors")
    (description
     "Implementation of the Cluster Estimated Standard Errors (CESE) proposed in
Jackson (2020) <DOI:10.1017/pan.2019.38> to compute clustered standard errors of
linear coefficients in regression models with grouped data.")
    (license license:expat)))

(define-public r-certara-vpcresults
  (package
    (name "r-certara-vpcresults")
    (version "3.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Certara.VPCResults" version))
       (sha256
        (base32 "0gvrvj8yx41h9kmrm8q02pwgrfz63a1f8cm8s98xcqbmqfh5bn40"))))
    (properties `((upstream-name . "Certara.VPCResults")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyvpc
                             r-sortable
                             r-shinywidgets
                             r-shinymeta
                             r-shinyjs
                             r-shinyjqui
                             r-shinycssloaders
                             r-shinyace
                             r-shiny
                             r-scales
                             r-rlang
                             r-plotly
                             r-htmltools
                             r-ggplot2
                             r-dt
                             r-dplyr
                             r-data-table
                             r-colourpicker
                             r-bslib))
    (home-page "https://certara.github.io/R-VPCResults/")
    (synopsis "Generate Visual Predictive Checks (VPC) Using 'shiny'")
    (description
     "Utilize the shiny interface to parameterize a Visual Predictive Check (VPC),
including selecting from different binning or binless methods and performing
stratification, censoring, and prediction correction.  Generate the underlying
tidyvpc and ggplot2 code directly from the user interface and download R or Rmd
scripts to reproduce the VPCs in R.")
    (license license:lgpl3)))

(define-public r-certara-r
  (package
    (name "r-certara-r")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Certara.R" version))
       (sha256
        (base32 "07k7dj37zywkfbrx85gnl6cvc0a0n1xyvmac0lg74nzqb6qb3i1z"))))
    (properties `((upstream-name . "Certara.R")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-ssh
                             r-sortable
                             r-shinywidgets
                             r-shinymaterial
                             r-shinyjs
                             r-shinyjqui
                             r-shiny
                             r-rlang
                             r-reshape
                             r-remotes
                             r-plotly
                             r-magrittr
                             r-jsonlite
                             r-htmltools
                             r-ggplot2
                             r-dt
                             r-dplyr
                             r-data-table
                             r-batchtools))
    (home-page "https://github.com/certara/R-Certara")
    (synopsis
     "Easily Install Pharmacometric Packages and Shiny Applications Developed by Certara")
    (description
     "This package provides a convenient set of wrapper functions to install
pharmacometric packages and Shiny applications developed by Certara PMX and
Integrated Drug Development (@code{iDD}).  The functions ensure the successful
installation of packages from non-standard repositories.")
    (license license:lgpl3)))

(define-public r-certara-nlme8
  (package
    (name "r-certara-nlme8")
    (version "3.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Certara.NLME8" version))
       (sha256
        (base32 "0ddwlrkb1cxjkpq12fy7ig3vp1wyxgvfa6lsvdbm111r6xbwz79j"))))
    (properties `((upstream-name . "Certara.NLME8")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2 r-reshape r-data-table r-batchtools))
    (home-page "https://cran.r-project.org/package=Certara.NLME8")
    (synopsis
     "Utilities for Certara's Nonlinear Mixed-Effects Modeling Engine")
    (description
     "Perform Nonlinear Mixed-Effects (NLME) Modeling using Certara's NLME-Engine.
Access the same Maximum Likelihood engines used in the Phoenix platform,
including algorithms for parametric methods, individual, and pooled data
analysis
<https://www.certara.com/app/uploads/2020/06/BR_@code{PhoenixNLME-v4.pdf>}.  The
Quasi-Random Parametric Expectation-Maximization Method (QRPEM) is also
supported <https://www.page-meeting.org/default.asp?abstract=2338>.  Execution
is supported both locally or on remote machines.  Remote execution includes
support for Linux Sun Grid Engine (SGE), Terascale Open-source Resource and
Queue Manager (TORQUE) grids, Linux and Windows multicore, and individual runs.")
    (license license:lgpl3)))

(define-public r-certainty
  (package
    (name "r-certainty")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ceRtainty" version))
       (sha256
        (base32 "01wgvjpxqwhgh6vx9vbmiv4d88bps790l6ij3gw5w69hbrrd9ixi"))))
    (properties `((upstream-name . "ceRtainty")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-rcolorbrewer r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ceRtainty")
    (synopsis "Certainty Equivalent")
    (description
     "Compute the certainty equivalents and premium risks as tools for risk-efficiency
analysis.  For more technical information, please refer to: Hardaker,
Richardson, Lien, & Schumann (2004) <doi:10.1111/j.1467-8489.2004.00239.x>, and
Richardson, & Outlaw (2008) <doi:10.2495/RISK080231>.")
    (license license:expat)))

(define-public r-cernaseek
  (package
    (name "r-cernaseek")
    (version "2.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CeRNASeek" version))
       (sha256
        (base32 "0l36bz73xy9miikqdigbnyr0bk83dx6wsaqlsc14b0r64jca4ak6"))))
    (properties `((upstream-name . "CeRNASeek")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-igraph r-gtools))
    (home-page "https://cran.r-project.org/package=CeRNASeek")
    (synopsis "Identification and Analysis of ceRNA Regulation")
    (description
     "This package provides several functions to identify and analyse @code{miRNA}
sponge, including popular methods for identifying @code{miRNA} sponge
interactions, two types of global @code{ceRNA} regulation prediction methods and
four types of context-specific prediction methods( Li Y et al.(2017)
<doi:10.1093/bib/bbx137>), which are based on @code{miRNA-messenger} RNA
regulation alone, or by integrating heterogeneous data, respectively.  In
addition, For predictive @code{ceRNA} relationship pairs, this package provides
several downstream analysis algorithms, including regulatory network analysis
and functional annotation analysis, as well as survival prognosis analysis based
on expression of @code{ceRNA} ternary pair.")
    (license license:gpl3)))

(define-public r-ceriolioutlierdetection
  (package
    (name "r-ceriolioutlierdetection")
    (version "1.1.15")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CerioliOutlierDetection" version))
       (sha256
        (base32 "1ngwq99q5xi3n06df36dhbgdpjdldfzsi70vhplwlha9cihd71k2"))))
    (properties `((upstream-name . "CerioliOutlierDetection")))
    (build-system r-build-system)
    (propagated-inputs (list r-robustbase))
    (home-page "https://christopherggreen.github.io/CerioliOutlierDetection/")
    (synopsis
     "Outlier Detection Using the Iterated RMCD Method of Cerioli (2010)")
    (description
     "This package implements the iterated RMCD method of Cerioli (2010) for
multivariate outlier detection via robust Mahalanobis distances.  Also provides
the finite-sample RMCD method discussed in the paper, as well as the methods
provided in Hardin and Rocke (2005) <doi:10.1198/106186005X77685> and Green and
Martin (2017) <https://christopherggreen.github.io/papers/hr05_extension.pdf>.
See also Chapter 2 of Green (2017)
<https://digital.lib.washington.edu/researchworks/handle/1773/40304>.")
    (license license:gpl2+)))

(define-public r-cerfit
  (package
    (name "r-cerfit")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CERFIT" version))
       (sha256
        (base32 "1mhyn5iyvnqqx881jfvacyxaldvn5q9h1jpsfy14sgkdjf75274s"))))
    (properties `((upstream-name . "CERFIT")))
    (build-system r-build-system)
    (propagated-inputs (list r-twang
                             r-rcpparmadillo
                             r-rcpp
                             r-randomforest
                             r-partykit
                             r-glmnet
                             r-cbps))
    (home-page "https://cran.r-project.org/package=CERFIT")
    (synopsis "Causal Effect Random Forest of Interaction Tress")
    (description
     "Fits a Causal Effect Random Forest of Interaction Tress (CERFIT) which is a
modification of the Random Forest algorithm where each split is chosen to
maximize subgroup treatment heterogeneity.  Doing this allows it to estimate the
individualized treatment effect for each observation in either randomized
controlled trial (RCT) or observational data.  For more information see X. Su,
A. T. PeÃ±a, L. Liu, and R. A. Levine (2018)
<doi:10.48550/@code{arXiv.1709.04862>}.")
    (license license:gpl2+)))

(define-public r-cereal
  (package
    (name "r-cereal")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cereal" version))
       (sha256
        (base32 "02s9hwp387dwzfbwwga05rxayk67zvj49hii7b4ksznynad7khsr"))))
    (properties `((upstream-name . "cereal")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs r-tibble r-rlang r-jsonlite))
    (home-page "https://r-lib.github.io/cereal/")
    (synopsis "Serialize 'vctrs' Objects to 'JSON'")
    (description
     "The vctrs package provides a concept of vector prototype that can be especially
useful when deploying models and code.  Serialize these object prototypes to
JSON so they can be used to check and coerce data in production systems, and
deserialize JSON back to the correct object prototypes.")
    (license license:expat)))

(define-public r-ceramic
  (package
    (name "r-ceramic")
    (version "0.9.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ceramic" version))
       (sha256
        (base32 "04mywwl8hm2plcs7m4p5sjhadvgfpy42pagn2cxajpcpl7gqskfc"))))
    (properties `((upstream-name . "ceramic")))
    (build-system r-build-system)
    (propagated-inputs (list r-wk
                             r-vapour
                             r-tibble
                             r-terra
                             r-stringr
                             r-sp
                             r-slippymath
                             r-rlang
                             r-rappdirs
                             r-purrr
                             r-glue
                             r-fs
                             r-dplyr
                             r-curl
                             r-crsmeta))
    (home-page "https://hypertidy.github.io/ceramic/")
    (synopsis "Download Online Imagery Tiles")
    (description
     "Download imagery tiles to a standard cache and load the data into raster
objects.  Facilities for AWS terrain
<https://registry.opendata.aws/terrain-tiles/> terrain and Mapbox
<https://www.mapbox.com/> servers are provided.")
    (license license:gpl3)))

(define-public r-cequre
  (package
    (name "r-cequre")
    (version "1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cequre" version))
       (sha256
        (base32 "06c8fdyl6434f1hfs8vr2pvg53m0ymc5wngjxsmya66ffyq6v5ny"))))
    (properties `((upstream-name . "cequre")))
    (build-system r-build-system)
    (native-inputs (list r-knitr gfortran))
    (home-page "https://cran.r-project.org/package=cequre")
    (synopsis
     "Censored Quantile Regression & Monotonicity-Respecting Restoring")
    (description
     "Perform censored quantile regression of Huang (2010) <doi:10.1214/09-AOS771>,
and restore monotonicity respecting via adaptive interpolation for dynamic
regression of Huang (2017) <doi:10.1080/01621459.2016.1149070>.  The
monotonicity-respecting restoration applies to general dynamic regression models
including (uncensored or censored) quantile regression model, additive hazards
model, and dynamic survival models of Peng and Huang (2007)
<doi:10.1093/biomet/asm058>, among others.")
    (license license:gpl2+)))

(define-public r-cepumd
  (package
    (name "r-cepumd")
    (version "2.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cepumd" version))
       (sha256
        (base32 "09kw26kqzcwjzqyxcrwijk4cz4m6m2i62wwmyc1sm0wl39lk7c0g"))))
    (properties `((upstream-name . "cepumd")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-stringr
                             r-rlang
                             r-readxl
                             r-readr
                             r-purrr
                             r-janitor
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://arcenis-r.github.io/cepumd/")
    (synopsis "Calculate Consumer Expenditure Survey (CE) Annual Estimates")
    (description
     "This package provides functions and data files to help CE Public-Use Microdata
(PUMD) users calculate annual estimated expenditure means, standard errors, and
quantiles according to the methods used by the CE with PUMD. For more
information on the CE please visit <https://www.bls.gov/cex>.  For further
reading on CE estimate calculations please see the CE Calculation section of the
U.S. Bureau of Labor Statistics (BLS) Handbook of Methods at
<https://www.bls.gov/opub/hom/cex/calculation.htm>.  For further information
about CE PUMD please visit <https://www.bls.gov/cex/pumd.htm>.")
    (license license:gpl3+)))

(define-public r-cepreader
  (package
    (name "r-cepreader")
    (version "1.2-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cepreader" version))
       (sha256
        (base32 "0n704vya03p3njx9z930mw0rg0vh14aq0kng5zh2nwkx1g9aqa2p"))))
    (properties `((upstream-name . "cepreader")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix))
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/")
    (synopsis "Read 'CEP' and Legacy 'CANOCO' Files")
    (description
     "Read Condensed Cornell Ecology Program ('CEP') and legacy CANOCO files into R
data frames.")
    (license (license:fsdg-compatible "MIT + file LICENCE"))))

(define-public r-cepr
  (package
    (name "r-cepr")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cepR" version))
       (sha256
        (base32 "02dj6vyfgc0lsgclbsmzpms1hnnwb3yjdayim7b7vpciym2c8ww3"))))
    (properties `((upstream-name . "cepR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-purrr r-magrittr r-httr r-dplyr))
    (home-page "https://github.com/RobertMyles/cepR")
    (synopsis "Busca CEPs Brasileiros")
    (description
     "Retorna detalhes de dados de CEPs brasileiros, bairros, logradouros e tal.
(Returns info of Brazilian postal codes, city names, addresses and so on.).")
    (license license:expat)))

(define-public r-cepp
  (package
    (name "r-cepp")
    (version "1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cepp" version))
       (sha256
        (base32 "01hvm6586xnb1crvk7brqh3dm2j44ia5lrl5swnf6pb682yskbq0"))))
    (properties `((upstream-name . "cepp")))
    (build-system r-build-system)
    (propagated-inputs (list r-trust r-randtoolbox))
    (home-page "https://cran.r-project.org/package=cepp")
    (synopsis "Context Driven Exploratory Projection Pursuit")
    (description
     "This package provides functions and Data to support Context Driven Exploratory
Projection Pursuit.")
    (license license:gpl3)))

(define-public r-cepiigeodist
  (package
    (name "r-cepiigeodist")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cepiigeodist" version))
       (sha256
        (base32 "0i1i8hyl4bkcyxrrfqs3m9yny33w0i33409f4kx83wfnablc54sv"))))
    (properties `((upstream-name . "cepiigeodist")))
    (build-system r-build-system)
    (home-page "https://pacha.dev/cepiigeodist/")
    (synopsis "CEPII's GeoDist Datasets")
    (description
     "This package provides data on countries and their main city or agglomeration and
the different distance measures and dummy variables indicating whether two
countries are contiguous, share a common language or a colonial relationship.
The reference article for these datasets is Mayer and Zignago (2011)
<http://www.cepii.fr/CEPII/en/publications/wp/abstract.asp?@code{NoDoc=3877>}.")
    (license license:cc0)))

(define-public r-cepa
  (package
    (name "r-cepa")
    (version "0.8.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CePa" version))
       (sha256
        (base32 "1nhcr9pyn2swv8jmqm26gl9plxr7qln3mjylmyawc94ayhnj45g0"))))
    (properties `((upstream-name . "CePa")))
    (build-system r-build-system)
    (arguments
     (list
      #:modules '((guix build r-build-system)
                  (guix build minify-build-system)
                  (guix build utils)
                  (ice-9 match))
      #:imported-modules `(,@%r-build-system-modules (guix build
                                                      minify-build-system))
      #:phases '(modify-phases %standard-phases
                  (add-after 'unpack 'process-javascript
                    (lambda* (#:key inputs #:allow-other-keys)
                      (with-directory-excursion "inst/"
                        (for-each (match-lambda
                                    ((source . target) (minify source
                                                               #:target target)))
                                  '())))))))
    (propagated-inputs (list r-rgraphviz r-igraph r-graph))
    (native-inputs (list esbuild))
    (home-page "https://github.com/jokergoo/CePa")
    (synopsis "Centrality-Based Pathway Enrichment")
    (description
     "It aims to find significant pathways through network topology information.  It
has several advantages compared with current pathway enrichment tools.  First,
pathway node instead of single gene is taken as the basic unit when analysing
networks to meet the fact that genes must be constructed into complexes to hold
normal functions.  Second, multiple network centrality measures are applied
simultaneously to measure importance of nodes from different aspects to make a
full view on the biological system. @code{CePa} extends standard pathway
enrichment methods, which include both over-representation analysis procedure
and gene-set analysis procedure. <doi:10.1093/bioinformatics/btt008>.")
    (license license:gpl2+)))

(define-public r-ceoptim
  (package
    (name "r-ceoptim")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CEoptim" version))
       (sha256
        (base32 "0b39q2imxgqwa836gzq6l93g0fsf8kdj2wjl4if8a8lw5inx7zgw"))))
    (properties `((upstream-name . "CEoptim")))
    (build-system r-build-system)
    (propagated-inputs (list r-sna r-msm r-mass))
    (home-page "https://cran.r-project.org/package=CEoptim")
    (synopsis "Cross-Entropy R Package for Optimization")
    (description "Optimization solver based on the Cross-Entropy method.")
    (license license:gpl2+)))

(define-public r-ceodata
  (package
    (name "r-ceodata")
    (version "1.3.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CEOdata" version))
       (sha256
        (base32 "0cf8d3qw2x2lww6hxw96b1b6dl6pq2n0w1ffl2d7870vcvzl3lwr"))))
    (properties `((upstream-name . "CEOdata")))
    (build-system r-build-system)
    (propagated-inputs (list r-urltools r-stringr r-jsonlite r-haven r-dplyr))
    (native-inputs (list r-r-rsp r-knitr))
    (home-page "https://ceo.gencat.cat/ca/inici/")
    (synopsis
     "Datasets of the CEO (Centre d'Estudis d'Opinio) for Opinion Polls in Catalonia")
    (description
     "Easy and convenient access to the datasets of the \"Centre d'Estudis d'Opinio\",
the Catalan institution for polling and public opinion.  The package uses the
data stored in the servers of the CEO and returns it in a tidy format.")
    (license license:gpl3)))

(define-public r-centrifuger
  (package
    (name "r-centrifuger")
    (version "0.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "centrifugeR" version))
       (sha256
        (base32 "078rm1i1qqx15qj75yajc11zfsnp6mcb391v5vc0dl03xjzsiz7q"))))
    (properties `((upstream-name . "centrifugeR")))
    (build-system r-build-system)
    (propagated-inputs (list r-shinythemes r-shiny r-pracma))
    (home-page "https://phamdn.shinyapps.io/centrifugeR/")
    (synopsis "Non-Trivial Balance of Centrifuge Rotors")
    (description
     "Find the numbers of test tubes that can be balanced in centrifuge rotors and
show various ways to load them.  Refer to Pham (2020)
<doi:10.31224/osf.io/4xs38> for more information on package functionality.")
    (license license:gpl3)))

(define-public r-centr
  (package
    (name "r-centr")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "centr" version))
       (sha256
        (base32 "1hk30x8icgcr53gdn88nimvs80djl310l59hfknd1a8z60ccnpsi"))))
    (properties `((upstream-name . "centr")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf))
    (native-inputs (list r-knitr))
    (home-page "https://ryanzomorrodi.github.io/centr/")
    (synopsis "Weighted and Unweighted Spatial Centers")
    (description
     "Generate mean and median weighted or unweighted spatial centers.  Functions are
analogous to their identically named counterparts within @code{ArcGIS} Pro'.
Median center methodology based off of Kuhn and Kuenne (1962)
<doi:10.1111/j.1467-9787.1962.tb00902.x>.")
    (license license:expat)))

(define-public r-centiserve
  (package
    (name "r-centiserve")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "centiserve" version))
       (sha256
        (base32 "1m6gqz2rk7023340laa5pc0ncbfka2qi9ajvh65fwijd7xvv3n5c"))))
    (properties `((upstream-name . "centiserve")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-igraph))
    (home-page "http://www.centiserver.org/")
    (synopsis "Find Graph Centrality Indices")
    (description
     "Calculates centrality indices additional to the igraph package centrality
functions.")
    (license license:gpl2+)))

(define-public r-centerline
  (package
    (name "r-centerline")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "centerline" version))
       (sha256
        (base32 "00bpl7qz5hm69mnbi5278bx7v676ni8c3xyq3kmb7z7pzjgx3g83"))))
    (properties `((upstream-name . "centerline")))
    (build-system r-build-system)
    (propagated-inputs (list r-wk r-sfnetworks r-sf r-geos))
    (home-page "https://github.com/atsyplenkov/centerline")
    (synopsis "Extract Centerline from Closed Polygons")
    (description
     "Generates skeletons of closed 2D polygons using Voronoi diagrams.  It provides
methods for sf', terra', and geos objects to compute polygon centerlines based
on the generated skeletons.  Voronoi, G. (1908) <doi:10.1515/crll.1908.134.198>.")
    (license license:expat)))

(define-public r-censusr
  (package
    (name "r-censusr")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "censusr" version))
       (sha256
        (base32 "1n9571fyr46wj1dcxc2xgns9865655yzlq7yfz8im014wh0ycwqc"))))
    (properties `((upstream-name . "censusr")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-httr r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/transportfoundry/censusr")
    (synopsis "Collect Data from the Census API")
    (description
     "Use the US Census API to collect summary data tables for SF1 and ACS datasets at
arbitrary geographies.")
    (license license:expat)))

(define-public r-censusapi
  (package
    (name "r-censusapi")
    (version "0.8.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "censusapi" version))
       (sha256
        (base32 "1wswd6kmb0fbyc3zs3q3dhhaa1la1z5alz4vg485ac9wacnab60r"))))
    (properties `((upstream-name . "censusapi")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr))
    (home-page "https://www.hrecht.com/censusapi/")
    (synopsis "Retrieve Data from the Census APIs")
    (description
     "This package provides a wrapper for the U.S. Census Bureau APIs that returns
data frames of Census data and metadata.  Available datasets include the
Decennial Census, American Community Survey, Small Area Health Insurance
Estimates, Small Area Income and Poverty Estimates, Population Estimates and
Projections, and more.")
    (license license:gpl3)))

(define-public r-census2016
  (package
    (name "r-census2016")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Census2016" version))
       (sha256
        (base32 "1c88jmd565v19w8dbvai10f9y5lyfmzsxsjblc3gdykf9kharvcq"))))
    (properties `((upstream-name . "Census2016")))
    (build-system r-build-system)
    (propagated-inputs (list r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=Census2016")
    (synopsis "Data from the Australian Census 2016")
    (description
     "This package contains selected variables from the time series profiles for
statistical areas level 2 from the 2006, 2011, and 2016 censuses of population
and housing, Australia.  Also provides methods for viewing the questions asked
for convenience during analysis.")
    (license (license:fsdg-compatible "CC BY 4.0"))))

(define-public r-censspatial
  (package
    (name "r-censspatial")
    (version "3.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CensSpatial" version))
       (sha256
        (base32 "10jgr9zvdvm8fgh0llfsxjkd5f565i1qh00zrqxz55is7p4r3h35"))))
    (properties `((upstream-name . "CensSpatial")))
    (build-system r-build-system)
    (propagated-inputs (list r-tmvtnorm
                             r-tlrmvnmvt
                             r-rcpp
                             r-raster
                             r-psych
                             r-optimx
                             r-numderiv
                             r-mvtnorm
                             r-msm
                             r-moments
                             r-lattice
                             r-geor))
    (home-page "https://cran.r-project.org/package=CensSpatial")
    (synopsis "Censored Spatial Models")
    (description
     "It fits linear regression models for censored spatial data.  It provides
different estimation methods as the SAEM (Stochastic Approximation of
Expectation Maximization) algorithm and seminaive that uses Kriging prediction
to estimate the response at censored locations and predict new values at unknown
locations.  It also offers graphical tools for assessing the fitted model.  More
details can be found in Ordonez et al. (2018)
<doi:10.1016/j.spasta.2017.12.001>.")
    (license license:gpl2+)))

(define-public r-censreg
  (package
    (name "r-censreg")
    (version "0.5-38")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "censReg" version))
       (sha256
        (base32 "1rrgvq883970zp311lmkvxxky29w48p54xa4hq7iaa33yq7dbmmb"))))
    (properties `((upstream-name . "censReg")))
    (build-system r-build-system)
    (propagated-inputs (list r-sandwich r-plm r-misctools r-maxlik r-glmmml))
    (home-page "http://www.sampleSelection.org")
    (synopsis "Censored Regression (Tobit) Models")
    (description
     "Maximum Likelihood estimation of censored regression (Tobit) models with
cross-sectional and panel data.")
    (license license:gpl2+)))

(define-public r-censored
  (package
    (name "r-censored")
    (version "0.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "censored" version))
       (sha256
        (base32 "171bfny4d8p8i82xv0mj315imb9ghvn2jzvirqmkm6k0cxmaqyrz"))))
    (properties `((upstream-name . "censored")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-survival
                             r-rlang
                             r-purrr
                             r-prodlim
                             r-parsnip
                             r-mboost
                             r-lifecycle
                             r-hardhat
                             r-glue
                             r-generics
                             r-dplyr
                             r-dials
                             r-cli))
    (home-page "https://github.com/tidymodels/censored")
    (synopsis "'parsnip' Engines for Survival Models")
    (description
     "Engines for survival models from the parsnip package.  These include parametric
models (e.g., Jackson (2016) <doi:10.18637/jss.v070.i08>), semi-parametric
(e.g., Simon et al (2011) <doi:10.18637/jss.v039.i05>), and tree-based models
(e.g., Buehlmann and Hothorn (2007) <doi:10.1214/07-STS242>).")
    (license license:expat)))

(define-public r-censorcopula
  (package
    (name "r-censorcopula")
    (version "2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "censorcopula" version))
       (sha256
        (base32 "16pk4xlpliif02qznrhvl8qmrr6k4kknygqxcm83nsjxy6dcyga8"))))
    (properties `((upstream-name . "censorcopula")))
    (build-system r-build-system)
    (propagated-inputs (list r-copula))
    (home-page "https://cran.r-project.org/package=censorcopula")
    (synopsis "Estimate Parameter of Bivariate Copula")
    (description
     "Implement an interval censor method to break ties when using data with ties to
fitting a bivariate copula.")
    (license license:gpl2+)))

(define-public r-censobr
  (package
    (name "r-censobr")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "censobr" version))
       (sha256
        (base32 "1rgl8qbhrj0yv3gw6rqx0zj5gpwwhgfja28pcqmnkglyzf8d8i5n"))))
    (properties `((upstream-name . "censobr")))
    (build-system r-build-system)
    (propagated-inputs (list r-fs
                             r-duckplyr
                             r-duckdb
                             r-dplyr
                             r-dbi
                             r-curl
                             r-checkmate
                             r-arrow))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ipeaGIT/censobr")
    (synopsis "Download Data from Brazil's Population Census")
    (description
     "Easy access to data from Brazil's population censuses.  The package provides a
simple and efficient way to download and read the data sets and the
documentation of all the population censuses taken in and after 1960 in the
country.  The package is built on top of the Arrow platform
<https://arrow.apache.org/docs/r/>, which allows users to work with
larger-than-memory census data using dplyr familiar functions.
<https://arrow.apache.org/docs/r/articles/arrow.html#analyzing-arrow-data-with-dplyr>.")
    (license license:expat)))

(define-public r-censo2017
  (package
    (name "r-censo2017")
    (version "0.6.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "censo2017" version))
       (sha256
        (base32 "0rj3a9i6faqsrx641p1nacdprfnzp8q45khpdrakmfnc7l40xh87"))))
    (properties `((upstream-name . "censo2017")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-rstudioapi
                             r-purrr
                             r-httr
                             r-duckdb
                             r-dbi
                             r-crayon
                             r-cli))
    (home-page "https://docs.ropensci.org/censo2017/")
    (synopsis
     "Base de Datos de Facil Acceso del Censo 2017 de Chile (2017 Chilean Census Easy Access Database)")
    (description
     "Provee un acceso conveniente a mas de 17 millones de registros de la base de
datos del Censo 2017.  Los datos fueron importados desde el DVD oficial del INE
usando el Convertidor REDATAM creado por Pablo De Grande.  Esta paquete esta
documentado intencionalmente en castellano asciificado para que funcione sin
problema en diferentes plataformas. (Provides convenient access to more than 17
million records from the Chilean Census 2017 database.  The datasets were
imported from the official DVD provided by the Chilean National Bureau of
Statistics by using the REDATAM converter created by Pablo De Grande and in
addition it includes the maps accompanying these datasets.).")
    (license license:cc0)))

(define-public r-censmfm
  (package
    (name "r-censmfm")
    (version "3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CensMFM" version))
       (sha256
        (base32 "00z425r6ijs8zgmw0srcia9v90m57y2aq8zrlspgc5qf8kzxq1iv"))))
    (properties `((upstream-name . "CensMFM")))
    (build-system r-build-system)
    (propagated-inputs (list r-tlrmvnmvt r-mvtnorm r-momtrunc r-gridextra
                             r-ggplot2))
    (home-page "https://cran.r-project.org/package=CensMFM")
    (synopsis "Finite Mixture of Multivariate Censored/Missing Data")
    (description
     "It fits finite mixture models for censored or/and missing data using several
multivariate distributions.  Point estimation and asymptotic inference (via
empirical information matrix) are offered as well as censored data generation.
Pairwise scatter and contour plots can be generated.  Possible multivariate
distributions are the well-known normal, Student-t and skew-normal
distributions.  This package is an complement of Lachos, V. H., Moreno, E. J.
L., Chen, K. & Cabral, C. R. B. (2017) <doi:10.1016/j.jmva.2017.05.005> for the
multivariate skew-normal case.")
    (license license:gpl2+)))

(define-public r-censcov
  (package
    (name "r-censcov")
    (version "1.0-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "censCov" version))
       (sha256
        (base32 "0i9vmyi12f1m5xnrl4cxk3z9qv7ymzxsyf4gbnpg1ph63yfnhv3g"))))
    (properties `((upstream-name . "censCov")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival))
    (home-page "https://cran.r-project.org/package=censCov")
    (synopsis "Linear Regression with a Randomly Censored Covariate")
    (description
     "Implementations of threshold regression approaches for linear regression models
with a covariate subject to random censoring, including deletion threshold
regression and completion threshold regression.  Reverse survival regression,
which flip the role of response variable and the covariate, is also considered.")
    (license license:gpl3+)))

(define-public r-censable
  (package
    (name "r-censable")
    (version "0.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "censable" version))
       (sha256
        (base32 "15p4ggnkcddm2lglf798bcjghppx0pqzc8nyljyiw0hwsw14c7yg"))))
    (properties `((upstream-name . "censable")))
    (build-system r-build-system)
    (propagated-inputs (list r-tinytiger
                             r-tibble
                             r-stringr
                             r-sf
                             r-rlang
                             r-purrr
                             r-memoise
                             r-magrittr
                             r-dplyr
                             r-censusapi))
    (home-page "https://christophertkenny.com/censable/")
    (synopsis "Making Census Data More Usable")
    (description
     "This package creates a common framework for organizing, naming, and gathering
population, age, race, and ethnicity data from the Census Bureau.  Accesses the
API <https://www.census.gov/data/developers/data-sets.html>.  Provides tools for
adding information to existing data to line up with Census data.")
    (license license:expat)))

(define-public r-cenroc
  (package
    (name "r-cenroc")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cenROC" version))
       (sha256
        (base32 "1rgs1h32jm7ls830f62gi5wdaqx3q2h4m4qirxqmv0pi8y5y2a9v"))))
    (properties `((upstream-name . "cenROC")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rcppeigen r-rcpp r-icenreg
                             r-condsurv))
    (home-page "https://cran.r-project.org/package=cenROC")
    (synopsis "Estimating Time-Dependent ROC Curve and AUC for Censored Data")
    (description
     "This package contains functions to estimate a smoothed and a non-smoothed
(empirical) time-dependent receiver operating characteristic curve and the
corresponding area under the receiver operating characteristic curve and the
optimal cutoff point for the right and interval censored survival data.  See
Beyene and El Ghouch (2020)<doi:10.1002/sim.8671> and Beyene and El Ghouch
(2022) <doi:10.1002/bimj.202000382>.")
    (license license:gpl2+)))

(define-public r-cengam
  (package
    (name "r-cengam")
    (version "0.5.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cenGAM" version))
       (sha256
        (base32 "0qic2g2bq24k9jimxdk8g7bsmi4br2r6159ipdhh5ym81ji3sf5p"))))
    (properties `((upstream-name . "cenGAM")))
    (build-system r-build-system)
    (propagated-inputs (list r-mgcv))
    (home-page "https://cran.r-project.org/package=cenGAM")
    (synopsis "Censored Regression with Smooth Terms")
    (description
     "Implementation of Tobit type I and type II families for censored regression
using the mgcv package, based on methods detailed in Woods (2016)
<doi:10.1080/01621459.2016.1180986>.")
    (license license:gpl2+)))

(define-public r-cencrne
  (package
    (name "r-cencrne")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cencrne" version))
       (sha256
        (base32 "1s5d6k01wlxs248wf9k77qxwnvaivxzsighsfdmd1hrf0klbwy5z"))))
    (properties `((upstream-name . "cencrne")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-mass))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://cran.r-project.org/package=cencrne")
    (synopsis
     "Consistent Estimation of the Number of Communities via Regularized Network Embedding")
    (description
     "The network analysis plays an important role in numerous application domains
including biomedicine.  Estimation of the number of communities is a fundamental
and critical issue in network analysis.  Most existing studies assume that the
number of communities is known a priori, or lack of rigorous theoretical
guarantee on the estimation consistency.  This method proposes a regularized
network embedding model to simultaneously estimate the community structure and
the number of communities in a unified formulation.  The proposed model equips
network embedding with a novel composite regularization term, which pushes the
embedding vector towards its center and collapses similar community centers with
each other.  A rigorous theoretical analysis is conducted, establishing
asymptotic consistency in terms of community detection and estimation of the
number of communities.  Reference: Ren, M., Zhang S. and Wang J. (2022).
\"Consistent Estimation of the Number of Communities via Regularized Network
Embedding\".  Biometrics, <doi:10.1111/biom.13815>.")
    (license license:gpl2)))

(define-public r-cenbar
  (package
    (name "r-cenbar")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CenBAR" version))
       (sha256
        (base32 "1k8ycm2rzwadr5bg6m0ay81c5v4wjg04yigch6a1w7g75gw01q50"))))
    (properties `((upstream-name . "CenBAR")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-mvtnorm
                             r-mass
                             r-glmnet
                             r-foreach
                             r-cvtools))
    (home-page "https://cran.r-project.org/package=CenBAR")
    (synopsis "Broken Adaptive Ridge AFT Model with Censored Data")
    (description
     "Broken adaptive ridge estimator for censored data is used to select variables
and estimate their coefficients in the semi-parametric accelerated failure time
model for right-censored survival data.")
    (license license:gpl2)))

(define-public r-cemco
  (package
    (name "r-cemco")
    (version "0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cemco" version))
       (sha256
        (base32 "172raa62i34d1vzsgy84h3b7mmdzvg9h657fcmgrlhlkwqzx0gyl"))))
    (properties `((upstream-name . "cemco")))
    (build-system r-build-system)
    (propagated-inputs (list r-rootsolve
                             r-nnet
                             r-mvtnorm
                             r-mclust
                             r-mass
                             r-foreach
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=cemco")
    (synopsis "Fit 'CemCO' Algorithm")
    (description
     "@code{CemCO} algorithm, a model-based (Gaussian) clustering algorithm that
removes/minimizes the effects of undesirable covariates during the clustering
process both in cluster centroids and in cluster covariance structures (Relvas
C. & Fujita A., (2020) <@code{arXiv:2004.02333>}).")
    (license license:gpl2+)))

(define-public r-cem
  (package
    (name "r-cem")
    (version "1.1.31")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cem" version))
       (sha256
        (base32 "1ylzsx2km9lf3x1rchwgs3nd8dzrac81f2jnd4qri35zvlilh1c6"))))
    (properties `((upstream-name . "cem")))
    (build-system r-build-system)
    (propagated-inputs (list r-randomforest r-nlme r-matchit r-lattice
                             r-combinat))
    (home-page "https://gking.harvard.edu/cem")
    (synopsis "Coarsened Exact Matching")
    (description
     "Implementation of the Coarsened Exact Matching algorithm discussed along with
its properties in Iacus, King, Porro (2011) <DOI:10.1198/jasa.2011.tm09599>;
Iacus, King, Porro (2012) <DOI:10.1093/pan/mpr013> and Iacus, King, Porro (2019)
<DOI:10.1017/pan.2018.29>.")
    (license license:gpl2)))

(define-public r-cellwise
  (package
    (name "r-cellwise")
    (version "2.5.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cellWise" version))
       (sha256
        (base32 "0asimy253lxm9yf47pynhxc7sfd3v5rkvnyf1sby7s4qkz06bh49"))))
    (properties `((upstream-name . "cellWise")))
    (build-system r-build-system)
    (propagated-inputs (list r-svd
                             r-shape
                             r-scales
                             r-rrcov
                             r-robustbase
                             r-reshape2
                             r-rcpparmadillo
                             r-rcpp
                             r-matrixstats
                             r-gridextra
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cellWise")
    (synopsis "Analyzing Data with Cellwise Outliers")
    (description
     "This package provides tools for detecting cellwise outliers and robust methods
to analyze data which may contain them.  Contains the implementation of the
algorithms described in Rousseeuw and Van den Bossche (2018)
<doi:10.1080/00401706.2017.1340909> (open access) Hubert et al. (2019)
<doi:10.1080/00401706.2018.1562989> (open access), Raymaekers and Rousseeuw
(2021) <doi:10.1080/00401706.2019.1677270> (open access), Raymaekers and
Rousseeuw (2021) <doi:10.1007/s10994-021-05960-5> (open access), Raymaekers and
Rousseeuw (2021) <doi:10.52933/jdssv.v1i3.18> (open access), Raymaekers and
Rousseeuw (2022) <@code{arXiv:2207.13493>} (open access) Rousseeuw (2022)
<doi:10.1016/j.ecosta.2023.01.007> (open access).  Examples can be found in the
vignettes: \"DDC_examples\", \"@code{MacroPCA_examples}\", \"wrap_examples\",
\"transfo_examples\", \"DI_examples\", \"@code{cellMCD_examples}\" ,
\"Correspondence_analysis_examples\", and \"cellwise_weights_examples\".")
    (license license:gpl2+)))

(define-public r-cellvolumedist
  (package
    (name "r-cellvolumedist")
    (version "1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cellVolumeDist" version))
       (sha256
        (base32 "1pbssq8zf1cmihs3fg5zgb3k876magxl84jld6vcfvvp76sxhr7l"))))
    (properties `((upstream-name . "cellVolumeDist")))
    (build-system r-build-system)
    (propagated-inputs (list r-minpack-lm r-gplots))
    (home-page "https://cran.r-project.org/package=cellVolumeDist")
    (synopsis
     "Functions to Fit Cell Volume Distributions and Thereby Estimate Cell Growth Rates and Division Times")
    (description
     "This package implements a methodology for using cell volume distributions to
estimate cell growth rates and division times that is described in the paper
entitled, \"Cell Volume Distributions Reveal Cell Growth Rates and Division
Times\", by Michael Halter, John T. Elliott, Joseph B. Hubbard, Alessandro Tona
and Anne L. Plant, which is in press in the Journal of Theoretical Biology.  In
order to reproduce the analysis used to obtain Table 1 in the paper, execute the
command \"example(@code{fitVolDist})\".")
    (license license:gpl2+)))

(define-public r-celltrackr
  (package
    (name "r-celltrackr")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "celltrackR" version))
       (sha256
        (base32 "0gmdxs9s3c1rk8mqc2pp6zdmzy9nij51m29vf24ii8s201f9raj6"))))
    (properties `((upstream-name . "celltrackR")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma r-ellipse))
    (native-inputs (list r-knitr))
    (home-page "http://www.motilitylab.net")
    (synopsis "Motion Trajectory Analysis")
    (description
     "This package provides methods for analyzing (cell) motion in two or three
dimensions.  Available measures include displacement, confinement ratio,
autocorrelation, straightness, turning angle, and fractal dimension.  Measures
can be applied to entire tracks, steps, or subtracks with varying length.  While
the methodology has been developed for cell trajectory analysis, it is
applicable to anything that moves including animals, people, or vehicles.  Some
of the methodology implemented in this packages was described by: Beauchemin,
Dixit, and Perelson (2007) <doi:10.4049/jimmunol.178.9.5505>, Beltman, Maree,
and de Boer (2009) <doi:10.1038/nri2638>, Gneiting and Schlather (2004)
<doi:10.1137/S0036144501394387>, Mokhtari, Mech, Zitzmann, Hasenberg, Gunzer,
and Figge (2013) <doi:10.1371/journal.pone.0080808>, Moreau, Lemaitre, Terriac,
Azar, Piel, Lennon-Dumenil, and Bousso (2012)
<doi:10.1016/j.immuni.2012.05.014>, Textor, Peixoto, Henrickson, Sinn, von
Andrian, and Westermann (2011) <doi:10.1073/pnas.1102288108>, Textor, Sinn, and
de Boer (2013) <doi:10.1186/1471-2105-14-S6-S10>, Textor, Henrickson, Mandl, von
Andrian, Westermann, de Boer, and Beltman (2014)
<doi:10.1371/journal.pcbi.1003752>.")
    (license license:gpl2)))

(define-public r-cellpypes
  (package
    (name "r-cellpypes")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cellpypes" version))
       (sha256
        (base32 "1px7p1xly71p48w72m5fcs2krxba72slnh638wpd98a52clbgz6l"))))
    (properties `((upstream-name . "cellpypes")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis
                             r-scutils
                             r-scattermore
                             r-scales
                             r-rlang
                             r-matrix
                             r-ggplot2
                             r-dplyr
                             r-cowplot))
    (home-page "https://github.com/FelixTheStudent/cellpypes")
    (synopsis "Cell Type Pipes for Single-Cell RNA Sequencing Data")
    (description
     "Annotate single-cell RNA sequencing data manually based on marker gene
thresholds.  Find cell type rules (gene+threshold) through exploration, use the
popular piping operator %>% to reconstruct complex cell type hierarchies.
cellpypes models technical noise to find positive and negative cells for a given
expression threshold and returns cell type labels or pseudobulks.  Cite this
package as Frauhammer (2022) <doi:10.5281/zenodo.6555728> and visit
<https://github.com/@code{FelixTheStudent/cellpypes>} for tutorials and newest
features.")
    (license license:gpl3+)))

(define-public r-cellorigins
  (package
    (name "r-cellorigins")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cellOrigins" version))
       (sha256
        (base32 "0nxhyz9bz0f598wpr10hm1d0zx83450xf9jkrl279v46x8sx36n4"))))
    (properties `((upstream-name . "cellOrigins")))
    (build-system r-build-system)
    (propagated-inputs (list r-iterpc))
    (home-page "https://cran.r-project.org/package=cellOrigins")
    (synopsis "Finds RNASeq Source Tissues Using In Situ Hybridisation Data")
    (description
     "Finds the most likely originating tissue(s) and developmental stage(s) of
tissue-specific RNA sequencing data.  The package identifies both pure
transcriptomes and mixtures of transcriptomes.  The most likely identity is
found through comparisons of the sequencing data with high-throughput in situ
hybridisation patterns.  Typical uses are the identification of cancer cell
origins, validation of cell culture strain identities, validation of single-cell
transcriptomes, and validation of identity and purity of flow-sorting and
dissection sequencing products.")
    (license (license:fsdg-compatible "CC BY-NC-SA 4.0"))))

(define-public r-cellkey
  (package
    (name "r-cellkey")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cellKey" version))
       (sha256
        (base32 "1brl0747mr9wpk0q299d55z94zhq2783nad1lanm5ia39r0x8i22"))))
    (properties `((upstream-name . "cellKey")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-sdctable
                             r-sdchierarchies
                             r-rlang
                             r-ptable
                             r-digest
                             r-data-table
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/sdcTools/cellKey")
    (synopsis
     "Consistent Perturbation of Statistical Frequency- And Magnitude Tables")
    (description
     "Data from statistical agencies and other institutions often need to be protected
before they can be published.  This package can be used to perturb statistical
tables in a consistent way.  The main idea is to add - at the micro data level -
a record key for each unit.  Based on these keys, for any cell in a statistical
table a cell key is computed as a function on the record keys contributing to a
specific cell.  Values that are added to the cell in order to perturb it are
derived from a lookup-table that maps values of cell keys to specific
perturbation values.  The theoretical basis for the methods implemented can be
found in Thompson, Broadfoot and Elazar (2013)
<https://unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.46/2013/Topic_1_ABS.pdf>
which was extended and enhanced by Giessing and Tent (2019)
<https://unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.46/2019/mtg1/SDC2019_S2_Germany_Giessing_Tent_AD.pdf>.")
    (license license:gpl2)))

(define-public r-cego
  (package
    (name "r-cego")
    (version "2.4.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CEGO" version))
       (sha256
        (base32 "0pr3mkygnwcaslf0z8np7vhf7y70l9xqbx61bp98my5gq8gfzcxg"))))
    (properties `((upstream-name . "CEGO")))
    (build-system r-build-system)
    (propagated-inputs (list r-quadprog
                             r-paramhelpers
                             r-matrix
                             r-mass
                             r-fastmatch
                             r-deoptim
                             r-anticlust))
    (home-page "https://cran.r-project.org/package=CEGO")
    (synopsis "Combinatorial Efficient Global Optimization")
    (description
     "Model building, surrogate model based optimization and Efficient Global
Optimization in combinatorial or mixed search spaces.")
    (license license:gpl3+)))

(define-public r-ceg
  (package
    (name "r-ceg")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ceg" version))
       (sha256
        (base32 "01la7kv0a3inc9vy5x010ysicfiv404bqfgs8csvqixviap9rd74"))))
    (properties `((upstream-name . "ceg")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgraphviz r-graph))
    (home-page "https://github.com/ptaranti/ceg")
    (synopsis "Chain Event Graph")
    (description
     "Create and learn Chain Event Graph (CEG) models using a Bayesian framework.  It
provides us with a Hierarchical Agglomerative algorithm to search the CEG model
space.  The package also includes several facilities for visualisations of the
objects associated with a CEG. The CEG class can represent a range of relational
data types, and supports arbitrary vertex, edge and graph attributes.  A Chain
Event Graph is a tree-based graphical model that provides a powerful graphical
interface through which domain experts can easily translate a process into
sequences of observed events using plain language.  CEGs have been a useful
class of graphical model especially to capture context-specific conditional
independences.  References: Collazo R, Gorgen C, Smith J. Chain Event Graph.
CRC Press, ISBN 9781498729604, 2018 (forthcoming); and Barday LM, Collazo RA,
Smith JQ, Thwaites PA, Nicholson AE. The Dynamic Chain Event Graph.  Electronic
Journal of Statistics, 9 (2) 2130-2169 <doi:10.1214/15-EJS1068>.")
    (license (list license:gpl2
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-ceemdanml
  (package
    (name "r-ceemdanml")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CEEMDANML" version))
       (sha256
        (base32 "0hc5sx1zvxj3j5psgcgzhw6l9zrvbbsnpw6qr7ww82bjjr3wbi3c"))))
    (properties `((upstream-name . "CEEMDANML")))
    (build-system r-build-system)
    (propagated-inputs (list r-tseries
                             r-rlibeemd
                             r-pso
                             r-neuralnet
                             r-lsts
                             r-forecast
                             r-fints
                             r-fgarch
                             r-earth
                             r-e1071
                             r-caret
                             r-atsa))
    (home-page "https://cran.r-project.org/package=CEEMDANML")
    (synopsis "CEEMDAN Decomposition Based Hybrid Machine Learning Models")
    (description
     "Noise in the time-series data significantly affects the accuracy of the Machine
Learning (ML) models (Artificial Neural Network and Support Vector Regression
are considered here).  Complete Ensemble Empirical Mode Decomposition with
Adaptive Noise (CEEMDAN) decomposes the time series data into sub-series and
help to improve the model performance.  The models can achieve higher prediction
accuracy than the traditional ML models.  Two models have been provided here for
time series forecasting.  More information may be obtained from Garai and Paul
(2023) <doi:10.1016/j.iswa.2023.200202>.")
    (license license:gpl3)))

(define-public r-ceda
  (package
    (name "r-ceda")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CEDA" version))
       (sha256
        (base32 "1bpqlqak48crqsz3sg6qcli1f3vhn38p421wcigfvd5f1hm3gdvg"))))
    (properties `((upstream-name . "CEDA")))
    (build-system r-build-system)
    (propagated-inputs (list r-mixtools
                             r-limma
                             r-ggsci
                             r-ggridges
                             r-ggprism
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://cran.r-project.org/package=CEDA")
    (synopsis "CRISPR Screen and Gene Expression Differential Analysis")
    (description
     "This package provides analytical methods for analyzing CRISPR screen data at
different levels of gene expression.  Multi-component normal mixture models and
EM algorithms are used for modeling.")
    (license license:asl2.0)))

(define-public r-cec
  (package
    (name "r-cec")
    (version "0.11.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CEC" version))
       (sha256
        (base32 "17s3npc7bm18f95rcly6sp15f8bjvf5zsjcms6wdrlcybx7pn42v"))))
    (properties `((upstream-name . "CEC")))
    (build-system r-build-system)
    (home-page "https://github.com/swarm-lab/cec")
    (synopsis "Cross-Entropy Clustering")
    (description
     "Splits data into Gaussian type clusters using the Cross-Entropy Clustering
('CEC') method.  This method allows for the simultaneous use of various types of
Gaussian mixture models, for performing the reduction of unnecessary clusters,
and for discovering new clusters by splitting them.  CEC is based on the work of
Spurek, P. and Tabor, J. (2014) <doi:10.1016/j.patcog.2014.03.006>.")
    (license license:gpl3)))

(define-public r-ceas
  (package
    (name "r-ceas")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ceas" version))
       (sha256
        (base32 "0xxinxavqkfg3zfl62mz64msivr5j8l88sshqc1z56kxldyv0xfn"))))
    (properties `((upstream-name . "ceas")))
    (build-system r-build-system)
    (propagated-inputs (list r-readxl r-ggplot2 r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://jamespeapen.github.io/ceas/")
    (synopsis "Cellular Energetics Analysis Software")
    (description
     "Analysis and visualization of cellular energetics data from Agilent Seahorse
XF96.  Cellular energetics is how cells make, use, and distribute units of
energy (primarily ATP).  Measuring real-time cellular energetics is essential to
understanding a tissue or cellâs bioenergetic state and fuel dependencies.
The Seahorse machine measures a cellâs or matrixâs oxygen consumption rate
(OCR) â a proxy of oxidative phosphorylation â and extracellular
acidification rate â a proxy of glycolysis.  This package offers flexible and
fast analysis and plotting capabilities for such data using the methods
described by Mookerjee et al. (2017) <doi:10.1074/jbc.m116.774471>.")
    (license license:expat)))

(define-public r-cdvinecopulaconditional
  (package
    (name "r-cdvinecopulaconditional")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CDVineCopulaConditional" version))
       (sha256
        (base32 "1wyy324vrwipdsq0p021bj1gdhyxg09g3dkw8wv5v6rfrrs84m9k"))))
    (properties `((upstream-name . "CDVineCopulaConditional")))
    (build-system r-build-system)
    (propagated-inputs (list r-vinecopula r-combinat))
    (home-page "https://cran.r-project.org/package=CDVineCopulaConditional")
    (synopsis "Sampling from Conditional C- and D-Vine Copulas")
    (description
     "This package provides tools for sampling from a conditional copula density
decomposed via Pair-Copula Constructions as C- or D- vine.  Here, the vines
which can be used for such a sampling are those which sample as first the
conditioning variables (when following the sampling algorithms shown in Aas et
al. (2009) <DOI:10.1016/j.insmatheco.2007.02.001>).  The used sampling algorithm
is presented and discussed in Bevacqua et al. (2017)
<DOI:10.5194/hess-2016-652>, and it is a modified version of that from Aas et
al. (2009) <DOI:10.1016/j.insmatheco.2007.02.001>.  A function is available to
select the best vine (based on information criteria) among those which allow for
such a conditional sampling.  The package includes a function to compare
scatterplot matrices and pair-dependencies of two multivariate datasets.")
    (license license:gpl2+)))

(define-public r-cdvi
  (package
    (name "r-cdvi")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CDVI" version))
       (sha256
        (base32 "1q8f1smj07jnzgp7p2yfviz6wvrlvi5dx7sh4x09yzqfca5v8g46"))))
    (properties `((upstream-name . "CDVI")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CDVI")
    (synopsis
     "Cuddy-Della Valle Index for Capturing the Instability in Time Series Data")
    (description
     "Cuddy-Della valle index gives the degree of instability present in the data by
accommodating the effect of a trend.  The adjusted R squared value of the best
fitted model is chosen.  The index is obtained by multiplying the coefficient of
variation with square root of one minus the adjusted R-squared value.  This
package has been developed using concept of Shankar et al.
(2022)<doi:10.3389/fsufs.2023.1208898>.")
    (license license:gpl3)))

(define-public r-cdss
  (package
    (name "r-cdss")
    (version "0.2-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CDSS" version))
       (sha256
        (base32 "13p5vg07lv1vbwpsd33x4mc8pvwf6s6yqikrbyakrfsjlznzw5gj"))))
    (properties `((upstream-name . "CDSS")))
    (build-system r-build-system)
    (propagated-inputs (list r-readods r-openxlsx))
    (home-page "https://cran.r-project.org/package=CDSS")
    (synopsis "Course-Dependent Skill Structures")
    (description
     "Deriving skill structures from skill assignment data for courses (sets of
learning objects).")
    (license license:gpl3)))

(define-public r-cdse
  (package
    (name "r-cdse")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CDSE" version))
       (sha256
        (base32 "02hrgp5ir4sihfa9hzv1bnavzpmf6fzdz4w9bbq3cxqmn1wbm4i2"))))
    (properties `((upstream-name . "CDSE")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra
                             r-sf
                             r-lutz
                             r-lubridate
                             r-jsonlite
                             r-httr2
                             r-geojsonsf))
    (home-page "https://zivankaraman.github.io/CDSE/")
    (synopsis "'Copernicus Data Space Ecosystem' API Wrapper")
    (description
     "This package provides interface to the Copernicus Data Space Ecosystem API
<https://dataspace.copernicus.eu/analyse/apis>, mainly for searching the catalog
of available data from Copernicus Sentinel missions and obtaining the images for
just the area of interest based on selected spectral bands.  The package uses
the Sentinel Hub REST API interface
<https://dataspace.copernicus.eu/analyse/apis/sentinel-hub> that provides access
to various satellite imagery archives.  It allows you to access raw satellite
data, rendered images, statistical analysis, and other features.  This package
is in no way officially related to or endorsed by Copernicus.")
    (license license:agpl3)))

(define-public r-cdsampling
  (package
    (name "r-cdsampling")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CDsampling" version))
       (sha256
        (base32 "17npsagvgw47bfi9y2gbdx5dr688bbsxrq8rmay0x2la0xqil445"))))
    (properties `((upstream-name . "CDsampling")))
    (build-system r-build-system)
    (propagated-inputs (list r-rglpk r-lpsolve))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CDsampling")
    (synopsis "'CDsampling': Constraint Sampling in Paid Research Studies")
    (description
     "In the context of paid research studies and clinical trials, budget
considerations and patient sampling from available populations are subject to
inherent constraints.  We introduce the CDsampling package, which integrates
optimal design theories within the framework of constrained sampling.  This
package offers the possibility to find both D-optimal approximate and exact
allocations for samplings with or without constraints.  Additionally, it
provides functions to find constrained uniform sampling as a robust sampling
strategy with limited model information.  Our package offers functions for the
computation of the Fisher information matrix under generalized linear models
(including regular linear regression model) and multinomial logistic models.To
demonstrate the applications, we also provide a simulated dataset and a real
dataset embedded in the package.  Yifei Huang, Liping Tong, and Jie Yang
(2025)<doi:10.5705/ss.202022.0414>.")
    (license license:expat)))

(define-public r-cds
  (package
    (name "r-cds")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cds" version))
       (sha256
        (base32 "1h34k96h7ajkaqsw4dlqri63hrbnshaqwrdl74wlgycdlbvrqj05"))))
    (properties `((upstream-name . "cds")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-limsolve r-copula r-colorspace r-clue))
    (home-page "https://cran.r-project.org/package=cds")
    (synopsis "Constrained Dual Scaling for Detecting Response Styles")
    (description
     "This is an implementation of constrained dual scaling for detecting response
styles in categorical data, including utility functions.  The procedure involves
adding additional columns to the data matrix representing the boundaries between
the rating categories.  The resulting matrix is then doubled and analyzed by
dual scaling.  One-dimensional solutions are sought which provide optimal scores
for the rating categories.  These optimal scores are constrained to follow
monotone quadratic splines.  Clusters are introduced within which the response
styles can vary.  The type of response style present in a cluster can be
diagnosed from the optimal scores for said cluster, and this can be used to
construct an imputed version of the data set which adjusts for response styles.")
    (license license:gpl2+)))

(define-public r-cdrcr
  (package
    (name "r-cdrcr")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cdrcR" version))
       (sha256
        (base32 "13fd936by6b47hlbwidv0jdqav6c4r2llgf3cajvivlpi98vk7c7"))))
    (properties `((upstream-name . "cdrcR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-sf
                             r-rlist
                             r-rlang
                             r-rjson
                             r-purrr
                             r-magrittr
                             r-jsonlite
                             r-httr
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=cdrcR")
    (synopsis "Load 'CDRC' Data")
    (description
     "This package provides a wrapper for the CDRC API that returns data frames or sf
of CDRC data.  The API web reference
is:<https://api.cdrc.ac.uk/swagger/index.html>.")
    (license license:gpl3)))

(define-public r-cdparcoord
  (package
    (name "r-cdparcoord")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cdparcoord" version))
       (sha256
        (base32 "0ym2ypw4bsvmx9q4vskrq4pdd92y47vs8pay8san40rgzwqr2agb"))))
    (properties `((upstream-name . "cdparcoord")))
    (build-system r-build-system)
    (propagated-inputs (list r-plotly r-partools r-freqparcoord r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cdparcoord")
    (synopsis "Top Frequency-Based Parallel Coordinates")
    (description
     "Parallel coordinate plotting with resolutions for large data sets and missing
values.")
    (license license:gpl2+)))

(define-public r-cdom
  (package
    (name "r-cdom")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cdom" version))
       (sha256
        (base32 "00xqqqhskjlkz8ii7kqyabxk8995w7g9jiz1isyqjpwg8nsa3x28"))))
    (properties `((upstream-name . "cdom")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-minpack-lm r-ggplot2 r-broom))
    (home-page "https://github.com/PMassicotte/cdom")
    (synopsis "R Functions to Model CDOM Spectra")
    (description
     "Wrapper functions to model and extract various quantitative information from
absorption spectra of chromophoric dissolved organic matter (CDOM).")
    (license license:gpl2+)))

(define-public r-cdmtools
  (package
    (name "r-cdmtools")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cdmTools" version))
       (sha256
        (base32 "0nd15lr8hdin8qnxykway70irvfi239rm4jx3ck253l7igswiz7s"))))
    (properties `((upstream-name . "cdmTools")))
    (build-system r-build-system)
    (propagated-inputs (list r-sirt
                             r-psych
                             r-gparotation
                             r-ggplot2
                             r-gdina
                             r-fungible
                             r-foreach
                             r-dosnow
                             r-combinat))
    (home-page "https://github.com/pablo-najera/cdmTools")
    (synopsis "Useful Tools for Cognitive Diagnosis Modeling")
    (description
     "This package provides useful tools for cognitive diagnosis modeling (CDM).  The
package includes functions for empirical Q-matrix estimation and validation,
such as the Hull method (NÃ¡jera, Sorrel, de la Torre, & Abad, 2021,
<doi:10.1111/bmsp.12228>) and the discrete factor loading method (Wang, Song, &
Ding, 2018, <doi:10.1007/978-3-319-77249-3_29>).  It also contains
dimensionality assessment procedures for CDM, including parallel analysis and
automated fit comparison as explored in NÃ¡jera, Abad, and Sorrel (2021,
<doi:10.3389/fpsyg.2021.614470>).  Other relevant methods and features for CDM
applications, such as the restricted DINA model (NÃ¡jera et al., 2023;
<doi:10.3102/10769986231158829>), the general nonparametric classification
method (Chiu et al., 2018; <doi:10.1007/s11336-017-9595-4>), and corrected
estimation of the classification accuracy via multiple imputation (Kreitchmann
et al., 2022; <doi:10.3758/s13428-022-01967-5>) are also available.  Lastly, the
package provides some useful functions for CDM simulation studies, such as
random Q-matrix generation and detection of complete/identified Q-matrices.")
    (license license:gpl3)))

(define-public r-cdmconnector
  (package
    (name "r-cdmconnector")
    (version "1.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CDMConnector" version))
       (sha256
        (base32 "1ma5hjldcnsw6h007s1yyzv5iix8z8vz5yfxx5g3z74kwlpa4jjy"))))
    (properties `((upstream-name . "CDMConnector")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr
                             r-waldo
                             r-tidyselect
                             r-tidyr
                             r-stringr
                             r-stringi
                             r-rlang
                             r-readr
                             r-purrr
                             r-omopgenerics
                             r-lifecycle
                             r-jsonlite
                             r-glue
                             r-generics
                             r-fs
                             r-dplyr
                             r-dbplyr
                             r-dbi
                             r-cli
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://darwin-eu.github.io/CDMConnector/")
    (synopsis "Connect to an OMOP Common Data Model")
    (description
     "This package provides tools for working with observational health data in the
Observational Medical Outcomes Partnership (OMOP) Common Data Model format with
a pipe friendly syntax.  Common data model database table references are stored
in a single compound object along with metadata.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-cdltools
  (package
    (name "r-cdltools")
    (version "1.13")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cdlTools" version))
       (sha256
        (base32 "0cxk4n0csg64479bz8xrpfg8mixwx7pb5sl5gwkrkl6pd256rw86"))))
    (properties `((upstream-name . "cdlTools")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra r-stringr r-rvest r-raster r-httr))
    (home-page "https://github.com/jlisic/cdlTools")
    (synopsis "Tools to Download and Work with USDA Cropscape Data")
    (description
     "Downloads USDA National Agricultural Statistics Service (NASS) cropscape data
for a specified state.  Utilities for fips, abbreviation, and name conversion
are also provided.  Full functionality requires an internet connection, but data
sets can be cached for later off-line use.")
    (license (license:fsdg-compatible "Unlimited"))))

(define-public r-cdlei
  (package
    (name "r-cdlei")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cdlei" version))
       (sha256
        (base32 "1zsgryrwr1nqhcyizrh67lm953b87ih9l4rvc6i59s4vg2ph1ph1"))))
    (properties `((upstream-name . "cdlei")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cdlei")
    (synopsis "Cause-Deleted Life Expectancy Improvement Procedure")
    (description
     "The concept of cause-deleted life expectancy improvement is statistic designed
to quantify the increase in life expectancy if a certain cause of death is
removed.  See Adamic, P. (2015)
(<https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2689352>).")
    (license license:gpl2)))

(define-public r-cdghmm
  (package
    (name "r-cdghmm")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CDGHMM" version))
       (sha256
        (base32 "18gf8p5h006h125dfygghxbkdbg26p77k632l2plhrpcgd3iszbw"))))
    (properties `((upstream-name . "CDGHMM")))
    (build-system r-build-system)
    (propagated-inputs (list r-ramify r-mvtnorm r-mass r-cluster))
    (home-page "https://cran.r-project.org/package=CDGHMM")
    (synopsis "Hidden Markov Models for Multivariate Panel Data")
    (description
     "Estimates hidden Markov models from the family of Cholesky-decomposed Gaussian
hidden Markov models (CDGHMM) under various missingness schemes.  This family
improves upon estimation of traditional Gaussian HMMs by directly modelling the
distinct correlation structures that arise from longitudinal data, as well as,
controlling for dropped out observations and non-random missingness.  See Neal,
Sochaniwsky and @code{McNicholas} (2024) <DOI:10.48550/@code{arXiv.2404.04122>}.")
    (license license:gpl2+)))

(define-public r-cdgd
  (package
    (name "r-cdgd")
    (version "0.3.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cdgd" version))
       (sha256
        (base32 "10cd1s06k2hcvzjsibz1nask7n22x98s0cpi1j0l974s1j426wzy"))))
    (properties `((upstream-name . "cdgd")))
    (build-system r-build-system)
    (propagated-inputs (list r-caret))
    (home-page "https://github.com/ang-yu/cdgd")
    (synopsis "Causal Decomposition of Group Disparities")
    (description
     "The framework of causal decomposition of group disparities developed by Yu and
Elwert (2023) <doi:10.48550/@code{arXiv.2306.16591>}.  This package implements
the decomposition estimators that are based on efficient influence functions.
For the nuisance functions of the estimators, both parametric and nonparametric
options are provided, as well as manual options in case the default models are
not satisfying.")
    (license license:expat)))

(define-public r-cdft
  (package
    (name "r-cdft")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CDFt" version))
       (sha256
        (base32 "19axaf3bh9gasnsfamd5ych1jn751scaplgwpmsf3liazcqqpa61"))))
    (properties `((upstream-name . "CDFt")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CDFt")
    (synopsis
     "Downscaling and Bias Correction via Non-Parametric CDF-Transform")
    (description
     "Statistical downscaling and bias correction (model output statistics) method
based on cumulative distribution functions (CDF) transformation.  See
Michelangeli, Vrac, Loukos (2009) Probabilistic downscaling approaches:
Application to wind cumulative distribution functions.  Geophysical Research
Letters, 36, L11708, <doi:10.1029/2009GL038401>. ; and Vrac, Drobinski, Merlo,
Herrmann, Lavaysse, Li, Somot (2012) Dynamical and statistical downscaling of
the French Mediterranean climate: uncertainty assessment.  Nat.  Hazards Earth
Syst.  Sci., 12, 2769-2784, www.nat-hazards-earth-syst-sci.net/12/2769/2012/,
<doi:10.5194/nhess-12-2769-2012>.")
    (license license:gpl2+)))

(define-public r-cdfquantreg
  (package
    (name "r-cdfquantreg")
    (version "1.3.1-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cdfquantreg" version))
       (sha256
        (base32 "1abbr14fqn56c4yqrz1qbzq03xl5qi6px29wljd3yzysypvh9his"))))
    (properties `((upstream-name . "cdfquantreg")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma r-mass r-formula))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cdfquantreg")
    (synopsis "Quantile Regression for Random Variables on the Unit Interval")
    (description
     "Employs a two-parameter family of distributions for modelling random variables
on the (0, 1) interval by applying the cumulative distribution function (cdf) of
one parent distribution to the quantile function of another.")
    (license license:gpl3)))

(define-public r-cder
  (package
    (name "r-cder")
    (version "0.3-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cder" version))
       (sha256
        (base32 "0h44yifiy0fqrmfpri0had1ps5d1jj1dgwllha5ng04rjwlvxpzz"))))
    (properties `((upstream-name . "cder")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-readr
                             r-lubridate
                             r-glue
                             r-dplyr
                             r-curl))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mkoohafkan/cder")
    (synopsis "Interface to the California Data Exchange Center (CDEC)")
    (description
     "Connect to the California Data Exchange Center (CDEC) Web Service
<http://cdec.water.ca.gov/>.  CDEC provides a centralized database to store,
process, and exchange real-time hydrologic information gathered by various
cooperators throughout California.  The CDEC Web Service
<http://cdec.water.ca.gov/dynamicapp/@code{wsSensorData>} provides a data
download service for accessing historical records.")
    (license license:gpl3+)))

(define-public r-cdcsis
  (package
    (name "r-cdcsis")
    (version "2.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cdcsis" version))
       (sha256
        (base32 "1vxhikdx4kqac29spzwwv696kax5fsdmmhnqgm8gjk538zq6kw4f"))))
    (properties `((upstream-name . "cdcsis")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-mvtnorm r-ks))
    (home-page "https://github.com/Mamba413/cdcsis")
    (synopsis
     "Conditional Distance Correlation Based Feature Screening and Conditional Independence Inference")
    (description
     "Conditional distance correlation <doi:10.1080/01621459.2014.993081> is a novel
conditional dependence measurement of two multivariate random variables given a
confounding variable.  This package provides conditional distance correlation,
performs the conditional distance correlation sure independence screening
procedure for ultrahigh dimensional data
<https://www3.stat.sinica.edu.tw/statistica/J28N1/J28N114/J28N114.html>, and
conducts conditional distance covariance test for conditional independence
assumption of two multivariate variable.")
    (license license:gpl2+)))

(define-public r-cdcplaces
  (package
    (name "r-cdcplaces")
    (version "1.1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CDCPLACES" version))
       (sha256
        (base32 "1hy6x2qicf1k7p00hpagm03h79xvw1d2wk04v74c4hlxxczyz29n"))))
    (properties `((upstream-name . "CDCPLACES")))
    (build-system r-build-system)
    (propagated-inputs (list r-zctacrosswalk r-yyjsonr r-tigris r-sf r-curl))
    (home-page "https://github.com/brendensm/CDCPLACES")
    (synopsis "Access the 'CDC PLACES' API")
    (description
     "Allows users to seamlessly query several CDC PLACES APIs
(<https://data.cdc.gov/browse?q=PLACES%20&@code{sortBy=relevance>}) by
geography, state, measure, and release year.  This package also contains a
function to explore the available measures for each release year.")
    (license license:expat)))

(define-public r-cdcatr
  (package
    (name "r-cdcatr")
    (version "1.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cdcatR" version))
       (sha256
        (base32 "168gs1v1a6pcz63q3hb1dc4mlllr38j91m91phb75np8hxfz2k2v"))))
    (properties `((upstream-name . "cdcatR")))
    (build-system r-build-system)
    (propagated-inputs (list r-npcd
                             r-ggplot2
                             r-gdina
                             r-foreach
                             r-dosnow
                             r-cowplot
                             r-cdmtools))
    (home-page "https://github.com/miguel-sorrel/cdcatR")
    (synopsis "Cognitive Diagnostic Computerized Adaptive Testing")
    (description
     "This package provides a set of functions for conducting cognitive diagnostic
computerized adaptive testing applications (Chen, 2009)
<DOI:10.1007/s11336-009-9123-2>).  It includes different item selection rules
such us the global discrimination index (Kaplan, de la Torre, and Barrada (2015)
<DOI:10.1177/0146621614554650>) and the nonparametric selection method (Chang,
Chiu, and Tsai (2019) <DOI:10.1177/0146621618813113>), as well as several
stopping rules.  Functions for generating item banks and responses are also
provided.  To guide item bank calibration, model comparison at the item level
can be conducted using the two-step likelihood ratio test statistic by Sorrel,
de la Torre, Abad and Olea (2017) <DOI:10.1027/1614-2241/a000131>.")
    (license license:gpl3)))

(define-public r-cdatanet
  (package
    (name "r-cdatanet")
    (version "2.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CDatanet" version))
       (sha256
        (base32 "1qzfxz72zpxi48djqhypqlmajk6rx91m0i997vsr0zry0dp2zrzb"))))
    (properties `((upstream-name . "CDatanet")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppprogress
                             r-rcppnumerical
                             r-rcppeigen
                             r-rcppdist
                             r-rcpparmadillo
                             r-rcpp
                             r-matrixcalc
                             r-matrix
                             r-formula-tools
                             r-formula
                             r-foreach
                             r-dorng
                             r-doparallel
                             r-ddpcr))
    (home-page "https://github.com/ahoundetoungan/CDatanet")
    (synopsis "Econometrics of Network Data")
    (description
     "Simulating and estimating peer effect models and network formation models.  The
class of peer effect models includes linear-in-means models (Lee, 2004;
<doi:10.1111/j.1468-0262.2004.00558.x>), Tobit models (Xu and Lee, 2015;
<doi:10.1016/j.jeconom.2015.05.004>), and discrete numerical data models
(Houndetoungan, 2024; <doi:10.2139/ssrn.3721250>).  The network formation models
include pair-wise regressions with degree heterogeneity (Graham, 2017;
<doi:10.3982/ECTA12679>) and exponential random graph models (Mele, 2017;
<doi:10.3982/ECTA10400>).")
    (license license:gpl3)))

(define-public r-cdata
  (package
    (name "r-cdata")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cdata" version))
       (sha256
        (base32 "1qsxaxj21p2avbnqcgzn9pkrg6i413vcx4mwhkw39jb91sgml9l2"))))
    (properties `((upstream-name . "cdata")))
    (build-system r-build-system)
    (propagated-inputs (list r-wrapr r-rquery r-rqdatatable))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/WinVector/cdata/")
    (synopsis "Fluid Data Transformations")
    (description
     "Supplies higher-order coordinatized data specification and fluid transform
operators that include pivot and anti-pivot as special cases.  The methodology
is describe in Zumel', 2018, \"Fluid data reshaping with cdata'\",
<https://winvector.github.io/@code{FluidData/FluidDataReshapingWithCdata.html>}
, <DOI:10.5281/zenodo.1173299> .  This package introduces the idea of explicit
control table specification of data transforms.  Works on in-memory data or on
remote data using rquery and SQL database interfaces.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-cd
  (package
    (name "r-cd")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cd" version))
       (sha256
        (base32 "1zzhkrsidny5h6jvbip2a4i4klqdgw7s1w8h8hkc3mpbxjfr615r"))))
    (properties `((upstream-name . "cd")))
    (build-system r-build-system)
    (home-page "https://github.com/resteorts/cd")
    (synopsis "CD Data for Entity Resolution")
    (description
     "Duplicated music data (pre-processed and formatted) for entity resolution.  The
total size of the data set is 9763.  There are respective gold standard records
that are labeled and can be considered as a unique identifier.")
    (license license:cc0)))

(define-public r-ccweights
  (package
    (name "r-ccweights")
    (version "0.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CCWeights" version))
       (sha256
        (base32 "0in3pl1n48jal6f7kiyw60by11vbga8vr45x0wywghd7dz60ppfv"))))
    (properties `((upstream-name . "CCWeights")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny
                             r-rmarkdown
                             r-readxl
                             r-readr
                             r-plotly
                             r-magrittr
                             r-fresh
                             r-dt
                             r-dplyr
                             r-bs4dash))
    (home-page "https://cran.r-project.org/package=CCWeights")
    (synopsis "Perform Weighted Linear Regression for Calibration Curve")
    (description
     "Automated assessment and selection of weighting factors for accurate
quantification using linear calibration curve.  In addition, a shiny App is
provided, allowing users to analyze their data using an interactive graphical
user interface, without any programming requirements.")
    (license license:gpl3)))

(define-public r-cctpack
  (package
    (name "r-cctpack")
    (version "1.5.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CCTpack" version))
       (sha256
        (base32 "1kkxsk9x4jz2bvldmba7fsri3zc1cjz15z0xicjmfc7lj72ngdig"))))
    (properties `((upstream-name . "CCTpack")))
    (build-system r-build-system)
    (propagated-inputs (list r-rjags
                             r-r2jags
                             r-psych
                             r-polycor
                             r-mvtnorm
                             r-mass))
    (home-page "https://cran.r-project.org/package=CCTpack")
    (synopsis
     "Consensus Analysis, Model-Based Clustering, and Cultural Consensus Theory Applications")
    (description
     "Consensus analysis, model-based clustering, and cultural consensus theory
applications to response data (e.g. questionnaires).  The models are applied
using hierarchical Bayesian inference.  The current package version supports
binary, ordinal, and continuous data formats.")
    (license license:gpl2+)))

(define-public r-cctools
  (package
    (name "r-cctools")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cctools" version))
       (sha256
        (base32 "03lp9pa9qr2hi584ivvmswxmwjw1c3a6xqladpqldjhzvzpxvcwi"))))
    (properties `((upstream-name . "cctools")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-qrng))
    (home-page "https://cran.r-project.org/package=cctools")
    (synopsis
     "Tools for the Continuous Convolution Trick in Nonparametric Estimation")
    (description
     "This package implements the uniform scaled beta distribution and the continuous
convolution kernel density estimator.")
    (license license:gpl3)))

(define-public r-cctest
  (package
    (name "r-cctest")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cctest" version))
       (sha256
        (base32 "1pcfilz9a06vlgj4g25aghpacdqmfwghqahlsf3h1hnxfzi50y4z"))))
    (properties `((upstream-name . "cctest")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cctest")
    (synopsis "Canonical Correlations and Tests of Independence")
    (description
     "This package provides a simple interface for multivariate correlation analysis
that unifies various classical statistical procedures including t-tests, tests
in univariate and multivariate linear models, parametric and nonparametric tests
for correlation, Kruskal-Wallis tests, common approximate versions of Wilcoxon
rank-sum and signed rank tests, chi-squared tests of independence, score tests
of particular hypotheses in generalized linear models, canonical correlation
analysis and linear discriminant analysis.")
    (license (license:fsdg-compatible "EUPL (>= 1.1)"))))

(define-public r-cctensor
  (package
    (name "r-cctensor")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ccTensor" version))
       (sha256
        (base32 "1r1cqx5kn12xkczpw7f8ij16csnnfy3gjf3kcgr95f070lhd1qna"))))
    (properties `((upstream-name . "ccTensor")))
    (build-system r-build-system)
    (propagated-inputs (list r-rtensor r-mass r-igraph r-fields))
    (home-page "https://github.com/rikenbit/ccTensor")
    (synopsis "CUR/CX Tensor Decomposition")
    (description
     "CUR/CX decomposition factorizes a matrix into two factor matrices and
Multidimensional CX Decomposition factorizes a tensor into a core tensor and
some factor matrices.  See the reference section of @code{GitHub} README.md
<https://github.com/rikenbit/@code{ccTensor>}, for details of the methods.")
    (license license:artistic2.0)))

(define-public r-ccss
  (package
    (name "r-ccss")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ccss" version))
       (sha256
        (base32 "0m2facn6kwxrjxg9a8z0pjnhp0rkgw6nxj6sac93ig24zygx4380"))))
    (properties `((upstream-name . "ccss")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ccss")
    (synopsis "Cluster Circular Systematic Sampling")
    (description
     "Draws systematic samples from a population that follows linear trend.  The
function returns a matrix comprising of the required samples as its column
vectors.  The samples produced are highly efficient and the inter sampling
variance is minimum.  The scheme will be useful in various field like
Bioinformatics where the samples are expensive and must be precise in reflecting
the population by possessing least sampling variance.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-ccsrfind
  (package
    (name "r-ccsrfind")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CCSRfind" version))
       (sha256
        (base32 "0h1nr91d3b8hwl7b8djhrmcf7bbxdl2y6krbqd31zfm5ly1bd7cc"))))
    (properties `((upstream-name . "CCSRfind")))
    (build-system r-build-system)
    (propagated-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CCSRfind")
    (synopsis "Convert ICD-10 Codes to CCSR Codes")
    (description
     "This package provides a tool for matching ICD-10 codes to corresponding Clinical
Classification Software Refined (CCSR) codes.  The main function, CCSRfind(),
identifies each CCSR code that applies to an individual given their diagnosis
codes.  It also provides a summary of CCSR codes that are matched to a dataset.
The package contains 3 datasets: DXCCSR (mapping of ICD-10 codes to CCSR codes),
Legend (conversion of DXCCSR to CCSRfind-usable format for CCSR codes with less
than or equal to 1000 ICD-10 diagnosis codes), and @code{LegendExtend}
(conversion of DXCCSR to CCSRfind-usable format for CCSR codes with more than
1000 ICD-10 dx codes).  The disc() function applies grepl() ('base') to multiple
columns and is used in CCSRfind().")
    (license license:gpl3)))

(define-public r-ccrtm
  (package
    (name "r-ccrtm")
    (version "0.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ccrtm" version))
       (sha256
        (base32 "1r2jmqb8wwmxr13xgzi5qfig96pclm0nmxm0glvwg0i72hvvqlbv"))))
    (properties `((upstream-name . "ccrtm")))
    (build-system r-build-system)
    (propagated-inputs (list r-testthat r-rcpp r-pracma r-expint))
    (home-page "https://github.com/MarcoDVisser/ccrtm")
    (synopsis "Coupled Chain Radiative Transfer Models")
    (description
     "This package provides a set of radiative transfer models to quantitatively
describe the absorption, reflectance and transmission of solar energy in
vegetation, and model remotely sensed spectral signatures of vegetation at
distinct spatial scales (leaf,canopy and stand).  The main principle behind
ccrtm is that many radiative transfer models can form a coupled chain, basically
models that feed into each other in a linked chain (from leaf, to canopy, to
stand, to atmosphere).  It allows the simulation of spectral datasets in the
solar spectrum (400-2500nm) using leaf models as PROSPECT5, 5b, and D which can
be coupled with canopy models as FLIM', SAIL and SAIL2'.  Currently, only a
simple atmospheric model ('skyl') is implemented.  Jacquemoud et al 2008 provide
the most comprehensive overview of these models <doi:10.1016/j.rse.2008.01.026>.")
    (license license:gpl2+)))

(define-public r-ccrs
  (package
    (name "r-ccrs")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ccrs" version))
       (sha256
        (base32 "1nyw4ip9v7y6yfbfdz3bwhy4r6hpp1hiip3ycldxlkl9wrxkxgrw"))))
    (properties `((upstream-name . "ccrs")))
    (build-system r-build-system)
    (propagated-inputs (list r-msm
                             r-lsbclust
                             r-limsolve
                             r-dplyr
                             r-colorspace
                             r-cds))
    (home-page "https://cran.r-project.org/package=ccrs")
    (synopsis "Correct and Cluster Response Style Biased Data")
    (description
     "This package provides functions for performing Correcting and Clustering
response-style-biased preference data (CCRS).  The main functions are
correct.RS() for correcting for response styles, and ccrs() for simultaneously
correcting and content-based clustering.  The procedure begin with making
rank-ordered boundary data from the given preference matrix using a function
called create.ccrsdata().  Then in correct.RS(), the response style is corrected
as follows: the rank-ordered boundary data are smoothed by I-spline functions,
the given preference data are transformed by the smoothed functions.  The
resulting data matrix, which is considered as bias-corrected data, can be used
for any data analysis methods.  If one wants to cluster respondents based on
their indicated preferences (content-based clustering), ccrs() can be applied to
the given (response-style-biased) preference data, which simultaneously corrects
for response styles and clusters respondents based on the contents.  Also, the
correction result can be checked by plot.crs() function.")
    (license license:gpl2+)))

(define-public r-ccremover
  (package
    (name "r-ccremover")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ccRemover" version))
       (sha256
        (base32 "1npd0vx2hyg7qbwd650987i49v5cxr6i1hlj5rw6fxc0b808s596"))))
    (properties `((upstream-name . "ccRemover")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ccRemover")
    (synopsis
     "Removes the Cell-Cycle Effect from Single-Cell RNA-Sequencing Data")
    (description
     "This package implements a method for identifying and removing the cell-cycle
effect from @code{scRNA-Seq} data.  The description of the method is in Barron
M. and Li J. (2016) <doi:10.1038/srep33892>.  Identifying and removing the
cell-cycle effect from single-cell RNA-Sequencing data.  Submitted.  Different
from previous methods, @code{ccRemover} implements a mechanism that formally
tests whether a component is cell-cycle related or not, and thus while it often
thoroughly removes the cell-cycle effect, it preserves other features/signals of
interest in the data.")
    (license license:gpl3)))

(define-public r-ccpsyc
  (package
    (name "r-ccpsyc")
    (version "0.2.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ccpsyc" version))
       (sha256
        (base32 "131ngns5nfkfp0wwf3hl0mhil7n040ss9ppshz4607rrk1ar9isf"))))
    (properties `((upstream-name . "ccpsyc")))
    (build-system r-build-system)
    (propagated-inputs (list r-xlsx
                             r-ufs
                             r-tidyr
                             r-tibble
                             r-rlang
                             r-readr
                             r-rcppalgos
                             r-psych
                             r-mcmcpack
                             r-magrittr
                             r-lavaan
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=ccpsyc")
    (synopsis "Methods for Cross-Cultural Psychology")
    (description
     "With the development of new cross-cultural methods this package is intended to
combine multiple functions automating and simplifying functions providing a
unified analysis approach for commonly employed methods.")
    (license license:gpl3)))

(define-public r-ccp
  (package
    (name "r-ccp")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CCP" version))
       (sha256
        (base32 "067nf1gag3ya7v9vzcpvallga5dr243q0q07fd370k0zynmhcfby"))))
    (properties `((upstream-name . "CCP")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CCP")
    (synopsis "Significance Tests for Canonical Correlation Analysis (CCA)")
    (description
     "Significance tests are provided for canonical correlation analysis, including
asymptotic tests and a Monte Carlo method.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-ccostr
  (package
    (name "r-ccostr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ccostr" version))
       (sha256
        (base32 "0yfmj8v7ip595v87w9dmlzl5rih2j0lsapswh9b9vvc20wnk48ld"))))
    (properties `((upstream-name . "ccostr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-survival
                             r-rlang
                             r-rdpack
                             r-msm
                             r-knitr
                             r-ggplot2
                             r-forcats
                             r-dplyr
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ccostr")
    (synopsis "Estimation of Mean Costs in Censored Data")
    (description
     "Implementation of estimators for inferring the mean of censored cost data.
Including the estimators BT from Bang and Tsiatis (2000)
<doi:10.1093/biomet/87.2.329> and ZT from Zhao and Tian (2001)
<doi:10.1111/j.0006-341X.2001.01002.x>.")
    (license license:expat)))

(define-public r-ccoptimalmatch
  (package
    (name "r-ccoptimalmatch")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ccoptimalmatch" version))
       (sha256
        (base32 "0a5a036iahzag5rwcrjnf7xvvyfgjcx4xdsy1xzrxxndvkjifwqw"))))
    (properties `((upstream-name . "ccoptimalmatch")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ccoptimalmatch")
    (synopsis "Implementation of Case-Control Optimal Matching")
    (description
     "Cases are matched to controls in an efficient, optimal and computationally
flexible way.  It uses the idea of sub-sampling in the level of the case, by
creating pseudo-observations of controls.  The user can select between
replacement and without replacement, the number of controls, and several
covariates to match upon.  See Mamouris (2021) <doi:10.1186/s12874-021-01256-3>
for an overview.")
    (license license:gpl2)))

(define-public r-ccmreportr
  (package
    (name "r-ccmreportr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ccmReportR" version))
       (sha256
        (base32 "0jxxz26f0azp9xafqilvbbfhzn4ys8q4pf4c8bbnmwwbckmjajxm"))))
    (properties `((upstream-name . "ccmReportR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-rlang
                             r-purrr
                             r-lubridate
                             r-keyring
                             r-jsonlite
                             r-httr
                             r-dplyr))
    (home-page "https://github.com/DurhamRegionHARP/ccmReportR")
    (synopsis "Wraps 'CCM' with Utility Functions")
    (description
     "This package provides a set of functions to perform queries against the CCM API
<https://mohcontacttracing.my.salesforce.com>.")
    (license license:expat)))

(define-public r-ccmmr
  (package
    (name "r-ccmmr")
    (version "0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CCMMR" version))
       (sha256
        (base32 "0y1lfjicyw0gs2r5nrqhkzyzkdbs6brdrzgc98k5fam79nj7kcbv"))))
    (properties `((upstream-name . "CCMMR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppeigen r-rcpp r-rann r-r2r))
    (home-page "https://github.com/djwtouw/CCMMR/")
    (synopsis "Minimization of the Convex Clustering Loss Function")
    (description
     "This package implements the convex clustering through majorization-minimization
(CCMM) algorithm described in Touw, Groenen, and Terada (2022)
<@code{arXiv:2211.01877>} to perform minimization of the convex clustering loss
function.")
    (license license:gpl3+)))

(define-public r-ccmm
  (package
    (name "r-ccmm")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ccmm" version))
       (sha256
        (base32 "0855nr74xxpy7in2vrw15g8pv7nm1374irc1c5hikr5hadk5pf8v"))))
    (properties `((upstream-name . "ccmm")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=ccmm")
    (synopsis "Compositional Mediation Model")
    (description
     "Estimate the direct and indirect (mediation) effects of treatment on the outcome
when intermediate variables (mediators) are compositional and high-dimensional.
Sohn, M.B. and Li, H. (2017).  Compositional Mediation Analysis for Microbiome
Studies. (AOAS: In revision).")
    (license license:gpl2+)))

(define-public r-ccml
  (package
    (name "r-ccml")
    (version "1.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ccml" version))
       (sha256
        (base32 "1njd8fi5n7zi0a7cadxqqlc7cpmqjqqp42ig6q13n8d7a542dacl"))))
    (properties `((upstream-name . "ccml")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-snftool
                             r-plyr
                             r-ggplot2
                             r-dicer
                             r-consensusclusterplus))
    (home-page "https://cran.r-project.org/package=ccml")
    (synopsis "Consensus Clustering for Different Sample Coverage Data")
    (description
     "Consensus clustering, also called meta-clustering or cluster ensembles, has been
increasingly used in clinical data.  Current consensus clustering methods tend
to ensemble a number of different clusters from mathematical replicates with
similar sample coverage.  As the fact of common variety of sample coverage in
the real-world data, a new consensus clustering strategy dealing with such
biological replicates is required.  This is a two-step consensus clustering
package, which is used to input multiple predictive labels with different sample
coverage (missing labels).")
    (license license:gpl2)))

(define-public r-ccmestimator
  (package
    (name "r-ccmestimator")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ccmEstimator" version))
       (sha256
        (base32 "1z53i7d2x1g93zskcyj93hxjyrvc9sjqmq887zaflwf22ikxvm6p"))))
    (properties `((upstream-name . "ccmEstimator")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/xiw021/ccmEstimator")
    (synopsis "Comparative Causal Mediation Estimation")
    (description
     "This package provides functions to perform comparative causal mediation analysis
to compare the mediation effects of different treatments via a common mediator.
Results contain the estimates and confidence intervals for the two comparative
causal mediation analysis estimands, as well as the ATE and ACME for each
treatment.  Functions provided in the package will automatically assess the
comparative causal mediation analysis scope conditions (i.e.  for each
comparative causal mediation estimand, a numerator and denominator that are both
estimated with the desired statistical significance and of the same sign).
Results will be returned for each comparative causal mediation estimand only if
scope conditions are met for it.  See details in
Bansak(2020)<doi:10.1017/pan.2019.31>.")
    (license license:gpl3)))

(define-public r-ccm
  (package
    (name "r-ccm")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CCM" version))
       (sha256
        (base32 "1mhl7yppniybdffylddbbb65n7gmv029fb46wlsxm4yf2xkplmwy"))))
    (properties `((upstream-name . "CCM")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CCM")
    (synopsis "Correlation Classification Method")
    (description
     "Classification method described in Dancik et al (2011)
<doi:10.1158/0008-5472.CAN-11-2427> that classifies a sample according to the
class with the maximum mean (or any other function of) correlation between the
test and training samples with known classes.")
    (license license:gpl2+)))

(define-public r-cclust
  (package
    (name "r-cclust")
    (version "0.6-26")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cclust" version))
       (sha256
        (base32 "0mwqna3751lff5n6bb0k09r7qwh0mpwdxgq68wd4wkl6l5akrv4j"))))
    (properties `((upstream-name . "cclust")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cclust")
    (synopsis "Convex Clustering Methods and Clustering Indexes")
    (description
     "Convex Clustering methods, including K-means algorithm, On-line Update algorithm
(Hard Competitive Learning) and Neural Gas algorithm (Soft Competitive
Learning), and calculation of several indexes for finding the number of clusters
in a data set.")
    (license license:gpl2)))

(define-public r-ccid
  (package
    (name "r-ccid")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ccid" version))
       (sha256
        (base32 "0cmkkllcny53dayl74wqhphjznwj7nw7hvaj1fn6mlp6338h3rp8"))))
    (properties `((upstream-name . "ccid")))
    (build-system r-build-system)
    (propagated-inputs (list r-idetect r-hdbinseg r-genenet r-gdata))
    (home-page "https://github.com/Anastasiou-Andreas/ccid")
    (synopsis
     "Cross-Covariance Isolate Detect: a New Change-Point Method for Estimating Dynamic Functional Connectivity")
    (description
     "This package provides efficient implementation of the Cross-Covariance Isolate
Detect (CCID) methodology for the estimation of the number and location of
multiple change-points in the second-order (cross-covariance or network)
structure of multivariate, possibly high-dimensional time series.  The method is
motivated by the detection of change points in functional connectivity networks
for functional magnetic resonance imaging (@code{fMRI}), electroencephalography
(EEG), magentoencephalography (MEG) and electrocorticography (E@code{CoG}) data.
 The main routines in the package have been extensively tested on @code{fMRI}
data.  For details on the CCID methodology, please see Anastasiou et al (2022),
Cross-covariance isolate detect: A new change-point method for estimating
dynamic functional connectivity.  Medical Image Analysis, Volume 75.")
    (license license:gpl3)))

(define-public r-cchsflow
  (package
    (name "r-cchsflow")
    (version "2.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cchsflow" version))
       (sha256
        (base32 "1cnf1xcwz86nzzgk998m3icdvb799hnj7dzcmhv26gjvix1dqj2g"))))
    (properties `((upstream-name . "cchsflow")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-sjlabelled r-magrittr r-haven r-dplyr))
    (home-page "https://github.com/Big-Life-Lab/cchsflow")
    (synopsis "Transforming and Harmonizing CCHS Variables")
    (description
     "Supporting the use of the Canadian Community Health Survey (CCHS) by
transforming variables from each cycle into harmonized, consistent versions that
span survey cycles (currently, 2001 to 2018).  CCHS data used in this library is
accessed and adapted in accordance to the Statistics Canada Open Licence
Agreement.  This package uses rec_with_table(), which was developed from sjmisc
rec().  LÃ¼decke D (2018). \"sjmisc: Data and Variable Transformation Functions\".
 Journal of Open Source Software, 3(26), 754. <doi:10.21105/joss.00754>.")
    (license license:expat)))

(define-public r-cchs
  (package
    (name "r-cchs")
    (version "0.4.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cchs" version))
       (sha256
        (base32 "14qmh4jb9i0imjkb33x61q074zsrng3acy52cw9p0zsxrbh4gdf5"))))
    (properties `((upstream-name . "cchs")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival))
    (home-page "https://cran.r-project.org/package=cchs")
    (synopsis
     "Cox Model for Case-Cohort Data with Stratified Subcohort-Selection")
    (description
     "This package contains a function, also called cchs', that calculates Estimator
III of Borgan et al (2000), <DOI:10.1023/A:1009661900674>.  This estimator is
for fitting a Cox proportional hazards model to data from a case-cohort study
where the subcohort was selected by stratified simple random sampling.")
    (license license:gpl3)))

(define-public r-ccdr
  (package
    (name "r-ccdr")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ccdR" version))
       (sha256
        (base32 "1fy6fici3f2p7v0ys2jabahd3phqpf9z0rvrydqdr19srllzspgm"))))
    (properties `((upstream-name . "ccdR")))
    (build-system r-build-system)
    (propagated-inputs (list r-urltools
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-purrr
                             r-jsonlite
                             r-httr
                             r-data-table
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/USEPA/ccdR")
    (synopsis "Utilities for Interacting with the 'CTX' APIs")
    (description
     "Access chemical, hazard, bioactivity, and exposure data from the Computational
Toxicology and Exposure ('CTX') APIs <https://api-ccte.epa.gov/docs/>.
@code{ccdR} was developed to streamline the process of accessing the information
available through the CTX APIs without requiring prior knowledge of how to use
APIs.  Most data is also available on the @code{CompTox} Chemical Dashboard
('CCD') <https://comptox.epa.gov/dashboard/> and other resources found at the
EPA Computational Toxicology and Exposure Online Resources
<https://www.epa.gov/comptox-tools>.")
    (license license:gpl3+)))

(define-public r-ccda
  (package
    (name "r-ccda")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ccda" version))
       (sha256
        (base32 "1kka4vmhpcnl4skdmijzsxrfj6dgax6hhlxvp7gkqlfaazq8pzf0"))))
    (properties `((upstream-name . "ccda")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=ccda")
    (synopsis "Combined Cluster and Discriminant Analysis")
    (description
     "This package implements the combined cluster and discriminant analysis method
for finding homogeneous groups of data with known origin as described in Kovacs
et.  al (2014): Classification into homogeneous groups using combined cluster
and discriminant analysis (CCDA).  Environmental Modelling & Software.
<doi:10.1016/j.envsoft.2014.01.010>.")
    (license license:gpl2)))

(define-public r-ccd
  (package
    (name "r-ccd")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CCd" version))
       (sha256
        (base32 "168yaz1vg0hp7vsi2mxrpds0qrwn6zhp299bmi40dxg28fxzmn8w"))))
    (properties `((upstream-name . "CCd")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfast))
    (home-page "https://cran.r-project.org/package=CCd")
    (synopsis "The Cauchy-Cacoullos (Discrete Cauchy) Distribution")
    (description
     "Maximum likelihood estimation of the Cauchy-Cacoullos (discrete Cauchy)
distribution.  Probability mass, distribution and quantile function are also
included.  The reference paper is: Papadatos N. (2022). \"The Characteristic
Function of the Discrete Cauchy Distribution in Memory of T. Cacoullos\".
Journal of Statistical Theory Practice, 16(3): 47.
<doi:10.1007/s42519-022-00268-6>.")
    (license license:gpl2+)))

(define-public r-cccrm
  (package
    (name "r-cccrm")
    (version "3.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cccrm" version))
       (sha256
        (base32 "15a797d9m90pwxc9lpa836dd3mml11pfmx256sgqysmd5rkn13fx"))))
    (properties `((upstream-name . "cccrm")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-purrr
                             r-progressr
                             r-parallelly
                             r-nlmeu
                             r-nlme
                             r-lifecycle
                             r-future
                             r-furrr
                             r-dplyr
                             r-deriv))
    (home-page "https://cran.r-project.org/package=cccrm")
    (synopsis
     "Concordance Correlation Coefficient for Repeated (and Non-Repeated) Measures")
    (description
     "Estimates the Concordance Correlation Coefficient to assess agreement.  The
scenarios considered are non-repeated measures, non-longitudinal repeated
measures (replicates) and longitudinal repeated measures.  It also includes the
estimation of the one-way intraclass correlation coefficient also known as
reliability index.  The estimation approaches implemented are variance
components and U-statistics approaches.  Description of methods can be found in
Fleiss (1986) <doi:10.1002/9781118032923> and Carrasco et al. (2013)
<doi:10.1016/j.cmpb.2012.09.002>.")
    (license license:gpl2+)))

(define-public r-cccp
  (package
    (name "r-cccp")
    (version "0.3-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cccp" version))
       (sha256
        (base32 "06ds1f954m2g3g85rccpvk1bhxqn544qqxg7wzs4jkb97h590dzn"))))
    (properties `((upstream-name . "cccp")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "https://cran.r-project.org/package=cccp")
    (synopsis "Cone Constrained Convex Problems")
    (description
     "Routines for solving convex optimization problems with cone constraints by means
of interior-point methods.  The implemented algorithms are partially ported from
CVXOPT, a Python module for convex optimization (see <https://cvxopt.org> for
more information).")
    (license license:gpl3+)))

(define-public r-cccm
  (package
    (name "r-cccm")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cccm" version))
       (sha256
        (base32 "1spwv5crmaysw19c2rq3cri2kmrfzqcb1wjdpri1ih6sgcg039gi"))))
    (properties `((upstream-name . "cccm")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-dplyr))
    (home-page "https://cran.r-project.org/package=cccm")
    (synopsis "Crossed Classification Credibility Model")
    (description
     "Calculates the credit debt for the next period based on the available data using
the cross-classification credibility model.")
    (license license:gpl3)))

(define-public r-ccapp
  (package
    (name "r-ccapp")
    (version "0.3.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ccaPP" version))
       (sha256
        (base32 "16bw98wqjm62gjcznlwj24akng1csi3dciw6v5rkg9v2xkjn44d5"))))
    (properties `((upstream-name . "ccaPP")))
    (build-system r-build-system)
    (propagated-inputs (list r-robustbase r-rcpparmadillo r-rcpp r-pcapp))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/aalfons/ccaPP")
    (synopsis "(Robust) Canonical Correlation Analysis via Projection Pursuit")
    (description
     "Canonical correlation analysis and maximum correlation via projection pursuit,
as well as fast implementations of correlation estimators, with a focus on
robust and nonparametric methods.")
    (license license:gpl2+)))

(define-public r-ccamlrgis
  (package
    (name "r-ccamlrgis")
    (version "4.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CCAMLRGIS" version))
       (sha256
        (base32 "1yx589sfc3amwgq68cwbs4p4n3nn1i1kgd1hakvmpv10zn2v8fqa"))))
    (properties `((upstream-name . "CCAMLRGIS")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra
                             r-sf
                             r-magrittr
                             r-lwgeom
                             r-isoband
                             r-dplyr
                             r-bezier))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ccamlr/CCAMLRGIS#ccamlrgis-r-package")
    (synopsis "Antarctic Spatial Data Manipulation")
    (description
     "Loads and creates spatial data, including layers and tools that are relevant to
the activities of the Commission for the Conservation of Antarctic Marine Living
Resources.  Provides two categories of functions: load functions and create
functions.  Load functions are used to import existing spatial layers from the
online CCAMLR GIS such as the ASD boundaries.  Create functions are used to
create layers from user data such as polygons and grids.")
    (license license:gpl3)))

(define-public r-cca
  (package
    (name "r-cca")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CCA" version))
       (sha256
        (base32 "0r1f7m64608hq6bpw36wsw6fr4s8bj26x4062brqgn5dbpqlgczk"))))
    (properties `((upstream-name . "CCA")))
    (build-system r-build-system)
    (propagated-inputs (list r-fields r-fda))
    (home-page "https://cran.r-project.org/package=CCA")
    (synopsis "Canonical Correlation Analysis")
    (description
     "This package provides a set of functions that extend the cancor function with
new numerical and graphical outputs.  It also include a regularized extension of
the canonical correlation analysis to deal with datasets with more variables
than observations.")
    (license license:gpl2+)))

(define-public r-cc
  (package
    (name "r-cc")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CC" version))
       (sha256
        (base32 "189si37ggichqmzy8m686zw1cijix7yfy8ma5iqpnq1q9vm3pcvy"))))
    (properties `((upstream-name . "CC")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CC")
    (synopsis "Control Charts")
    (description
     "This package provides tools for creating and visualizing statistical process
control charts.  Control charts are used for monitoring measurement processes,
such as those occurring in manufacturing.  The objective is to monitor the
history of such processes and flag outlying measurements: out-of-control
signals.  Montgomery, D. (2009, ISBN:978-0-470-16992-6) contains an extensive
discussion of the methodology.")
    (license license:gpl2+)))

(define-public r-cbt
  (package
    (name "r-cbt")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CBT" version))
       (sha256
        (base32 "13h6sf7w03nfq2arqymwww13ywnv9xnqbqazlzn856mj3ggaqda7"))))
    (properties `((upstream-name . "CBT")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CBT")
    (synopsis "Confidence Bound Target Algorithm")
    (description
     "The Confidence Bound Target (CBT) algorithm is designed for infinite arms bandit
problem.  It is shown that CBT algorithm achieves the regret lower bound for
general reward distributions.  Reference: Hock Peng Chan and Shouri Hu (2018)
<@code{arXiv:1805.11793>}.")
    (license license:gpl2)))

(define-public r-cbsr
  (package
    (name "r-cbsr")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CBSr" version))
       (sha256
        (base32 "175xx7igxpx2s9jl9ncjabqr6n05v5ipwm7shpqm19qfqxb4ygrz"))))
    (properties `((upstream-name . "CBSr")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (propagated-inputs (list r-rjava r-nlcoptim))
    (home-page "https://cran.r-project.org/package=CBSr")
    (synopsis
     "Fits Cubic Bezier Spline Functions to Intertemporal and Risky Choice Data")
    (description
     "Uses monotonically constrained Cubic Bezier Splines (CBS) to approximate latent
utility functions in intertemporal choice and risky choice data.  For more
information, see Lee, Glaze, Bradlow, and Kable
<doi:10.1007/s11336-020-09723-4>.")
    (license license:gpl3)))

(define-public r-cbsodatar
  (package
    (name "r-cbsodatar")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cbsodataR" version))
       (sha256
        (base32 "0pj3c8jgdfqz5m4ws2g6jzx4xghsyji8fmm1vk5l2w07pcm1xs9a"))))
    (properties `((upstream-name . "cbsodataR")))
    (build-system r-build-system)
    (propagated-inputs (list r-whisker r-jsonlite))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/edwindj/cbsodataR")
    (synopsis "Statistics Netherlands (CBS) Open Data API Client")
    (description
     "The data and meta data from Statistics Netherlands (<https://www.cbs.nl>) can be
browsed and downloaded.  The client uses the open data API of Statistics
Netherlands.")
    (license license:gpl2)))

(define-public r-cbq
  (package
    (name "r-cbq")
    (version "0.2.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cbq" version))
       (sha256
        (base32 "12ix60mvs4rlh3376m6qcq5zslng1925hrsz5byddfdjx5wilyv7"))))
    (properties `((upstream-name . "cbq")))
    (build-system r-build-system)
    (propagated-inputs (list r-stanheaders
                             r-rstantools
                             r-rstan
                             r-rcppeigen
                             r-rcpp
                             r-formula
                             r-bh))
    (home-page "https://cran.r-project.org/package=cbq")
    (synopsis "Conditional Binary Quantile Models")
    (description
     "Estimates conditional binary quantile models developed by Lu (2020)
<doi:10.1017/pan.2019.29>.  The estimation procedure is implemented based on
Markov chain Monte Carlo methods.")
    (license license:expat)))

(define-public r-cbps
  (package
    (name "r-cbps")
    (version "0.23")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CBPS" version))
       (sha256
        (base32 "0bdkx7phi58200jgijqmv5d7v2kiksj07sxx2sjmkd1dcjdy13zd"))))
    (properties `((upstream-name . "CBPS")))
    (build-system r-build-system)
    (propagated-inputs (list r-numderiv r-nnet r-matchit r-mass r-glmnet))
    (home-page "https://cran.r-project.org/package=CBPS")
    (synopsis "Covariate Balancing Propensity Score")
    (description
     "This package implements the covariate balancing propensity score (CBPS) proposed
by Imai and Ratkovic (2014) <DOI:10.1111/rssb.12027>.  The propensity score is
estimated such that it maximizes the resulting covariate balance as well as the
prediction of treatment assignment.  The method, therefore, avoids an iteration
between model fitting and balance checking.  The package also implements optimal
CBPS from Fan et al. (in-press) <DOI:10.1080/07350015.2021.2002159>, several
extensions of the CBPS beyond the cross-sectional, binary treatment setting.
They include the CBPS for longitudinal settings so that it can be used in
conjunction with marginal structural models from Imai and Ratkovic (2015)
<DOI:10.1080/01621459.2014.956872>, treatments with three- and four-valued
treatment variables, continuous-valued treatments from Fong, Hazlett, and Imai
(2018) <DOI:10.1214/17-AOAS1101>, propensity score estimation with a large
number of covariates from Ning, Peng, and Imai (2020)
<DOI:10.1093/biomet/asaa020>, and the situation with multiple distinct binary
treatments administered simultaneously.  In the future it will be extended to
other settings including the generalization of experimental and instrumental
variable estimates.")
    (license license:gpl2+)))

(define-public r-cbpe
  (package
    (name "r-cbpe")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CBPE" version))
       (sha256
        (base32 "1l6vs2dq0ckspy9ksdwkds5jyr7a14c34bd9lpx1hnfw3savhhcp"))))
    (properties `((upstream-name . "CBPE")))
    (build-system r-build-system)
    (home-page "https://github.com/mnrzrad/CBPE")
    (synopsis "Correlation-Based Penalized Estimators")
    (description
     "This package provides correlation-based penalty estimators for both linear and
logistic regression models by implementing a new regularization method that
incorporates correlation structures within the data.  This method encourages a
grouping effect where strongly correlated predictors tend to be in or out of the
model together.  See Tutz and Ulbricht (2009) <doi:10.1007/s11222-008-9088-5>
and Algamal and Lee (2015) <doi:10.1016/j.eswa.2015.08.016>.")
    (license license:gpl2+)))

(define-public r-cbnetworkma
  (package
    (name "r-cbnetworkma")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CBnetworkMA" version))
       (sha256
        (base32 "12zg5pq029z8kw00jvb8al4igfkklacnhdchbaphhk39dg7qp4yr"))))
    (properties `((upstream-name . "CBnetworkMA")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CBnetworkMA")
    (synopsis "Contrast-Based Bayesian Network Meta Analysis")
    (description
     "This package provides a function that facilitates fitting three types of models
for contrast-based Bayesian Network Meta Analysis.  The first model is that
which is described in Lu and Ades (2006) <doi:10.1198/016214505000001302>.  The
other two models are based on a Bayesian nonparametric methods that permit ties
when comparing treatment or for a treatment effect to be exactly equal to zero.
In addition to the model fits, the package provides a summary of the interplay
between treatment effects based on the procedure described in Barrientos, Page,
and Lin (2023) <doi:10.48550/@code{arXiv.2207.06561>}.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-cbl
  (package
    (name "r-cbl")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cbl" version))
       (sha256
        (base32 "1wgc9nsc875s2h583gigh9hyr9d15dp35rnmb1znwqy11jrswbw3"))))
    (properties `((upstream-name . "cbl")))
    (build-system r-build-system)
    (propagated-inputs (list r-lightgbm r-glmnet r-foreach r-data-table))
    (home-page "https://github.com/dswatson/cbl")
    (synopsis "Causal Discovery under a Confounder Blanket")
    (description
     "This package provides methods for learning causal relationships among a set of
foreground variables X based on signals from a (potentially much larger) set of
background variables Z, which are known non-descendants of X. The confounder
blanket learner (CBL) uses sparse regression techniques to simultaneously
perform many conditional independence tests, with complementary pairs stability
selection to guarantee finite sample error control.  CBL is sound and complete
with respect to a so-called \"lazy oracle\", and works with both linear and
nonlinear systems.  For details, see Watson & Silva (2022)
<@code{arXiv:2205.05715>}.")
    (license license:gpl3+)))

(define-public r-cbioportalr
  (package
    (name "r-cbioportalr")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cbioportalR" version))
       (sha256
        (base32 "0vr8sjp2fkz24zcws6i46kmswf30yj147y3108i6sk7ncc2mavr5"))))
    (properties `((upstream-name . "cbioportalR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-jsonlite
                             r-httr
                             r-glue
                             r-dplyr
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/karissawhiting/cbioportalR")
    (synopsis "Browse and Query Clinical and Genomic Data from cBioPortal")
    (description
     "This package provides R users with direct access to genomic and clinical data
from the @code{cBioPortal} web resource via user-friendly functions that wrap
@code{cBioPortal's} existing API endpoints
<https://www.cbioportal.org/api/swagger-ui/index.html>.  Users can browse and
query genomic data on mutations, copy number alterations and fusions, as well as
data on tumor mutational burden ('TMB'), microsatellite instability status
('MSI'), FACETS and select clinical data points (depending on the study).  See
<https://www.cbioportal.org/> and Gao et al., (2013)
<doi:10.1126/scisignal.2004088> for more information on the @code{cBioPortal}
web resource.")
    (license license:expat)))

(define-public r-cbinom
  (package
    (name "r-cbinom")
    (version "1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cbinom" version))
       (sha256
        (base32 "1vi2kjlss4fmra1h8r6xgk4y66gzpdp61hcyzby2rqji93sib195"))))
    (properties `((upstream-name . "cbinom")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://cran.r-project.org/package=cbinom")
    (synopsis "Continuous Analog of a Binomial Distribution")
    (description
     "Implementation of the d/p/q/r family of functions for a continuous analog to the
standard discrete binomial with continuous size parameter and continuous support
with x in [0, size + 1], following Ilienko (2013) <@code{arXiv:1303.5990>}.")
    (license license:gpl2+)))

(define-public r-cbctools
  (package
    (name "r-cbctools")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cbcTools" version))
       (sha256
        (base32 "07has80n7n23y2y3shalps1hkw1r8f4fld1r48g42fdrwkhhf6jw"))))
    (properties `((upstream-name . "cbcTools")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-randtoolbox
                             r-mass
                             r-logitr
                             r-idefix
                             r-ggplot2
                             r-fastdummies
                             r-doe-base
                             r-algdesign))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jhelvy/cbcTools")
    (synopsis
     "Choice-Based Conjoint Experiment Design Generation and Power Evaluation in R")
    (description
     "Design and evaluate choice-based conjoint survey experiments.  Generate a
variety of survey designs, including random designs, full factorial designs,
orthogonal designs, D-optimal designs, and Bayesian D-efficient designs as well
as designs with \"no choice\" options and \"labeled\" (also known as \"alternative
specific\") designs.  Conveniently inspect the design balance and overlap, and
simulate choice data for a survey design either randomly or according to a
multinomial or mixed logit utility model defined by user-provided prior
parameters.  Conduct a power analysis for a given survey design by estimating
the same model on different subsets of the data to simulate different sample
sizes.  Full factorial and orthogonal designs are obtained using the
@code{DoE.base} package (GrÃ¶mping, 2018) <doi:10.18637/jss.v085.i05>.
D-optimal designs are obtained using the @code{AlgDesign} package (Wheeler,
2022) <https://CRAN.R-project.org/package=@code{AlgDesign>}.  Bayesian
D-efficient designs are obtained using the idefix package (Traets et al, 2020)
<doi:10.18637/jss.v096.i03>.  Choice simulation and model estimation in power
analyses are handled using the logitr package (Helveston, 2023)
<doi:10.18637/jss.v105.i10>.")
    (license license:expat)))

(define-public r-cbcgrps
  (package
    (name "r-cbcgrps")
    (version "2.8.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CBCgrps" version))
       (sha256
        (base32 "0z34vcdq5lp1l15l3a67lpvfla0g0qsb5ijbc9h575h7fpf28jqf"))))
    (properties `((upstream-name . "CBCgrps")))
    (build-system r-build-system)
    (propagated-inputs (list r-nortest))
    (home-page "https://cran.r-project.org/package=CBCgrps")
    (synopsis "Compare Baseline Characteristics Between Groups")
    (description
     "Compare baseline characteristics between two or more groups.  The variables
being compared can be factor and numeric variables.  The function will
automatically judge the type and distribution of the variables, and make
statistical description and bivariate analysis.")
    (license license:gpl2)))

(define-public r-cbbinom
  (package
    (name "r-cbbinom")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cbbinom" version))
       (sha256
        (base32 "0n0qyzlsm54dl71n5rdrim6rvmsbk3g8n5r0i2q91yk9fayaz9ly"))))
    (properties `((upstream-name . "cbbinom")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-hypergeo2 r-bh))
    (home-page "https://github.com/zhuxr11/cbbinom")
    (synopsis "Continuous Analog of a Beta-Binomial Distribution")
    (description
     "Implementation of the d/p/q/r family of functions for a continuous analog to the
standard discrete beta-binomial with continuous size parameter and continuous
support with x in [0, size + 1].")
    (license license:expat)))

(define-public r-cbass
  (package
    (name "r-cbass")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cbass" version))
       (sha256
        (base32 "1x7k9srf2jgjhlha9fjm7rfcd9msk05nxa3p7657ns8y2v12s0nq"))))
    (properties `((upstream-name . "cbass")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cbass")
    (synopsis "Classification -- Bayesian Adaptive Smoothing Splines")
    (description
     "Fit multiclass Classification version of Bayesian Adaptive Smoothing Splines
(CBASS) to data using reversible jump MCMC. The multiclass classification
problem consists of a response variable that takes on unordered categorical
values with at least three levels, and a set of inputs for each response
variable.  The CBASS model consists of a latent multivariate probit formulation,
and the means of the latent Gaussian random variables are specified using
adaptive regression splines.  The MCMC alternates updates of the latent Gaussian
variables and the spline parameters.  All the spline parameters (variables,
signs, knots, number of interactions), including the number of basis functions
used to model each latent mean, are inferred.  Functions are provided to process
inputs, initialize the chain, run the chain, and make predictions.  Predictions
are made on a probabilistic basis, where, for a given input, the probabilities
of each categorical value are produced.  See Marrs and Francom (2023)
\"Multiclass classification using Bayesian multivariate adaptive regression
splines\" Under review.")
    (license license:gpl3)))

(define-public r-cbanalysis
  (package
    (name "r-cbanalysis")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cbanalysis" version))
       (sha256
        (base32 "0h0h8krlb6rckjpcw0jbbr8pcy3jm0cszimbm56l0ca668kiix06"))))
    (properties `((upstream-name . "cbanalysis")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cbanalysis")
    (synopsis "Coffee Break Descriptive Analysis")
    (description
     "This package provides a set of functions that helps you to generate descriptive
statistics based on the variable types.")
    (license license:gpl2)))

(define-public r-cba
  (package
    (name "r-cba")
    (version "0.2-25")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cba" version))
       (sha256
        (base32 "0a05nfmi9a1gj1r2ms310360wxdw5zgvgb9rc0awf684i5cibjy7"))))
    (properties `((upstream-name . "cba")))
    (build-system r-build-system)
    (propagated-inputs (list r-proxy))
    (home-page "https://cran.r-project.org/package=cba")
    (synopsis "Clustering for Business Analytics")
    (description
     "This package implements clustering techniques such as Proximus and Rock, utility
functions for efficient computation of cross distances and data manipulation.")
    (license license:gpl2)))

(define-public r-cb2
  (package
    (name "r-cb2")
    (version "1.3.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CB2" version))
       (sha256
        (base32 "0431bd956hmkrhs9x845vjwbzzwzd7n9nfx9y95mv6qv84zd4wv2"))))
    (properties `((upstream-name . "CB2")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-readr
                             r-rcpparmadillo
                             r-rcpp
                             r-r-utils
                             r-pheatmap
                             r-metap
                             r-magrittr
                             r-glue
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CB2")
    (synopsis "CRISPR Pooled Screen Analysis using Beta-Binomial Test")
    (description
     "This package provides functions for hit gene identification and quantification
of @code{sgRNA} (single-guided RNA) abundances for CRISPR (Clustered Regularly
Interspaced Short Palindromic Repeats) pooled screen data analysis.  Details are
in Jeong et al. (2019) <doi:10.1101/gr.245571.118> and Baggerly et al. (2003)
<doi:10.1093/bioinformatics/btg173>.")
    (license license:expat)))

(define-public r-caviarpd
  (package
    (name "r-caviarpd")
    (version "0.3.13")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "caviarpd" version))
       (sha256
        (base32 "0zf9s8wnyxfzmnxrq80xbxr1lrlgqdclwjbdrs6pfmdqmyix8dp6"))))
    (properties `((upstream-name . "caviarpd")))
    (build-system r-build-system)
    (inputs (list))
    (home-page "https://github.com/dbdahl/caviarpd")
    (synopsis "Cluster Analysis via Random Partition Distributions")
    (description
     "Cluster analysis is performed using pairwise distance information and a random
partition distribution.  The method is implemented for two random partition
distributions.  It draws samples and then obtains and plots clustering
estimates.  An implementation of a selection algorithm is provided for the mass
parameter of the partition distribution.  Since pairwise distances are the
principal input to this procedure, it is most comparable to the hierarchical and
k-medoids clustering methods.  The method is Dahl, Andros, Carter (2022+)
<doi:10.1002/sam.11602>.")
    (license (list license:expat license:asl2.0))))

(define-public r-cavariants
  (package
    (name "r-cavariants")
    (version "6.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CAvariants" version))
       (sha256
        (base32 "02m2kq0ggj7g0c2x8pdvasc881prbbyrs92rfy61qmbm8kxiy8js"))))
    (properties `((upstream-name . "CAvariants")))
    (build-system r-build-system)
    (propagated-inputs (list r-plotly r-gridextra r-ggrepel r-ggplot2
                             r-ggforce))
    (home-page "https://www.R-project.org")
    (synopsis "Correspondence Analysis Variants")
    (description
     "This package provides six variants of two-way correspondence analysis (ca):
simple ca, singly ordered ca, doubly ordered ca, non symmetrical ca, singly
ordered non symmetrical ca, and doubly ordered non symmetrical ca.")
    (license license:gpl3+)))

(define-public r-cautiouslearning
  (package
    (name "r-cautiouslearning")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CautiousLearning" version))
       (sha256
        (base32 "1m5x93l4bscrpcxk0pva6d6n2qnzhzxh0a6a81p97l8lqgs1qw2q"))))
    (properties `((upstream-name . "CautiousLearning")))
    (build-system r-build-system)
    (propagated-inputs (list r-spc r-sitmo r-rcpp r-bh))
    (home-page "https://cran.r-project.org/package=CautiousLearning")
    (synopsis
     "Control Charts with Guaranteed In-Control Performance and Cautious Parameters Learning")
    (description
     "Design and use of control charts for detecting mean changes based on a delayed
updating of the in-control parameter estimates.  See Capizzi and Masarotto
(2019) <doi:10.1080/00224065.2019.1640096> for the description of the method.")
    (license license:expat)))

(define-public r-causcor
  (package
    (name "r-causcor")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CausCor" version))
       (sha256
        (base32 "0hqzzy6wmxws90q4p7d2k0781zmkqq344l352zj9lcqh23ci4p8i"))))
    (properties `((upstream-name . "CausCor")))
    (build-system r-build-system)
    (propagated-inputs (list r-writexls r-magrittr r-ggplot2 r-dplyr r-cowplot))
    (home-page "https://github.com/sugym/CausCor")
    (synopsis "Calculate Correlations and Estimate Causality")
    (description
     "This tool performs pairwise correlation analysis and estimate causality.
Particularly, it is useful for detecting the metabolites that would be altered
by the gut bacteria.")
    (license license:expat)))

(define-public r-causalweight
  (package
    (name "r-causalweight")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "causalweight" version))
       (sha256
        (base32 "0412ald8wq2fnam4bb2dc1yrx21vk2c6vbn76lf46c5apb9sw3ij"))))
    (properties `((upstream-name . "causalweight")))
    (build-system r-build-system)
    (propagated-inputs (list r-xgboost
                             r-superlearner
                             r-sandwich
                             r-ranger
                             r-np
                             r-mvtnorm
                             r-larf
                             r-hdm
                             r-grf
                             r-glmnet
                             r-fastdummies
                             r-e1071
                             r-checkmate))
    (home-page "https://cran.r-project.org/package=causalweight")
    (synopsis
     "Estimation Methods for Causal Inference Based on Inverse Probability Weighting")
    (description
     "Various estimators of causal effects based on inverse probability weighting,
doubly robust estimation, and double machine learning.  Specifically, the
package includes methods for estimating average treatment effects, direct and
indirect effects in causal mediation analysis, and dynamic treatment effects.
The models refer to studies of Froelich (2007)
<doi:10.1016/j.jeconom.2006.06.004>, Huber (2012)
<doi:10.3102/1076998611411917>, Huber (2014) <doi:10.1080/07474938.2013.806197>,
Huber (2014) <doi:10.1002/jae.2341>, Froelich and Huber (2017)
<doi:10.1111/rssb.12232>, Hsu, Huber, Lee, and Lettry (2020)
<doi:10.1002/jae.2765>, and others.")
    (license license:expat)))

(define-public r-causalslse
  (package
    (name "r-causalslse")
    (version "0.3-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "causalSLSE" version))
       (sha256
        (base32 "0qi3mnkdcirj4dyrvvgs2r9752x8zfkiq5rzqaj1501w2k9kwir9"))))
    (properties `((upstream-name . "causalSLSE")))
    (build-system r-build-system)
    (propagated-inputs (list r-texreg r-sandwich))
    (native-inputs (list r-knitr gfortran))
    (home-page "https://cran.r-project.org/package=causalSLSE")
    (synopsis "Semiparametric Least Squares Inference for Causal Effects")
    (description
     "Several causal effects are measured using least squares regressions and basis
function approximations.  Backward and forward selection methods based on
different criteria are used to select the basis functions.")
    (license license:gpl2+)))

(define-public r-causalsens
  (package
    (name "r-causalsens")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "causalsens" version))
       (sha256
        (base32 "0gmy24vp50xfl4qrnn314svyic8fhqnfhr43zwbcbgipf877hdvh"))))
    (properties `((upstream-name . "causalsens")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://www.mattblackwell.org/software/causalsens/")
    (synopsis
     "Selection Bias Approach to Sensitivity Analysis for Causal Effects")
    (description
     "The causalsens package provides functions to perform sensitivity analyses and to
study how various assumptions about selection bias affects estimates of causal
effects.")
    (license license:gpl2+)))

(define-public r-causalqueries
  (package
    (name "r-causalqueries")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CausalQueries" version))
       (sha256
        (base32 "0bivanhgimfnw1dn16ggyj6yjjq1j3jv05xwixqcg96zdnw5va4z"))))
    (properties `((upstream-name . "CausalQueries")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-stanheaders
                             r-rstantools
                             r-rstan
                             r-rlang
                             r-rcppeigen
                             r-rcpparmadillo
                             r-rcpp
                             r-lifecycle
                             r-latex2exp
                             r-knitr
                             r-ggplot2
                             r-ggdag
                             r-dplyr
                             r-dirmult
                             r-dagitty
                             r-bh))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CausalQueries")
    (synopsis "Make, Update, and Query Binary Causal Models")
    (description
     "Users can declare binary causal models, update beliefs about causal types given
data and calculate arbitrary estimands.  Model definition makes use of dagitty
functionality.  Updating is implemented in stan'.  The approach used in
@code{CausalQueries} is a generalization of the biqq models described in \"Mixing
Methods: A Bayesian Approach\" (Humphreys and Jacobs, 2015,
<DOI:10.1017/S0003055415000453>).  The conceptual extension makes use of work on
probabilistic causal models described in Pearl's Causality (Pearl, 2009,
<DOI:10.1017/CBO9780511803161>).")
    (license license:expat)))

(define-public r-causalpaf
  (package
    (name "r-causalpaf")
    (version "1.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "causalPAF" version))
       (sha256
        (base32 "1hgixasanddxs9y1l45qmx5chhq0ri6npvzqwazjkk61byl2wj6c"))))
    (properties `((upstream-name . "causalPAF")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlist
                             r-reshape2
                             r-mass
                             r-magrittr
                             r-gridextra
                             r-ggplot2
                             r-ggdag
                             r-forestplot
                             r-dplyr
                             r-dagitty
                             r-checkmate))
    (home-page "https://github.com/MauriceOConnell/causalPAF")
    (synopsis "Causal Effect for Population Attributable Fractions (PAF)")
    (description
     "Calculates population attributable fraction causal effects.  The
@code{causalPAF} package contains a suite of functions for causal analysis
calculations of population attributable fractions (PAF) given a causal diagram
which apply both: Pathway-specific population attributable fractions (PS-PAFs)
OâConnell and Ferguson (2022) <doi:10.1093/ije/dyac079> and Sequential
population attributable fractions Ferguson, OâConnell, and OâDonnell (2020)
<doi:10.1186/s13690-020-00442-x>.  Results are presentable in both table and
plot format.")
    (license license:gpl2+)))

(define-public r-causalot
  (package
    (name "r-causalot")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "causalOT" version))
       (sha256
        (base32 "10fvmhv4g791xhrxdfhyjn02fk0b80z4n9y73l1hhc3fr4vzphz3"))))
    (properties `((upstream-name . "causalOT")))
    (build-system r-build-system)
    (propagated-inputs (list r-torch
                             r-sandwich
                             r-rlang
                             r-rcppeigen
                             r-rcpp
                             r-r6
                             r-osqp
                             r-matrixstats
                             r-matrix
                             r-loo
                             r-lbfgsb3c
                             r-ggplot2
                             r-cbps
                             r-bh))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=causalOT")
    (synopsis "Optimal Transport Weights for Causal Inference")
    (description
     "Uses optimal transport distances to find probabilistic matching estimators for
causal inference.  These methods are described in Dunipace, Eric (2021)
<@code{arXiv:2109.01991>}.  The package will build the weights, estimate
treatment effects, and calculate confidence intervals via the methods described
in the paper.  The package also supports several other methods as described in
the help files.")
    (license (license:fsdg-compatible "GPL (== 3.0)"))))

(define-public r-causaloptim
  (package
    (name "r-causaloptim")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "causaloptim" version))
       (sha256
        (base32 "18rms13kwkai4yj1h8npb3dgnpy884i8vznn4cbma2frqal0rqyn"))))
    (properties `((upstream-name . "causaloptim")))
    (build-system r-build-system)
    (arguments
     (list
      #:modules '((guix build r-build-system)
                  (guix build minify-build-system)
                  (guix build utils)
                  (ice-9 match))
      #:imported-modules `(,@%r-build-system-modules (guix build
                                                      minify-build-system))
      #:phases '(modify-phases %standard-phases
                  (add-after 'unpack 'process-javascript
                    (lambda* (#:key inputs #:allow-other-keys)
                      (with-directory-excursion "inst/"
                        (for-each (match-lambda
                                    ((source . target) (minify source
                                                               #:target target)))
                                  '())))))))
    (propagated-inputs (list r-shiny r-rcdd r-igraph))
    (native-inputs (list r-knitr esbuild))
    (home-page "https://sachsmc.github.io/causaloptim/")
    (synopsis
     "An Interface to Specify Causal Graphs and Compute Bounds on Causal Effects")
    (description
     "When causal quantities are not identifiable from the observed data, it still may
be possible to bound these quantities using the observed data.  We outline a
class of problems for which the derivation of tight bounds is always a linear
programming problem and can therefore, at least theoretically, be solved using a
symbolic linear optimizer.  We extend and generalize the approach of Balke and
Pearl (1994) <doi:10.1016/B978-1-55860-332-5.50011-0> and we provide a user
friendly graphical interface for setting up such problems via directed acyclic
graphs (DAG), which only allow for problems within this class to be depicted.
The user can then define linear constraints to further refine their assumptions
to meet their specific problem, and then specify a causal query using a text
interface.  The program converts this user defined DAG, query, and constraints,
and returns tight bounds.  The bounds can be converted to R functions to
evaluate them for specific datasets, and to latex code for publication.  The
methods and proofs of tightness and validity of the bounds are described in a
paper by Sachs, Jonzon, Gabriel, and SjÃ¶lander (2022)
<doi:10.1080/10618600.2022.2071905>.")
    (license license:expat)))

(define-public r-causalmodels
  (package
    (name "r-causalmodels")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CausalModels" version))
       (sha256
        (base32 "19m1qfzssrwmsxiiyqiqby102qmxxcmbyxhggd9bb44z2iicf8cl"))))
    (properties `((upstream-name . "CausalModels")))
    (build-system r-build-system)
    (propagated-inputs (list r-multcomp r-geepack r-causaldata r-boot))
    (home-page "https://github.com/ander428/CausalModels")
    (synopsis "Causal Inference Modeling for Estimation of Causal Effects")
    (description
     "This package provides an array of statistical models common in causal inference
such as standardization, IP weighting, propensity matching, outcome regression,
and doubly-robust estimators.  Estimates of the average treatment effects from
each model are given with the standard error and a 95% Wald confidence interval
(Hernan, Robins (2020)
<https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/>).")
    (license license:gpl3)))

(define-public r-causalmetar
  (package
    (name "r-causalmetar")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CausalMetaR" version))
       (sha256
        (base32 "03y973ph52qxh9kyiybrvgrk5b1kd6i1lynkmmmv40vbnx59fs7y"))))
    (properties `((upstream-name . "CausalMetaR")))
    (build-system r-build-system)
    (propagated-inputs (list r-superlearner r-progress r-nnet r-metafor
                             r-glmnet))
    (home-page "https://github.com/ly129/CausalMetaR")
    (synopsis "Causally Interpretable Meta-Analysis")
    (description
     "This package provides robust and efficient methods for estimating causal effects
in a target population using a multi-source dataset, including those of Dahabreh
et al. (2019) <doi:10.1111/biom.13716>, Robertson et al. (2021)
<doi:10.48550/@code{arXiv.2104.05905>}, and Wang et al. (2024)
<doi:10.48550/@code{arXiv.2402.02684>}.  The multi-source data can be a
collection of trials, observational studies, or a combination of both, which
have the same data structure (outcome, treatment, and covariates).  The target
population can be based on an internal dataset or an external dataset where only
covariate information is available.  The causal estimands available are average
treatment effects and subgroup treatment effects.  See Wang et al. (2024)
<doi:10.48550/@code{arXiv.2402.04341>} for a detailed guide on using the
package.")
    (license license:gpl3+)))

(define-public r-causalmbsts
  (package
    (name "r-causalmbsts")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CausalMBSTS" version))
       (sha256
        (base32 "1mjw2zyddkci6vkbyz3d94l5z1aj3rc2w6lag5igbfv4q0n5qcrp"))))
    (properties `((upstream-name . "CausalMBSTS")))
    (build-system r-build-system)
    (propagated-inputs (list r-mixmatrix
                             r-matrix
                             r-mass
                             r-kfas
                             r-forecast
                             r-cholwishart))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CausalMBSTS")
    (synopsis "MBSTS Models for Causal Inference and Forecasting")
    (description
     "This package infers the causal effect of an intervention on a multivariate
response through the use of Multivariate Bayesian Structural Time Series models
(MBSTS) as described in Menchetti & Bojinov (2020) <@code{arXiv:2006.12269>}.
The package also includes functions for model building and forecasting.")
    (license license:gpl3+)))

(define-public r-causalimpact
  (package
    (name "r-causalimpact")
    (version "1.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CausalImpact" version))
       (sha256
        (base32 "0h3sh35962vdph72svfdvk6b1gl7wnj2kfkkpcjldbiszlfxp7wx"))))
    (properties `((upstream-name . "CausalImpact")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-ggplot2 r-bsts r-boom r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://google.github.io/CausalImpact/")
    (synopsis
     "Inferring Causal Effects using Bayesian Structural Time-Series Models")
    (description
     "This package implements a Bayesian approach to causal impact estimation in time
series, as described in Brodersen et al. (2015) <DOI:10.1214/14-AOAS788>.  See
the package documentation on @code{GitHub}
<https://google.github.io/@code{CausalImpact/>} to get started.")
    (license (list license:asl2.0
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-causalhypergraph
  (package
    (name "r-causalhypergraph")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "causalHyperGraph" version))
       (sha256
        (base32 "096ggvryh580lcx4mhzsgbfifc6fqldw30a9ss6cxjvzf00prgkf"))))
    (properties `((upstream-name . "causalHyperGraph")))
    (build-system r-build-system)
    (propagated-inputs (list r-useful r-stringr r-diagrammersvg r-diagrammer
                             r-cna))
    (home-page "https://cran.r-project.org/package=causalHyperGraph")
    (synopsis "Drawing Causal Hypergraphs")
    (description
     "Draws causal hypergraph plots from models output by configurational comparative
methods such as Coincidence Analysis (CNA) or Qualitative Comparative Analysis
(QCA).")
    (license license:gpl2+)))

(define-public r-causalgps
  (package
    (name "r-causalgps")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CausalGPS" version))
       (sha256
        (base32 "0hb010hsqn3ahsp3kqmn4r1qa3y3znz7kc7j8pv9zdx2cpyrnmi4"))))
    (properties `((upstream-name . "CausalGPS")))
    (build-system r-build-system)
    (propagated-inputs (list r-xgboost
                             r-wcorr
                             r-superlearner
                             r-rlang
                             r-rcpp
                             r-polycor
                             r-mass
                             r-logger
                             r-locpol
                             r-kernsmooth
                             r-gnm
                             r-ggplot2
                             r-gam
                             r-ecume
                             r-data-table
                             r-cowplot))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/NSAPH-Software/CausalGPS")
    (synopsis
     "Matching on Generalized Propensity Scores with Continuous Exposures")
    (description
     "This package provides a framework for estimating causal effects of a continuous
exposure using observational data, and implementing matching and weighting on
the generalized propensity score.  Wu, X., Mealli, F., Kioumourtzoglou, M.A.,
Dominici, F. and Braun, D., 2022.  Matching on generalized propensity scores
with continuous exposures.  Journal of the American Statistical Association,
pp.1-29.")
    (license license:gpl3)))

(define-public r-causalgam
  (package
    (name "r-causalgam")
    (version "0.1-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CausalGAM" version))
       (sha256
        (base32 "1riz11hfg96iks7734rg692l75nfrd3hmr9gw563j27rkk1nfkl6"))))
    (properties `((upstream-name . "CausalGAM")))
    (build-system r-build-system)
    (propagated-inputs (list r-gam))
    (home-page "https://cran.r-project.org/package=CausalGAM")
    (synopsis "Estimation of Causal Effects with Generalized Additive Models")
    (description
     "This package implements various estimators for average treatment effects - an
inverse probability weighted (IPW) estimator, an augmented inverse probability
weighted (AIPW) estimator, and a standard regression estimator - that make use
of generalized additive models for the treatment assignment model and/or outcome
model.  See: Glynn, Adam N. and Kevin M. Quinn.  2010. \"An Introduction to the
Augmented Inverse Propensity Weighted Estimator.\" Political Analysis.  18:
36-56.")
    (license license:gpl2)))

(define-public r-causaleffect
  (package
    (name "r-causaleffect")
    (version "1.3.15")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "causaleffect" version))
       (sha256
        (base32 "1dyadjl941zback2jadsxi20a572gk1z7s6vrb432k2w65pdm2sv"))))
    (properties `((upstream-name . "causaleffect")))
    (build-system r-build-system)
    (propagated-inputs (list r-igraph))
    (native-inputs (list r-r-rsp))
    (home-page "https://github.com/santikka/causaleffect/")
    (synopsis
     "Deriving Expressions of Joint Interventional Distributions and Transport Formulas in Causal Models")
    (description
     "This package provides functions for identification and transportation of causal
effects.  Provides a conditional causal effect identification algorithm (IDC) by
Shpitser, I. and Pearl, J. (2006)
<http://ftp.cs.ucla.edu/pub/stat_ser/r329-uai.pdf>, an algorithm for
transportability from multiple domains with limited experiments by Bareinboim,
E. and Pearl, J. (2014) <http://ftp.cs.ucla.edu/pub/stat_ser/r443.pdf>, and a
selection bias recovery algorithm by Bareinboim, E. and Tian, J. (2015)
<http://ftp.cs.ucla.edu/pub/stat_ser/r445.pdf>.  All of the previously mentioned
algorithms are based on a causal effect identification algorithm by Tian , J.
(2002) <http://ftp.cs.ucla.edu/pub/stat_ser/r309.pdf>.")
    (license license:gpl2+)))

(define-public r-causaldrf
  (package
    (name "r-causaldrf")
    (version "0.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "causaldrf" version))
       (sha256
        (base32 "1dvgvzg7cyjzb8x3gxa7n6bnh34q7rps6f1xks1s0b3gjf53hvbp"))))
    (properties `((upstream-name . "causaldrf")))
    (build-system r-build-system)
    (propagated-inputs (list r-survey r-mgcv))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=causaldrf")
    (synopsis "Estimating Causal Dose Response Functions")
    (description
     "This package provides functions and data to estimate causal dose response
functions given continuous, ordinal, or binary treatments.  A description of the
methods is given in Galagate (2016)
<https://drum.lib.umd.edu/handle/1903/18170>.")
    (license license:expat)))

(define-public r-causaldisco
  (package
    (name "r-causaldisco")
    (version "0.9.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "causalDisco" version))
       (sha256
        (base32 "1lni0y76prhvw60m0awwgmfadwlv1ciywlr85sr8ig2vaxf1smh9"))))
    (properties `((upstream-name . "causalDisco")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales
                             r-rcolorbrewer
                             r-pcalg
                             r-igraph
                             r-gtools
                             r-clipr))
    (home-page "https://github.com/annennenne/causalDisco")
    (synopsis "Tools for Causal Discovery on Observational Data")
    (description
     "Various tools for inferring causal models from observational data.  The package
includes an implementation of the temporal Peter-Clark (TPC) algorithm.
Petersen, Osler and EkstrÃ¸m (2021) <doi:10.1093/aje/kwab087>.  It also includes
general tools for evaluating differences in adjacency matrices, which can be
used for evaluating performance of causal discovery procedures.")
    (license license:gpl2)))

(define-public r-causaldata
  (package
    (name "r-causaldata")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "causaldata" version))
       (sha256
        (base32 "1v5apihm9005j1kf3p1d28v6jaqx87ryc43kjhwd5mvvm10rmflc"))))
    (properties `((upstream-name . "causaldata")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble))
    (home-page "https://github.com/NickCH-K/causaldata")
    (synopsis "Example Data Sets for Causal Inference Textbooks")
    (description
     "Example data sets to run the example problems from causal inference textbooks.
Currently, contains data sets for Huntington-Klein, Nick (2021) \"The Effect\"
<https://theeffectbook.net>, Cunningham, Scott (2021, ISBN-13:
978-0-300-25168-5) \"Causal Inference: The Mixtape\", and HernÃ¡n, Miguel and
James Robins (2020) \"Causal Inference: What If\"
<https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/>.")
    (license license:expat)))

(define-public r-causalcmprsk
  (package
    (name "r-causalcmprsk")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "causalCmprsk" version))
       (sha256
        (base32 "079wr4w30153hxvk2q9ki19h54p8vyvc1y6ka8j5vk6rcf8gmg5l"))))
    (properties `((upstream-name . "causalCmprsk")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-purrr
                             r-inline
                             r-foreach
                             r-doparallel
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Bella2001/causalCmprsk")
    (synopsis
     "Nonparametric and Cox-Based Estimation of Average Treatment Effects in Competing Risks")
    (description
     "Estimation of average treatment effects (ATE) of point interventions on
time-to-event outcomes with K competing risks (K can be 1).  The method uses
propensity scores and inverse probability weighting for emulation of baseline
randomization, which is described in Charpignon et al. (2022)
<doi:10.1038/s41467-022-35157-w>.")
    (license license:gpl2+)))

(define-public r-causalbatch
  (package
    (name "r-causalbatch")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "causalBatch" version))
       (sha256
        (base32 "0jq5a6ch12v55x8fwz6as43wb4q5nc56hqb97jcsgksvsy9cn2g3"))))
    (properties `((upstream-name . "causalBatch")))
    (build-system r-build-system)
    (propagated-inputs (list r-sva
                             r-nnet
                             r-matchit
                             r-magrittr
                             r-dplyr
                             r-cdcsis))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/neurodata/causal_batch")
    (synopsis "Causal Batch Effects")
    (description
     "Software which provides numerous functionalities for detecting and removing
group-level effects from high-dimensional scientific data which, when combined
with additional assumptions, allow for causal conclusions, as-described in our
manuscripts Bridgeford et al. (2024) <doi:10.1101/2021.09.03.458920> and
Bridgeford et al. (2023) <@code{arXiv:2307.13868>}.  Also provides a number of
useful utilities for generating simulations and balancing covariates across
multiple groups/batches of data via matching and propensity trimming for more
than two groups.")
    (license license:expat)))

(define-public r-causal-decomp
  (package
    (name "r-causal-decomp")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "causal.decomp" version))
       (sha256
        (base32 "12iy64dnb91l47vai9qawlwvg17x5amqg0kdj8npk1mgzm2zfz4j"))))
    (properties `((upstream-name . "causal.decomp")))
    (build-system r-build-system)
    (propagated-inputs (list r-suppdists
                             r-spelling
                             r-psweight
                             r-nnet
                             r-mass
                             r-cbps))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=causal.decomp")
    (synopsis "Causal Decomposition Analysis")
    (description
     "We implement causal decomposition analysis using the methods proposed by Park,
Lee, and Qin (2020) and Park, Kang, and Lee (2021+) <@code{arXiv:2109.06940>}.
This package allows researchers to use the multiple-mediator-imputation,
single-mediator-imputation, and product-of-coefficients regression methods to
estimate the initial disparity, disparity reduction, and disparity remaining.
It also allows to make the inference conditional on baseline covariates.  We
also implement sensitivity analysis for the causal decomposition analysis using
R-squared values as sensitivity parameters (Park, Kang, Lee, and Ma, 2023).")
    (license license:gpl2)))

(define-public r-causact
  (package
    (name "r-causact")
    (version "0.5.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "causact" version))
       (sha256
        (base32 "0sf32v47n18sf3x5f08pzl7mc66g95fw6nym02vvyr6a30zv1b5b"))))
    (properties `((upstream-name . "causact")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-rstudioapi
                             r-rlang
                             r-reticulate
                             r-purrr
                             r-magrittr
                             r-lifecycle
                             r-igraph
                             r-ggplot2
                             r-forcats
                             r-dplyr
                             r-diagrammer
                             r-cowplot))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/flyaflya/causact")
    (synopsis "Fast, Easy, and Visual Bayesian Inference")
    (description
     "Accelerate Bayesian analytics workflows in R through interactive modelling,
visualization, and inference.  Define probabilistic graphical models using
directed acyclic graphs (DAGs) as a unifying language for business stakeholders,
statisticians, and programmers.  This package relies on interfacing with the
numpyro python package.")
    (license license:expat)))

(define-public r-cauphy
  (package
    (name "r-cauphy")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cauphy" version))
       (sha256
        (base32 "1rb5fjlh91k229a0hcw8d7x7wjf3m7p9apschq83xgpv4d5a0b2m"))))
    (properties `((upstream-name . "cauphy")))
    (build-system r-build-system)
    (propagated-inputs (list r-robustbase
                             r-pracma
                             r-phylolm
                             r-nloptr
                             r-hdinterval
                             r-foreach
                             r-doparallel
                             r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://gilles-didier.github.io/cauphy/")
    (synopsis "Trait Evolution on Phylogenies Using the Cauchy Process")
    (description
     "The Cauchy Process can model pulsed continuous trait evolution on phylogenies.
The likelihood is tractable, and is used for parameter inference and ancestral
trait reconstruction.  See Bastide and Didier (2023)
<doi:10.1093/sysbio/syad053>.")
    (license license:gpl3+)))

(define-public r-cauchypca
  (package
    (name "r-cauchypca")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cauchypca" version))
       (sha256
        (base32 "157ydm2vizv7cwvxi7id7wws7v0h3iymgwsbvk13q4jlk8ygnnqn"))))
    (properties `((upstream-name . "cauchypca")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfast2 r-rfast r-foreach r-doparallel))
    (home-page "https://cran.r-project.org/package=cauchypca")
    (synopsis
     "Robust Principal Component Analysis Using the Cauchy Distribution")
    (description
     "This package provides a new robust principal component analysis algorithm is
implemented that relies upon the Cauchy Distribution.  The algorithm is suitable
for high dimensional data even if the sample size is less than the number of
variables.  The methodology is described in this paper: Fayomi A., Pantazis Y.,
Tsagris M. and Wood A.T.A. (2024). \"Cauchy robust principal component analysis
with applications to high-dimensional data sets\".  Statistics and Computing, 34:
26. <doi:10.1007/s11222-023-10328-x>.")
    (license license:gpl2+)))

(define-public r-cauchycp
  (package
    (name "r-cauchycp")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CauchyCP" version))
       (sha256
        (base32 "0sv1gfvgwqvm7zb3rhlhmfgfwm2i49wzzkg473gdmamvvpvzih43"))))
    (properties `((upstream-name . "CauchyCP")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival))
    (home-page "https://cran.r-project.org/package=CauchyCP")
    (synopsis "Powerful Test for Survival Data under Non-Proportional Hazards")
    (description
     "An omnibus test of change-point Cox regression models to improve the statistical
power of detecting signals of non-proportional hazards patterns.  The technical
details can be found in Hong Zhang, Qing Li, Devan Mehrotra and Judong Shen
(2021) <@code{arXiv:2101.00059>}.  Extensive simulation studies demonstrate
that, compared to existing tests under non-proportional hazards, the proposed
@code{CauchyCP} test 1) controls the type I error better at small alpha levels;
2) increases the power of detecting time-varying effects; and 3) is more
computationally efficient.")
    (license license:gpl2)))

(define-public r-cattexact
  (package
    (name "r-cattexact")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CATTexact" version))
       (sha256
        (base32 "07ciln6cfvqya7dwwn6mhd9lk2833hypm4badizgfi2k749d1p00"))))
    (properties `((upstream-name . "CATTexact")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CATTexact")
    (synopsis
     "Computation of the p-Value for the Exact Conditional Cochran-Armitage Trend Test")
    (description
     "This package provides functions for computing the one-sided p-values of the
Cochran-Armitage trend test statistic for the asymptotic and the exact
conditional test.  The computation of the p-value for the exact test is
performed using an algorithm following an idea by Mehta, et al. (1992)
<doi:10.2307/1390598>.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-catt
  (package
    (name "r-catt")
    (version "2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CATT" version))
       (sha256
        (base32 "12xdspl1gbf51snyrl44nn7alfyccdfihibkgvzr66lrby8b8fhg"))))
    (properties `((upstream-name . "CATT")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CATT")
    (synopsis "The Cochran-Armitage Trend Test")
    (description
     "This function conducts the Cochran-Armitage trend test to a 2 by k contingency
table.  It will report the test statistic (Z) and p-value.A linear trend in the
frequencies will be calculated, because the weights (0,1,2) will be used by
default.")
    (license license:gpl3)))

(define-public r-catsurv
  (package
    (name "r-catsurv")
    (version "1.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "catSurv" version))
       (sha256
        (base32 "0jw7jlam7d44g9sbwmxckm4mywhky2a6h1w5w849g47p7mvi32dc"))))
    (properties `((upstream-name . "catSurv")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppparallel
                             r-rcppgsl
                             r-rcpparmadillo
                             r-rcpp
                             r-plyr
                             r-ltm
                             r-jsonlite
                             r-bh))
    (home-page "https://cran.r-project.org/package=catSurv")
    (synopsis "Computerized Adaptive Testing for Survey Research")
    (description
     "This package provides methods of computerized adaptive testing for survey
researchers.  See Montgomery and Rossiter (2020) <doi:10.1093/jssam/smz027>.
Includes functionality for data fit with the classic item response methods
including the latent trait model, Birnbaum`s three parameter model, the graded
response, and the generalized partial credit model.  Additionally, includes
several ability parameter estimation and item selection routines.  During item
selection, all calculations are done in compiled C++ code.")
    (license license:gpl3)))

(define-public r-catsim
  (package
    (name "r-catsim")
    (version "0.2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "catsim" version))
       (sha256
        (base32 "1lwc13xf7794fln5ylwwb9w9s1ah7y2h7wil1hjhz9vxhfpa044w"))))
    (properties `((upstream-name . "catsim")))
    (build-system r-build-system)
    (propagated-inputs (list r-testthat r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://gzt.github.io/catsim/")
    (synopsis "Binary and Categorical Image Similarity Index")
    (description
     "Computes a structural similarity metric (after the style of MS-SSIM for images)
for binary and categorical 2D and 3D images.  Can be based on accuracy (simple
matching), Cohen's kappa, Rand index, adjusted Rand index, Jaccard index, Dice
index, normalized mutual information, or adjusted mutual information.  In
addition, has fast computation of Cohen's kappa, the Rand indices, and the two
mutual informations.  Implements the methods of Thompson and Maitra (2020)
<doi:10.48550/@code{arXiv.2004.09073>}.")
    (license license:gpl3)))

(define-public r-catseyes
  (package
    (name "r-catseyes")
    (version "0.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "catseyes" version))
       (sha256
        (base32 "11n2kxkqv4hqymkj6lkpcvhq6325q8f5w384xf8zb71jl8vx616l"))))
    (properties `((upstream-name . "catseyes")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=catseyes")
    (synopsis
     "Create Catseye Plots Illustrating the Normal Distribution of the Means")
    (description
     "This package provides the tools to produce catseye plots, principally by
catseyesplot() function which calls R's standard plot() function internally, or
alternatively by the catseyes() function to overlay the catseye plot onto an
existing R plot window.  Catseye plots illustrate the normal distribution of the
mean (picture a normal bell curve reflected over its base and rotated 90
degrees), with a shaded confidence interval; they are an intuitive way of
illustrating and comparing normally distributed estimates, and are arguably a
superior alternative to standard confidence intervals, since they show the full
distribution rather than fixed quantile bounds.  The catseyesplot and catseyes
functions require pre-calculated means and standard errors (or standard
deviations), provided as numeric vectors; this allows the flexibility of
obtaining this information from a variety of sources, such as direct calculation
or prediction from a model.  Catseye plots, as illustrations of the normal
distribution of the means, are described in Cumming (2013 & 2014).  Cumming, G.
(2013).  The new statistics: Why and how.  Psychological Science, 27, 7-29.
<doi:10.1177/0956797613504966> pmid:24220629.")
    (license license:gpl3)))

(define-public r-cats
  (package
    (name "r-cats")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cats" version))
       (sha256
        (base32 "0snc5vrf8qm53yd42gskhnpp6lfgfkldgpjj3jbcry0wpbfc0dv0"))))
    (properties `((upstream-name . "cats")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-tidyr
                             r-purrr
                             r-plotly
                             r-openxlsx
                             r-mvtnorm
                             r-ggplot2
                             r-foreach
                             r-forcats
                             r-epitools
                             r-dplyr
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=cats")
    (synopsis "Cohort Platform Trial Simulation")
    (description
     "Cohort @code{plAtform} Trial Simulation whereby every cohort consists of two
arms, control and experimental treatment.  Endpoints are co-primary binary
endpoints and decisions are made using either Bayesian or frequentist decision
rules.  Realistic trial trajectories are simulated and the operating
characteristics of the designs are calculated.")
    (license license:expat)))

(define-public r-catregs
  (package
    (name "r-catregs")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "catregs" version))
       (sha256
        (base32 "0zmgq5w8kd8ldfkz9j43vpzjnyv5rcaaj57r7b7gsxwi3gdvqr4a"))))
    (properties `((upstream-name . "catregs")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=catregs")
    (synopsis "Post-Estimation Functions for Generalized Linear Mixed Models")
    (description
     "Several functions for working with mixed effects regression models for limited
dependent variables.  The functions facilitate post-estimation of model
predictions or margins, and comparisons between model predictions for assessing
or probing moderation.  Additional helper functions facilitate model comparisons
and implements simulation-based inference for model predictions of
alternative-specific outcome models.  See also, Melamed and Doan (2024, ISBN:
978-1032509518).")
    (license (list license:gpl2 license:gpl3))))

(define-public r-catreg
  (package
    (name "r-catreg")
    (version "2.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CatReg" version))
       (sha256
        (base32 "02pxarc4v45w8ncx8hq084m69qgl9s2lkrv1biz60vrvl99dg016"))))
    (properties `((upstream-name . "CatReg")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-rcpp))
    (home-page "https://cran.r-project.org/package=CatReg")
    (synopsis
     "Solution Paths for Linear and Logistic Regression Models with Categorical Predictors, with SCOPE Penalty")
    (description
     "Computes solutions for linear and logistic regression models with potentially
high-dimensional categorical predictors.  This is done by applying a nonconvex
penalty (SCOPE) and computing solutions in an efficient path-wise fashion.  The
scaling of the solution paths is selected automatically.  Includes functionality
for selecting tuning parameter lambda by k-fold cross-validation and early
termination based on information criteria.  Solutions are computed by cyclical
block-coordinate descent, iterating an innovative dynamic programming algorithm
to compute exact solutions for each block.")
    (license license:gpl2+)))

(define-public r-catr
  (package
    (name "r-catr")
    (version "3.17")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "catR" version))
       (sha256
        (base32 "178pq6cy3kjpd7mpaky2y8f18561gsf727y0y6rmgm2bn71p2i76"))))
    (properties `((upstream-name . "catR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=catR")
    (synopsis
     "Generation of IRT Response Patterns under Computerized Adaptive Testing")
    (description
     "This package provides routines for the generation of response patterns under
unidimensional dichotomous and polytomous computerized adaptive testing (CAT)
framework.  It holds many standard functions to estimate ability, select the
first item(s) to administer and optimally select the next item, as well as
several stopping rules.  Options to control for item exposure and content
balancing are also available (Magis and Barrada (2017)
<doi:10.18637/jss.v076.c01>).")
    (license license:gpl3+)))

(define-public r-catpredi
  (package
    (name "r-catpredi")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CatPredi" version))
       (sha256
        (base32 "0wj37pav20s273ha8pwmzypcdl8frakrxn5k149lg6vkgl6qmj8x"))))
    (properties `((upstream-name . "CatPredi")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rms r-rgenoud r-mgcv))
    (home-page "https://cran.r-project.org/package=CatPredi")
    (synopsis
     "Optimal Categorisation of Continuous Variables in Prediction Models")
    (description
     "Allows the user to categorise a continuous predictor variable in a logistic or a
Cox proportional hazards regression setting, by maximising the discriminative
ability of the model.  I Barrio, I Arostegui, MX Rodriguez-Alvarez, JM Quintana
(2015) <doi:10.1177/0962280215601873>.  I Barrio, MX Rodriguez-Alvarez, L
Meira-Machado, C Esteban, I Arostegui (2017)
<https://www.idescat.cat/sort/sort411/41.1.3.barrio-etal.pdf>.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-catmaply
  (package
    (name "r-catmaply")
    (version "0.9.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "catmaply" version))
       (sha256
        (base32 "1vjnh0qvqdfsv4p28yg5r4s9m0l0d7f1r07vamlhvhshb5cfnmsy"))))
    (properties `((upstream-name . "catmaply")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-rlang r-plotly r-magrittr r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/VerkehrsbetriebeZuerich/catmaply")
    (synopsis "Heatmap for Categorical Data using 'plotly'")
    (description
     "This package provides methods and plotting functions for displaying categorical
data on an interactive heatmap using plotly'.  Provides functionality for
strictly categorical heatmaps, heatmaps illustrating categorized continuous data
and annotated heatmaps.  Also, there are various options to interact with the
x-axis to prevent overlapping axis labels, e.g. via simple sliders or range
sliders.  Besides the viewer pane, resulting plots can be saved as a standalone
HTML file, embedded in R Markdown documents or in a Shiny app.")
    (license license:expat)))

(define-public r-catmap
  (package
    (name "r-catmap")
    (version "1.6.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "catmap" version))
       (sha256
        (base32 "18449qh10jxfi8p49gmbnib5y013nfdgdblbs4n0mfs0nnzb10sx"))))
    (properties `((upstream-name . "catmap")))
    (build-system r-build-system)
    (propagated-inputs (list r-metafor r-forestplot))
    (home-page "http://github.com/tpq/catmap")
    (synopsis "Case-Control and TDT Meta-Analysis Package")
    (description
     "Although many software tools can perform meta-analyses on genetic case-control
data, none of these apply to combined case-control and family-based (TDT)
studies.  This package conducts fixed-effects (with inverse variance weighting)
and random-effects [@code{DerSimonian} and Laird (1986)
<DOI:10.1016/0197-2456(86)90046-2>] meta-analyses on combined genetic data.
Specifically, this package implements a fixed-effects model [Kazeem and Farrall
(2005) <DOI:10.1046/j.1529-8817.2005.00156.x>] and a random-effects model
[Nicodemus (2008) <DOI:10.1186/1471-2105-9-130>] for combined studies.")
    (license license:gpl2)))

(define-public r-catlearn
  (package
    (name "r-catlearn")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "catlearn" version))
       (sha256
        (base32 "1bzzzqprgyskkf1dnb5k4pqkdn5m67a3pxbnk1cnhscagcjndvy6"))))
    (properties `((upstream-name . "catlearn")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rcpparmadillo
                             r-rcpp
                             r-foreach
                             r-dplyr
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=catlearn")
    (synopsis "Formal Psychological Models of Categorization and Learning")
    (description
     "Formal psychological models of categorization and learning,
independently-replicated data sets against which to test them, and simulation
archives.")
    (license license:gpl2+)))

(define-public r-catirt
  (package
    (name "r-catirt")
    (version "0.5.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "catIrt" version))
       (sha256
        (base32 "1wagk9f9mvf3b5yvwpas9yqjzpcp786d37wn71jj1af0khry8k62"))))
    (properties `((upstream-name . "catIrt")))
    (build-system r-build-system)
    (propagated-inputs (list r-numderiv))
    (home-page "https://github.com/swnydick/catIrt")
    (synopsis "Simulate IRT-Based Computerized Adaptive Tests")
    (description
     "This package provides functions designed to simulate data that conform to basic
unidimensional IRT models (for now 3-parameter binary response models and graded
response models) along with Post-Hoc CAT simulations of those models given
various item selection methods, ability estimation methods, and termination
criteria.  See Wainer (2000) <doi:10.4324/9781410605931>, van der Linden &
Pashley (2010) <doi:10.1007/978-0-387-85461-8_1>, and Eggen (1999)
<doi:10.1177/01466219922031365> for more details.")
    (license license:gpl2+)))

(define-public r-cati
  (package
    (name "r-cati")
    (version "0.99.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cati" version))
       (sha256
        (base32 "02g33kkp97kswiyjsd378zpa3fc9rjk2d9f4l1gdh7pzglabsmgl"))))
    (properties `((upstream-name . "cati")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-rastervis
                             r-nlme
                             r-hypervolume
                             r-geometry
                             r-fd
                             r-e1071
                             r-ape
                             r-ade4))
    (home-page "https://github.com/adrientaudiere/cati")
    (synopsis "Community Assembly by Traits: Individuals and Beyond")
    (description
     "Detect and quantify community assembly processes using trait values of
individuals or populations, the T-statistics and other metrics, and dedicated
null models.")
    (license license:gpl2+)))

(define-public r-catfun
  (package
    (name "r-catfun")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "catfun" version))
       (sha256
        (base32 "1482rll333fvy4h58f15flfs7qrck3vk9bzpdn3hayhnmc7svmma"))))
    (properties `((upstream-name . "catfun")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-magrittr
                             r-hmisc
                             r-epitools
                             r-desctools
                             r-cli
                             r-broom))
    (home-page "https://cran.r-project.org/package=catfun")
    (synopsis "Categorical Data Analysis")
    (description
     "Includes wrapper functions around existing functions for the analysis of
categorical data and introduces functions for calculating risk differences and
matched odds ratios.  R currently supports a wide variety of tools for the
analysis of categorical data.  However, many functions are spread across a
variety of packages with differing syntax and poor compatibility with each
another.  prop_test() combines the functions binom.test(), prop.test() and
@code{BinomCI}() into one output.  prop_power() allows for power and sample size
calculations for both balanced and unbalanced designs.  riskdiff() is used for
calculating risk differences and matched_or() is used for calculating matched
odds ratios.  For further information on methods used that are not documented in
other packages see Nathan Mantel and William Haenszel (1959)
<doi:10.1093/jnci/22.4.719> and Alan Agresti (2002) <ISBN:0-471-36093-7>.")
    (license license:expat)))

(define-public r-catencoders
  (package
    (name "r-catencoders")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CatEncoders" version))
       (sha256
        (base32 "1q9wzq06lac8z9y8b65alsxpb48bw8wqmifd893kknk51xq6r9kl"))))
    (properties `((upstream-name . "CatEncoders")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-data-table))
    (home-page "https://cran.r-project.org/package=CatEncoders")
    (synopsis "Encoders for Categorical Variables")
    (description
     "This package contains some commonly used categorical variable encoders, such as
@code{LabelEncoder} and @code{OneHotEncoder}'.  Inspired by the encoders
implemented in Python sklearn.preprocessing package (see
<http://scikit-learn.org/stable/modules/preprocessing.html>).")
    (license (list license:gpl2 license:gpl3))))

(define-public r-categoryencodings
  (package
    (name "r-categoryencodings")
    (version "1.4.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "categoryEncodings" version))
       (sha256
        (base32 "0ns8ml2hm41650bi8yag6w3k9nb2ky43370444cgy3i7ajpzw87w"))))
    (properties `((upstream-name . "categoryEncodings")))
    (build-system r-build-system)
    (propagated-inputs (list r-sparsepca r-glmnet r-data-table))
    (home-page "https://github.com/JSzitas/categoryEncodings")
    (synopsis "Category Variable Encodings")
    (description
     "Simple, fast, and automatic encodings for category data using a data.table
backend.  Most of the methods are an implementation of \"Sufficient
Representation for Categorical Variables\" by Johannemann, Hadad, Athey, Wager
(2019) <@code{arXiv:1908.09874>}, particularly their mean, sparse principal
component analysis, low rank representation, and multinomial logit encodings.")
    (license license:gpl3)))

(define-public r-catdyn
  (package
    (name "r-catdyn")
    (version "1.1-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CatDyn" version))
       (sha256
        (base32 "0gkaxs7apqhq7mp3chjsyhrnk3qkk11f8p7smmyj6h73888ry8jn"))))
    (properties `((upstream-name . "CatDyn")))
    (build-system r-build-system)
    (propagated-inputs (list r-optimx r-bb))
    (home-page "https://cran.r-project.org/package=CatDyn")
    (synopsis "Fishery Stock Assessment by Catch Dynamics Models")
    (description
     "Based on fishery Catch Dynamics instead of fish Population Dynamics (hence
@code{CatDyn}) and using high-frequency or medium-frequency catch in biomass or
numbers, fishing nominal effort, and mean fish body weight by time step, from
one or two fishing fleets, estimate stock abundance, natural mortality rate, and
fishing operational parameters.  It includes methods for data organization,
plotting standard exploratory and analytical plots, predictions, for 100 types
of models of increasing complexity, and 72 likelihood models for the data.")
    (license license:gpl2+)))

(define-public r-catdataanalysis
  (package
    (name "r-catdataanalysis")
    (version "0.1-5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CatDataAnalysis" version))
       (sha256
        (base32 "19bbilvz9h2bswpm5992c48cm4slc73kf0ny2mp78vhcfadri9cb"))))
    (properties `((upstream-name . "CatDataAnalysis")))
    (build-system r-build-system)
    (home-page "https://github.com/cjgeyer/CatDataAnalysis")
    (synopsis "Datasets for Categorical Data Analysis by Agresti")
    (description
     "Datasets used in the book \"Categorical Data Analysis\" by Agresti (2012,
ISBN:978-0-470-46363-5) but not printed in the book.  Datasets and help pages
were automatically produced from the source
<https://users.stat.ufl.edu/~aa/cda/data.html> by the R script foo.R, which can
be found in the @code{GitHub} repository.")
    (license license:gpl2+)))

(define-public r-catcont
  (package
    (name "r-catcont")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "catcont" version))
       (sha256
        (base32 "0ix6ipm3nn9aq5vxirjga2kwwfnxn4v8ggfjlg5v9027v2r8rb96"))))
    (properties `((upstream-name . "catcont")))
    (build-system r-build-system)
    (propagated-inputs (list r-dplyr))
    (home-page "https://cran.r-project.org/package=catcont")
    (synopsis
     "Test, Identify, Select and Mutate Categorical or Continuous Values")
    (description
     "This package provides methods and utilities for testing, identifying, selecting
and mutating objects as categorical or continous types.  These functions work on
both atomic vectors as well as recursive objects: data.frames, data.tables,
tibbles, lists, etc..")
    (license (list license:gpl2
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-catastro
  (package
    (name "r-catastro")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CatastRo" version))
       (sha256
        (base32 "0v2gb6hvvh5zv5w3gvk07mnya2y2gra271if8nqi1khb7l52l516"))))
    (properties `((upstream-name . "CatastRo")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-tibble
                             r-terra
                             r-stringi
                             r-sf
                             r-rappdirs
                             r-mapspain
                             r-httr2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://ropenspain.github.io/CatastRo/")
    (synopsis "Interface to the API 'Sede Electronica Del Catastro'")
    (description
     "Access public spatial data available under the INSPIRE directive.  Tools for
downloading references and addresses of properties, as well as map images.")
    (license license:gpl2)))

(define-public r-catalog
  (package
    (name "r-catalog")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "catalog" version))
       (sha256
        (base32 "1j43c34qdklv8pskaidq5fxrygv9lngamdcrkij9c844qj7iff14"))))
    (properties `((upstream-name . "catalog")))
    (build-system r-build-system)
    (propagated-inputs (list r-sparklyr r-dplyr))
    (home-page "https://nathaneastwood.github.io/catalog/")
    (synopsis "Access the 'Spark Catalog' API via 'sparklyr'")
    (description
     "Gain access to the Spark Catalog API making use of the sparklyr API. Catalog
<https://spark.apache.org/docs/2.4.3/api/java/org/apache/spark/sql/catalog/Catalog.html>
is the interface for managing a metastore (aka metadata catalog) of relational
entities (e.g. database(s), tables, functions, table columns and temporary
views).")
    (license license:gpl2+)))

(define-public r-cata
  (package
    (name "r-cata")
    (version "0.1.0.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cata" version))
       (sha256
        (base32 "049wrqbmw77jlcwcikgjqjsnw4s3f6w4hvhilp2kvljpflmvjymf"))))
    (properties `((upstream-name . "cata")))
    (build-system r-build-system)
    (home-page "https://CRAN.R-project.org/package=cata")
    (synopsis "Analysis of Check-All-that-Apply (CATA) Data")
    (description
     "Package contains functions for analyzing check-all-that-apply (CATA) data from
consumer and sensory tests.  Cochran's Q test, @code{McNemar's} test, and
Penalty-Lift analysis are provided; for details, see Meyners, Castura & Carr
(2013) <doi:10.1016/j.foodqual.2013.06.010>.  Cluster analysis can be performed
using b-cluster analysis, then evaluated using various measures; for details,
see Castura, Meyners, Varela & NÃ¦s (2022) <doi:10.1016/j.foodqual.2022.104564>.
 Methods are adapted to cluster consumers based on their product-related hedonic
responses; for details, see Castura, Meyners, Pohjanheimo, Varela & NÃ¦s (2023)
<doi:10.1111/joss.12860>.")
    (license license:gpl2+)))

(define-public r-cat2cat
  (package
    (name "r-cat2cat")
    (version "0.4.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cat2cat" version))
       (sha256
        (base32 "0bfrl4mzkl7diigzksdri7kl549bxf767hl7s0whs6n7dyif0ap8"))))
    (properties `((upstream-name . "cat2cat")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Polkas/cat2cat")
    (synopsis
     "Handling an Inconsistently Coded Categorical Variable in a Longitudinal Dataset")
    (description
     "Unifying an inconsistently coded categorical variable between two different time
points in accordance with a mapping table.  The main rule is to replicate the
observation if it could be assigned to a few categories.  Then using frequencies
or statistical methods to approximate the probabilities of being assigned to
each of them.  This procedure was invented and implemented in the paper by
Nasinski, Majchrowska, and Broniatowska (2020)
<doi:10.24425/cejeme.2020.134747>.")
    (license (list license:gpl2+
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-cat
  (package
    (name "r-cat")
    (version "0.0-9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cat" version))
       (sha256
        (base32 "1wz6mbjzx03267yrszjimcd8yi82z2nfwyvz6l1ry2l300hv2qfs"))))
    (properties `((upstream-name . "cat")))
    (build-system r-build-system)
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=cat")
    (synopsis
     "Analysis and Imputation of Categorical-Variable Datasets with Missing Values")
    (description
     "This package performs analysis of categorical-variable with missing values.
Implements methods from Schafer, JL, Analysis of Incomplete Multivariate Data,
Chapman and Hall.")
    (license (license:fsdg-compatible "file://LICENSE"))))

(define-public r-cast
  (package
    (name "r-cast")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CAST" version))
       (sha256
        (base32 "1ga9j2c17gp14hgjd5wa8liak1m0qnhp27hl0r1iqk3gkxq3z5c9"))))
    (properties `((upstream-name . "CAST")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-twosamples
                             r-terra
                             r-sp
                             r-sf
                             r-plyr
                             r-ggplot2
                             r-forcats
                             r-fnn
                             r-data-table
                             r-caret))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/HannaMeyer/CAST")
    (synopsis "'caret' Applications for Spatial-Temporal Models")
    (description
     "Supporting functionality to run caret with spatial or spatial-temporal data.
caret is a frequently used package for model training and prediction using
machine learning.  CAST includes functions to improve spatial or
spatial-temporal modelling tasks using caret'.  It includes the newly suggested
Nearest neighbor distance matching cross-validation to estimate the performance
of spatial prediction models and allows for spatial variable selection to
selects suitable predictor variables in view to their contribution to the
spatial model performance.  CAST further includes functionality to estimate the
(spatial) area of applicability of prediction models.  Methods are described in
Meyer et al. (2018) <doi:10.1016/j.envsoft.2017.12.001>; Meyer et al. (2019)
<doi:10.1016/j.ecolmodel.2019.108815>; Meyer and Pebesma (2021)
<doi:10.1111/2041-210X.13650>; MilÃ  et al. (2022)
<doi:10.1111/2041-210X.13851>; Meyer and Pebesma (2022)
<doi:10.1038/s41467-022-29838-9>; Linnenbrink et al. (2023)
<doi:10.5194/egusphere-2023-1308>.  The package is described in detail in Meyer
et al. (2024) <doi:10.48550/@code{arXiv.2404.06978>}.")
    (license license:gpl2+)))

(define-public r-cassowaryr
  (package
    (name "r-cassowaryr")
    (version "2.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cassowaryr" version))
       (sha256
        (base32 "1zyna3nqkdb9f2cq2k41g2nbvw35gwz6yidz3ma1rpkha5cqdi1r"))))
    (properties `((upstream-name . "cassowaryr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tibble
                             r-splancs
                             r-progress
                             r-magrittr
                             r-interp
                             r-igraph
                             r-ggplot2
                             r-energy
                             r-dplyr
                             r-alphahull))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/numbats/cassowaryr")
    (synopsis
     "Compute Scagnostics on Pairs of Numeric Variables in a Data Set")
    (description
     "Computes a range of scatterplot diagnostics (scagnostics) on pairs of numerical
variables in a data set.  A range of scagnostics, including graph and
association-based scagnostics described by Leland Wilkinson and Graham Wills
(2008) <doi:10.1198/106186008X320465> and association-based scagnostics
described by Katrin Grimm (2016,ISBN:978-3-8439-3092-5) can be computed.
Summary and plotting functions are provided.")
    (license license:gpl3)))

(define-public r-cassandra
  (package
    (name "r-cassandra")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cassandRa" version))
       (sha256
        (base32 "19ar7yyigxgn05f9a594b161znjvdczn7gzlajjjc3dq1ccxw84b"))))
    (properties `((upstream-name . "cassandRa")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-tidyr
                             r-rlang
                             r-reshape2
                             r-purrr
                             r-magrittr
                             r-ggplot2
                             r-dplyr
                             r-boot
                             r-bipartite))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cassandRa")
    (synopsis
     "Finds Missing Links and Metric Confidence Intervals in Ecological Bipartite Networks")
    (description
     "This package provides methods to deal with under sampling in ecological
bipartite networks from Terry and Lewis (2020) Ecology <doi:10.1002/ecy.3047>
Includes tools to fit a variety of statistical network models and sample
coverage estimators to highlight most likely missing links.  Also includes
simple functions to resample from observed networks to generate confidence
intervals for common ecological network metrics.")
    (license license:gpl3)))

(define-public r-casmi
  (package
    (name "r-casmi")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CASMI" version))
       (sha256
        (base32 "1xj2d2p75hf6ypz57vbkrlcmf1gk52pv1fadyv9d40lzy8rc3667"))))
    (properties `((upstream-name . "CASMI")))
    (build-system r-build-system)
    (propagated-inputs (list r-entropyestimation r-entropy))
    (home-page "https://cran.r-project.org/package=CASMI")
    (synopsis "'CASMI'-Based Functions")
    (description
     "This package contains Coverage Adjusted Standardized Mutual Information
('CASMI')-based functions.  CASMI is a fundamental concept of a series of
methods.  For more information about CASMI and CASMI'-related methods, please
refer to the corresponding publications (e.g., a feature selection method, Shi,
J., Zhang, J., & Ge, Y. (2019) <doi:10.3390/e21121179>, and a dataset quality
measurement method, Shi, J., Zhang, J., & Ge, Y. (2019)
<doi:10.1109/ICHI.2019.8904553>) or contact the package author for the latest
updates.")
    (license license:gpl3)))

(define-public r-casmap
  (package
    (name "r-casmap")
    (version "0.6.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CASMAP" version))
       (sha256
        (base32 "1447d4gflan2093fb68inb2ysx5svb9vhnjc7lnkgpjsiam4p8yy"))))
    (properties `((upstream-name . "CASMAP")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CASMAP")
    (synopsis
     "Detection of Statistically Significant Combinations of SNPs in Association Mapping")
    (description
     "This package provides a significant pattern mining-based toolbox for
region-based genome-wide association studies and higher-order epistasis
analyses, implementing the methods described in Llinares-LÃ³pez et al. (2017)
<doi:10.1093/bioinformatics/btx071>.")
    (license license:gpl2+)))

(define-public r-casino
  (package
    (name "r-casino")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "casino" version))
       (sha256
        (base32 "07fphn46718gr1zm0xr43mwv7yk697xrc40lxxin315cf3gm0cka"))))
    (properties `((upstream-name . "casino")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-r6
                             r-purrr
                             r-magrittr
                             r-ggplot2
                             r-dplyr
                             r-crayon))
    (native-inputs (list r-knitr))
    (home-page "https://anthonypileggi.github.io/casino")
    (synopsis "Play Casino Games")
    (description
     "Play casino games in the R console, including poker, blackjack, and a slot
machine.  Try to build your fortune before you succumb to the gambler's ruin!")
    (license license:expat)))

(define-public r-cases
  (package
    (name "r-cases")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cases" version))
       (sha256
        (base32 "16yfypaqjnl3b99a55mri2j55xaj7dixw76wbpbfa3s4y0zylwpz"))))
    (properties `((upstream-name . "cases")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm
                             r-multcomp
                             r-matrix
                             r-magrittr
                             r-ggplot2
                             r-extradistr
                             r-dplyr
                             r-corrplot
                             r-copula
                             r-boot
                             r-bindata))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://github.com/maxwestphal/cases")
    (synopsis "Stratified Evaluation of Subgroup Classification Accuracy")
    (description
     "Enables simultaneous statistical inference for the accuracy of multiple
classifiers in multiple subgroups (strata).  For instance, allows to perform
multiple comparisons in diagnostic accuracy studies with co-primary endpoints
sensitivity and specificity. (Westphal, Max, and Antonia Zapf. (2021).
\"Statistical Inference for Diagnostic Test Accuracy Studies with Multiple
Comparisons.\" <@code{arXiv:2105.13469>}.).")
    (license license:expat)))

(define-public r-casematch
  (package
    (name "r-casematch")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "caseMatch" version))
       (sha256
        (base32 "1lzskh04v2mc6487zd2sq2l14si0mpid91f6avn0i3zz19nqyqsz"))))
    (properties `((upstream-name . "caseMatch")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=caseMatch")
    (synopsis "Identify Similar Cases for Qualitative Case Studies")
    (description
     "Allows users to identify similar cases for qualitative case studies using
statistical matching methods.")
    (license license:gpl2+)))

(define-public r-casecohortcoxsurvival
  (package
    (name "r-casecohortcoxsurvival")
    (version "0.0.36")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CaseCohortCoxSurvival" version))
       (sha256
        (base32 "13qb83x566m41kqy7jql6pfha2p9sr26bxqmkga7nwx6ddl7270p"))))
    (properties `((upstream-name . "CaseCohortCoxSurvival")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-nnet))
    (home-page "https://cran.r-project.org/package=CaseCohortCoxSurvival")
    (synopsis "Case-Cohort Cox Survival Inference")
    (description
     "Cox model inference for relative hazard and covariate-specific pure risk
estimated from stratified and unstratified case-cohort data as described in
Etievant, L., Gail, M.H. (Lifetime Data Analysis, 2024)
<doi:10.1007/s10985-024-09621-2>.")
    (license license:gpl2)))

(define-public r-casebasedreasoning
  (package
    (name "r-casebasedreasoning")
    (version "0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CaseBasedReasoning" version))
       (sha256
        (base32 "0ayckjq53lmdm429bvb4fjsbyy7cp3jgds30swmzq9qf75bnaa55"))))
    (properties `((upstream-name . "CaseBasedReasoning")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-survival
                             r-rms
                             r-rcppparallel
                             r-rcpparmadillo
                             r-rcpp
                             r-ranger
                             r-r6
                             r-purrr
                             r-pryr
                             r-ggplot2
                             r-dplyr
                             r-cowplot))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/sipemu/case-based-reasoning")
    (synopsis "Case Based Reasoning")
    (description
     "Case-based reasoning is a problem-solving methodology that involves solving a
new problem by referring to the solution of a similar problem in a large set of
previously solved problems.  The key aspect of Case Based Reasoning is to
determine the problem that \"most closely\" matches the new problem at hand.  This
is achieved by defining a family of distance functions and using these distance
functions as parameters for local averaging regression estimates of the final
result.  The optimal distance function is chosen based on a specific error
measure used in regression estimation.  This approach allows for efficient
problem-solving by leveraging past experiences and adapting solutions from
similar cases.  The underlying concept is inspired by the work of Dippon J.
(2002) <doi:10.1016/S0167-9473(02)00058-0>.")
    (license license:expat)))

(define-public r-casebase
  (package
    (name "r-casebase")
    (version "0.10.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "casebase" version))
       (sha256
        (base32 "0p2dixiww3l1lwbr512is6prjm606kx8y0wlq90mwfkxbzzq59d9"))))
    (properties `((upstream-name . "casebase")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam r-survival r-mgcv r-ggplot2 r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://sahirbhatnagar.com/casebase/")
    (synopsis
     "Fitting Flexible Smooth-in-Time Hazards and Risk Functions via Logistic and Multinomial Regression")
    (description
     "Fit flexible and fully parametric hazard regression models to survival data with
single event type or multiple competing causes via logistic and multinomial
regression.  Our formulation allows for arbitrary functional forms of time and
its interactions with other predictors for time-dependent hazards and hazard
ratios.  From the fitted hazard model, we provide functions to readily calculate
and plot cumulative incidence and survival curves for a given covariate profile.
 This approach accommodates any log-linear hazard function of prognostic time,
treatment, and covariates, and readily allows for non-proportionality.  We also
provide a plot method for visualizing incidence density via population time
plots.  Based on the case-base sampling approach of Hanley and Miettinen (2009)
<DOI:10.2202/1557-4679.1125>, Saarela and Arjas (2015) <DOI:10.1111/sjos.12125>,
and Saarela (2015) <DOI:10.1007/s10985-015-9352-x>.")
    (license license:expat)))

(define-public r-cascsim
  (package
    (name "r-cascsim")
    (version "0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cascsim" version))
       (sha256
        (base32 "0n6frnbby1pjpx1z9lzxflmja2mg0dy99c5f7biakpaqi82x5xjb"))))
    (properties `((upstream-name . "cascsim")))
    (build-system r-build-system)
    (propagated-inputs (list r-scatterplot3d r-r2html r-moments r-fitdistrplus
                             r-copula))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cascsim")
    (synopsis "Casualty Actuarial Society Individual Claim Simulator")
    (description
     "It is an open source insurance claim simulation engine sponsored by the Casualty
Actuarial Society.  It generates individual insurance claims including open
claims, reopened claims, incurred but not reported claims and future claims.  It
also includes claim data fitting functions to help set simulation assumptions.
It is useful for claim level reserving analysis.  Parodi (2013)
<https://www.actuaries.org.uk/documents/triangle-free-reserving-non-traditional-framework-estimating-reserves-and-reserve-uncertainty>.")
    (license license:gpl3)))

(define-public r-cascore
  (package
    (name "r-cascore")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CASCORE" version))
       (sha256
        (base32 "1ns20gxm7a4n2h6zdysz4p7pij5mivhdj2ssccdy36g1lihgjz8q"))))
    (properties `((upstream-name . "CASCORE")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma))
    (home-page "https://arxiv.org/abs/2306.15616")
    (synopsis
     "Covariate Assisted Spectral Clustering on Ratios of Eigenvectors")
    (description
     "This package provides functions for implementing the novel algorithm CASCORE,
which is designed to detect latent community structure in graphs with node
covariates.  This algorithm can handle models such as the covariate-assisted
degree corrected stochastic block model (CADCSBM).  CASCORE specifically
addresses the disagreement between the community structure inferred from the
adjacency information and the community structure inferred from the covariate
information.  For more detailed information, please refer to the reference
paper: Yaofang Hu and Wanjie Wang (2022) <@code{arXiv:2306.15616>}.  In addition
to CASCORE, this package includes several classical community detection
algorithms that are compared to CASCORE in our paper.  These algorithms are:
Spectral Clustering On Ratios-of Eigenvectors (SCORE), normalized PCA, ordinary
PCA, network-based clustering, covariates-based clustering and
covariate-assisted spectral clustering (CASC).  By providing these additional
algorithms, the package enables users to compare their performance with CASCORE
in community detection tasks.")
    (license license:gpl2)))

(define-public r-cascadeselect
  (package
    (name "r-cascadeselect")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cascadeSelect" version))
       (sha256
        (base32 "1hb8h0v7c76jbhqp713wkmx278q9calpg1rwgdhbrdbq6caldhq7"))))
    (properties `((upstream-name . "cascadeSelect")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-reactr r-htmltools r-fontawesome))
    (home-page "https://github.com/stla/cascadeSelect")
    (synopsis "Cascade Select Input for 'Shiny'")
    (description
     "This package provides a cascade select widget for usage in Shiny applications.
This is useful for selection of hierarchical choices (e.g. continent, country,
city).  It is taken from the @code{JavaScript} library @code{PrimeReact}'.")
    (license license:gpl3)))

(define-public r-cascadedata
  (package
    (name "r-cascadedata")
    (version "1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CascadeData" version))
       (sha256
        (base32 "0cbnp8mqv3alsz7b5fa8djg1yd46zkn1f3b0pqww2yn8zavd4fih"))))
    (properties `((upstream-name . "CascadeData")))
    (build-system r-build-system)
    (home-page "https://fbertran.github.io/CascadeData/")
    (synopsis "Experimental Data of Cascade Experiments in Genomics")
    (description
     "These experimental expression data (5 leukemic CLL B-lymphocyte of aggressive
form from GSE39411', <doi:10.1073/pnas.1211130110>), after B-cell receptor
stimulation, are used as examples by packages such as the Cascade one, a
modeling tool allowing gene selection, reverse engineering, and prediction in
cascade networks.  Jung, N., Bertrand, F., Bahram, S., Vallat, L., and
Maumy-Bertrand, M. (2014) <doi:10.1093/bioinformatics/btt705>.")
    (license license:gpl2+)))

(define-public r-cascade
  (package
    (name "r-cascade")
    (version "2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Cascade" version))
       (sha256
        (base32 "1hfbv9129rnrjqspjd8wnhw0qrp1m142bixlwddzr6j2sg7r8s20"))))
    (properties `((upstream-name . "Cascade")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam
                             r-tnet
                             r-survival
                             r-nnls
                             r-magic
                             r-limma
                             r-lattice
                             r-lars
                             r-igraph
                             r-cluster
                             r-animation
                             r-abind))
    (native-inputs (list r-r-rsp))
    (home-page "https://fbertran.github.io/Cascade/")
    (synopsis
     "Selection, Reverse-Engineering and Prediction in Cascade Networks")
    (description
     "This package provides a modeling tool allowing gene selection, reverse
engineering, and prediction in cascade networks.  Jung, N., Bertrand, F.,
Bahram, S., Vallat, L., and Maumy-Bertrand, M. (2014)
<doi:10.1093/bioinformatics/btt705>.")
    (license license:gpl2+)))

(define-public r-casabourse
  (package
    (name "r-casabourse")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "casabourse" version))
       (sha256
        (base32 "1s7zp44cmfnq4l9rzydqpnv9s2z4v7bvng8diz3bhzkg2zhpglnq"))))
    (properties `((upstream-name . "casabourse")))
    (build-system r-build-system)
    (propagated-inputs (list r-rvest r-rjsonio r-r-utils r-gsheet))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/AODiakite")
    (synopsis "Casablanca Stock Exchange Data")
    (description
     "It provides real-time data from the Casablanca Stock Exchange.  The objective is
to facilitate access to data for all users of the R programming language.  It
includes a variety of data accessible just by function call.")
    (license license:gpl2)))

(define-public r-cartography
  (package
    (name "r-cartography")
    (version "3.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cartography" version))
       (sha256
        (base32 "1sww3n7glkzrpf1ki31z8309qr5496m1rm5gj3cprwif8fxfyjx5"))))
    (properties `((upstream-name . "cartography")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp
                             r-sf
                             r-rcpp
                             r-raster
                             r-png
                             r-curl
                             r-classint))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/riatelab/cartography/")
    (synopsis "Thematic Cartography")
    (description
     "Create and integrate maps in your R workflow.  This package helps to design
cartographic representations such as proportional symbols, choropleth, typology,
flows or discontinuities maps.  It also offers several features that improve the
graphic presentation of maps, for instance, map palettes, layout elements
(scale, north arrow, title...), labels or legends.  See Giraud and Lambert
(2017) <doi:10.1007/978-3-319-57336-6_13>.")
    (license license:gpl3)))

(define-public r-cartographr
  (package
    (name "r-cartographr")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cartographr" version))
       (sha256
        (base32 "0difm4rnsbjr103fhabvg4g41qwa9klpp65k2yzn25x02caypg4v"))))
    (properties `((upstream-name . "cartographr")))
    (build-system r-build-system)
    (propagated-inputs (list r-sysfonts
                             r-showtext
                             r-sf
                             r-osmdata
                             r-ggplot2
                             r-crayon
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://da-wi.github.io/cartographr/")
    (synopsis "Crafting Print-Ready Maps and Layered Visualizations")
    (description
     "Simplifying the creation of print-ready maps, this package offers a
user-friendly interface derived from ggplot2 for handling @code{OpenStreetMap}
data.  It streamlines the map-making process, allowing users to focus on the
story their maps tell.  Transforming raw geospatial data into informative
visualizations is made easy with simple features sf geometries.  Whether for
urban planning, environmental studies, or impactful public presentations, this
tool facilitates straightforward and effective map creation.  Enhance the
dissemination of spatial information with high-quality, narrative-driven
visualizations!")
    (license license:gpl3+)))

(define-public r-cartographer
  (package
    (name "r-cartographer")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cartographer" version))
       (sha256
        (base32 "0jdnwrzxrvwcjf80dn0alhgz3713vfhwd4cs7k386x188y38l8ia"))))
    (properties `((upstream-name . "cartographer")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf r-rlang r-dplyr r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/cidm-ph/cartographer")
    (synopsis "Turn Place Names into Map Data")
    (description
     "This package provides a tool for easily matching spatial data when you have a
list of place/region names.  You might have a data frame that came from a
spreadsheet tracking some data by suburb or state.  This package can convert it
into a spatial data frame ready for plotting.  The actual map data is provided
by other packages (or your own code).")
    (license license:expat)))

(define-public r-cartogramr
  (package
    (name "r-cartogramr")
    (version "1.2-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cartogramR" version))
       (sha256
        (base32 "16xa989hiaq17qgys14p68z2jdn79pyylzhnd5y5cqd43hiixkn0"))))
    (properties `((upstream-name . "cartogramR")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf r-data-table r-cleancall))
    (home-page "https://cran.r-project.org/package=cartogramR")
    (synopsis "Continuous Cartogram")
    (description
     "Procedures for making continuous cartogram.  Procedures available are: flow
based cartogram (Gastner & Newman (2004) <doi:10.1073/pnas.0400280101>), fast
flow based cartogram (Gastner, Seguy & More (2018)
<doi:10.1073/pnas.1712674115>), rubber band based cartogram (Dougenik et al.
(1985) <doi:10.1111/j.0033-0124.1985.00075.x>).")
    (license license:expat)))

(define-public r-cartograflow
  (package
    (name "r-cartograflow")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cartograflow" version))
       (sha256
        (base32 "0bfw04wjd7bghw08ynnfc43yh80vhg9vpmd8qsx328860f1q5vw6"))))
    (properties `((upstream-name . "cartograflow")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf
                             r-rlang
                             r-reshape2
                             r-plotly
                             r-igraph
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/fbahoken/cartogRaflow")
    (synopsis "Filtering Matrix for Flow Mapping")
    (description
     "This package provides functions to prepare and filter an origin-destination
matrix for thematic flow mapping purposes.  This comes after Bahoken, Francoise
(2016), Mapping flow matrix a contribution, @code{PhD} in Geography -
Territorial sciences.  See Bahoken (2017) <doi:10.4000/netcom.2565>.")
    (license license:gpl3)))

(define-public r-carsurv
  (package
    (name "r-carsurv")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "carSurv" version))
       (sha256
        (base32 "0wv7lp10i4sdfqyizg77ghblp3pcp7wzhs946sm0wl6w00krav9j"))))
    (properties `((upstream-name . "carSurv")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rcpp r-mboost r-fdrtool r-corpcor))
    (home-page "https://cran.r-project.org/package=carSurv")
    (synopsis "Correlation-Adjusted Regression Survival (CARS) Scores")
    (description
     "This package contains functions to estimate the Correlation-Adjusted Regression
Survival (CARS) Scores.  The method is described in Welchowski, T. and Zuber, V.
and Schmid, M., (2018), Correlation-Adjusted Regression Survival Scores for
High-Dimensional Variable Selection, <@code{arXiv:1802.08178>}.")
    (license license:gpl3)))

(define-public r-carrot
  (package
    (name "r-carrot")
    (version "3.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CARRoT" version))
       (sha256
        (base32 "1himmzsshhr2f5hljr60p7w3wq5ybdsb0f9kiga56hpppg352l3f"))))
    (properties `((upstream-name . "CARRoT")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-nnet r-foreach r-doparallel))
    (home-page "https://cran.r-project.org/package=CARRoT")
    (synopsis
     "Predicting Categorical and Continuous Outcomes Using One in Ten Rule")
    (description
     "Predicts categorical or continuous outcomes while concentrating on a number of
key points.  These are Cross-validation, Accuracy, Regression and Rule of Ten or
\"one in ten rule\" (CAR@code{RoT}), and, in addition to it R-squared statistics,
prior knowledge on the dataset etc.  It performs the cross-validation specified
number of times by partitioning the input into training and test set and fitting
linear/multinomial/binary regression models to the training set.  All regression
models satisfying chosen constraints are fitted and the ones with the best
predictive power are given as an output.  Best predictive power is understood as
highest accuracy in case of binary/multinomial outcomes, smallest absolute and
relative errors in case of continuous outcomes.  For binary case there is also
an option of finding a regression model which gives the highest AUROC (Area
Under Receiver Operating Curve) value.  The option of parallel toolbox is also
available.  Methods are described in Peduzzi et al. (1996)
<doi:10.1016/S0895-4356(96)00236-3> , Rhemtulla et al. (2012)
<doi:10.1037/a0029315>, Riley et al. (2018) <doi:10.1002/sim.7993>, Riley et al.
(2019) <doi:10.1002/sim.7992>.")
    (license license:gpl2)))

(define-public r-carpenter
  (package
    (name "r-carpenter")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "carpenter" version))
       (sha256
        (base32 "13ahhdc6f5ngrhb7slqbxzfs3wswixh0argyr6l46cv4fdkaa80s"))))
    (properties `((upstream-name . "carpenter")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-pander
                             r-magrittr
                             r-lazyeval
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/lwjohnst86/carpenter")
    (synopsis "Build Common Tables of Summary Statistics for Reports")
    (description
     "Mainly used to build tables that are commonly presented for bio-medical/health
research, such as basic characteristic tables or descriptive statistics.")
    (license license:expat)))

(define-public r-caroline
  (package
    (name "r-caroline")
    (version "0.9.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "caroline" version))
       (sha256
        (base32 "15q2cqfrfvy934cdfg886sp6lzmfp1bqddjpkv0bhqzpnmscbpq4"))))
    (properties `((upstream-name . "caroline")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=caroline")
    (synopsis
     "Collection of Database, Data Structure, Visualization, and Utility Functions for R")
    (description
     "The caroline R library contains dozens of functions useful for: database
migration (@code{dbWriteTable2}), database style joins & aggregation (nerge,
@code{groupBy} & @code{bestBy}), data structure conversion (nv, tab2df), legend
table making (sstable & leghead), plot annotation (labsegs & mvlabs), data
visualization (pies, sparge, & @code{raPlot}), character string manipulation (m
& pad), file I/O (write.delim), batch scripting and more.  The package's
greatest contributions lie in the database style merge, aggregation and
interface functions as well as in it's extensive use and propagation of row,
column and vector names in most functions.")
    (license license:artistic2.0)))

(define-public r-caroc
  (package
    (name "r-caroc")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "caROC" version))
       (sha256
        (base32 "0cklvzfg95yyr37hdfmrna2z6lnhf9f6rrqcjsba1wjmqs8abgsh"))))
    (properties `((upstream-name . "caROC")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer r-quantreg))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=caROC")
    (synopsis "Continuous Biomarker Evaluation with Adjustment of Covariates")
    (description
     "Compute covariate-adjusted specificity at controlled sensitivity level, or
covariate-adjusted sensitivity at controlled specificity level, or
covariate-adjust receiver operating characteristic curve, or covariate-adjusted
thresholds at controlled sensitivity/specificity level.  All statistics could
also be computed for specific sub-populations given their covariate values.
Methods are described in Ziyi Li, Yijian Huang, Datta Patil, Martin G. Sanda
(2021+) \"Covariate adjustment in continuous biomarker assessment\".")
    (license license:gpl2)))

(define-public r-carms
  (package
    (name "r-carms")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CARMS" version))
       (sha256
        (base32 "0w7xhvwvn5vsc0w9fn3mh750lfqh5183ads1ihv7ypdhdywb5c0p"))))
    (properties `((upstream-name . "CARMS")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-diagram))
    (home-page "http://www.openreliability.org")
    (synopsis "Continuous Time Markov Rate Modeling for Reliability Analysis")
    (description
     "Emulation of an application originally created by Paul Pukite.  Computer Aided
Rate Modeling and Simulation.  Jan Pukite and Paul Pukite, (1998, ISBN
978-0-7803-3482), William J. Stewart, (1994, ISBN: 0-691-03699-3).")
    (license license:gpl3+)))

(define-public r-carme
  (package
    (name "r-carme")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CARME" version))
       (sha256
        (base32 "0nam14g052swb44sw07as4agk0z47f7mc1kqlj0z9m1ywsbisnpl"))))
    (properties `((upstream-name . "CARME")))
    (build-system r-build-system)
    (propagated-inputs (list r-stanheaders
                             r-rstantools
                             r-rstan
                             r-rcppparallel
                             r-rcppeigen
                             r-rcpp
                             r-mass
                             r-expm
                             r-bh))
    (home-page "https://cran.r-project.org/package=CARME")
    (synopsis "CAR-MM Modelling in Stan")
    (description
     "Stan based functions to estimate CAR-MM models.  These models allow to estimate
Generalised Linear Models with CAR (conditional autoregressive) spatial random
effects for spatially and temporally misaligned data, provided a suitable
Multiple Membership matrix.  The main references are Gramatica, Liverani and
Congdon (2023) <doi:10.1214/23-BA1370>, Petrof, Neyens, Nuyts, Nackaerts, Nemery
and Faes (2020) <doi:10.1002/sim.8697> and Gramatica, Congdon and Liverani
<doi:10.1111/rssc.12480>.")
    (license license:gpl3+)))

(define-public r-carm
  (package
    (name "r-carm")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CARM" version))
       (sha256
        (base32 "068rpz7bjc767yw4vcrf63ckyvdk2f1kskmfcc7955qf9ki5c49c"))))
    (properties `((upstream-name . "CARM")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-dplyr r-arrangements))
    (home-page "https://cran.r-project.org/package=CARM")
    (synopsis
     "Covariate-Adjusted Adaptive Randomization via Mahalanobis-Distance")
    (description
     "In randomized controlled trial (RCT), balancing covariate is often one of the
most important concern.  CARM package provides functions to balance the
covariates and generate allocation sequence by covariate-adjusted Adaptive
Randomization via Mahalanobis-distance (ARM) for RCT. About what ARM is and how
it works please see Y. Qin, Y. Li, W. Ma, H. Yang, and F. Hu (2022). \"Adaptive
randomization via Mahalanobis distance\" Statistica Sinica.
<doi:10.5705/ss.202020.0440>.  In addition, the package is also suitable for the
randomization process of multi-arm trials.  For details, please see Yang H, Qin
Y, Wang F, et al. (2023). \"Balancing covariates in multi-arm trials via adaptive
randomization\" Computational Statistics & Data
Analysis.<doi:10.1016/j.csda.2022.107642>.")
    (license license:gpl2+)))

(define-public r-carlson
  (package
    (name "r-carlson")
    (version "3.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Carlson" version))
       (sha256
        (base32 "19z4b74kjqpgbb87ddd5sx0ydjnaa54mqrc1yz4wdl8md7d1anbq"))))
    (properties `((upstream-name . "Carlson")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://github.com/stla/Carlson")
    (synopsis "Carlson Elliptic Integrals and Incomplete Elliptic Integrals")
    (description
     "Evaluation of the Carlson elliptic integrals and the incomplete elliptic
integrals with complex arguments.  The implementations use Carlson's algorithms
<doi:10.1007/BF02198293>.  Applications of elliptic integrals include
probability distributions, geometry, physics, mechanics, electrodynamics,
statistical mechanics, astronomy, geodesy, geodesics on conics, and magnetic
field calculations.")
    (license license:gpl3)))

(define-public r-carletonstats
  (package
    (name "r-carletonstats")
    (version "2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CarletonStats" version))
       (sha256
        (base32 "1d9g773l1ra5cr2q3azlkpkqy2035zq065cpfyavf57js0ks5ciq"))))
    (properties `((upstream-name . "CarletonStats")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales r-patchwork r-ggplot2))
    (home-page "https://github.com/aloy/CarletonStats")
    (synopsis "Functions for Statistics Classes at Carleton College")
    (description
     "Includes commands for bootstrapping and permutation tests, a command for created
grouped bar plots, and a demo of the quantile-normal plot for data drawn from
different distributions.")
    (license license:gpl2)))

(define-public r-caribou
  (package
    (name "r-caribou")
    (version "1.1-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "caribou" version))
       (sha256
        (base32 "1spz5ymqv8k48yg0rrdrs9ylasdif2jwcq2z33gagd6yrim1a3q3"))))
    (properties `((upstream-name . "caribou")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=caribou")
    (synopsis "Estimation of Caribou Abundance Based on Radio Telemetry Data")
    (description
     "Estimation of population size of migratory caribou herds based on large scale
aggregations monitored by radio telemetry.  It implements the methodology found
in the article by Rivest et al. (1998) about caribou abundance estimation.  It
also includes a function based on the Lincoln-Petersen Index as applied to radio
telemetry data by White and Garrott (1990).")
    (license license:gpl2)))

(define-public r-cargo
  (package
    (name "r-cargo")
    (version "0.4.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cargo" version))
       (sha256
        (base32 "0r1c9cklnagan37kinblwvm3icq7krmyqwx9x6iss1br0a4580ch"))))
    (properties `((upstream-name . "cargo")))
    (build-system r-build-system)
    (home-page "https://github.com/dbdahl/cargo-framework")
    (synopsis "Develop R Packages using Rust")
    (description
     "This package provides a framework is provided to develop R packages using Rust
<https://www.rust-lang.org/> with minimal overhead, and more wrappers are easily
added.  Help is provided to use Cargo <https://doc.rust-lang.org/cargo/> in a
manner consistent with CRAN policies.  Rust code can also be embedded directly
in an R script.  The package is not official, affiliated with, nor endorsed by
the Rust project.")
    (license (list license:expat license:asl2.0))))

(define-public r-carfima
  (package
    (name "r-carfima")
    (version "2.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "carfima" version))
       (sha256
        (base32 "1n68jqn42m54xn7jq8qywrpnvggrcsgvgnlqg6nw0pgiplbkynih"))))
    (properties `((upstream-name . "carfima")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncnorm r-pracma r-mvtnorm r-invgamma
                             r-deoptim))
    (home-page "https://cran.r-project.org/package=carfima")
    (synopsis
     "Continuous-Time Fractionally Integrated ARMA Process for Irregularly Spaced Long-Memory Time Series Data")
    (description
     "We provide a toolbox to fit a continuous-time fractionally integrated ARMA
process (CARFIMA) on univariate and irregularly spaced time series data via both
frequentist and Bayesian machinery.  A general-order CARFIMA(p, H, q) model for
p>q is specified in Tsai and Chan (2005) <doi:10.1111/j.1467-9868.2005.00522.x>
and it involves p+q+2 unknown model parameters, i.e., p AR parameters, q MA
parameters, Hurst parameter H, and process uncertainty (standard deviation)
sigma.  Also, the model can account for heteroscedastic measurement errors, if
the information about measurement error standard deviations is known.  The
package produces their maximum likelihood estimates and asymptotic uncertainties
using a global optimizer called the differential evolution algorithm.  It also
produces posterior samples of the model parameters via Metropolis-Hastings
within a Gibbs sampler equipped with adaptive Markov chain Monte Carlo.  These
fitting procedures, however, may produce numerical errors if p>2.  The toolbox
also contains a function to simulate discrete time series data from CARFIMA(p,
H, q) process given the model parameters and observation times.")
    (license license:gpl2)))

(define-public r-caretforecast
  (package
    (name "r-caretforecast")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "caretForecast" version))
       (sha256
        (base32 "0z8r64cb3w0m5a7khysvfmnf1ywa7svi5lvxiwx1a6j6868zbxlr"))))
    (properties `((upstream-name . "caretForecast")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-generics r-forecast r-dplyr r-caret))
    (home-page "https://github.com/Akai01/caretForecast")
    (synopsis
     "Conformal Time Series Forecasting Using State of Art Machine Learning Algorithms")
    (description
     "Conformal time series forecasting using the caret infrastructure.  It provides
access to state-of-the-art machine learning models for forecasting applications.
 The hyperparameter of each model is selected based on time series
cross-validation, and forecasting is done recursively.")
    (license license:gpl3+)))

(define-public r-caresid
  (package
    (name "r-caresid")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "caresid" version))
       (sha256
        (base32 "1mrnvg6dl1344j880ngw9hxfg5rc82ljv25ahc1pqgs0ji8v5di2"))))
    (properties `((upstream-name . "caresid")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggrepel r-ggplot2 r-ca))
    (home-page "https://cran.r-project.org/package=caresid")
    (synopsis "Correspondence Analysis Plot and Associations Visualisation")
    (description
     "This package performs a Correspondence Analysis (CA) on a contingency table and
creates a scatterplot of the row and column points on the selected dimensions.
Optionally, the function can add segments to the plot to visualize significant
associations between row and column categories on the basis of positive
(unadjusted) standardized residuals larger than a given threshold.")
    (license license:gpl2+)))

(define-public r-careless
  (package
    (name "r-careless")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "careless" version))
       (sha256
        (base32 "1ncfcz5zznchcj4ndfhk9lb72l766yzsiicq5ry0m4djn74d9lva"))))
    (properties `((upstream-name . "careless")))
    (build-system r-build-system)
    (propagated-inputs (list r-psych))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ryentes/careless/")
    (synopsis "Procedures for Computing Indices of Careless Responding")
    (description
     "When taking online surveys, participants sometimes respond to items without
regard to their content.  These types of responses, referred to as careless or
insufficient effort responding, constitute significant problems for data
quality, leading to distortions in data analysis and hypothesis testing, such as
spurious correlations.  The R package careless provides solutions designed to
detect such careless / insufficient effort responses by allowing easy
calculation of indices proposed in the literature.  It currently supports the
calculation of longstring, even-odd consistency, psychometric synonyms/antonyms,
Mahalanobis distance, and intra-individual response variability (also termed
inter-item standard deviation).  For a review of these methods, see Curran
(2016) <doi:10.1016/j.jesp.2015.07.006>.")
    (license license:expat)))

(define-public r-carecall
  (package
    (name "r-carecall")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "caRecall" version))
       (sha256
        (base32 "1ml8cfsi4h8q5f0y3m6s5v8sdldj302ndl75m6f7lagsiiiwhd77"))))
    (properties `((upstream-name . "caRecall")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-jsonlite r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/WraySmith/caRecall")
    (synopsis "Government of Canada Vehicle Recalls Database API Wrapper")
    (description
     "This package provides API access to the Government of Canada Vehicle Recalls
Database <https://tc.api.canada.ca/en/detail?api=VRDB> used by the Defect
Investigations and Recalls Division for vehicles, tires, and child car seats.
The API wrapper provides access to recall summary information searched using
make, model, and year range, as well as detailed recall information searched
using recall number.")
    (license license:expat)))

(define-public r-care4cmodel
  (package
    (name "r-care4cmodel")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "care4cmodel" version))
       (sha256
        (base32 "0526z49v4mxfxjlpzjnqyzc8j2lvj1aw47f3izsk1vrs193vxnvw"))))
    (properties `((upstream-name . "care4cmodel")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-rlang
                             r-rdpack
                             r-purrr
                             r-ggplot2
                             r-dplyr
                             r-desolve))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=care4cmodel")
    (synopsis "Carbon-Related Assessment of Silvicultural Concepts")
    (description
     "This package provides a simulation model and accompanying functions that support
assessing silvicultural concepts on the forest estate level with a focus on the
CO2 uptake by wood growth and CO2 emissions by forest operations.  For achieving
this, a virtual forest estate area is split into the areas covered by typical
phases of the silvicultural concept of interest.  Given initial area shares of
these phases, the dynamics of these areas is simulated.  The typical carbon
stocks and flows which are known for all phases are attributed post-hoc to the
areas and upscaled to the estate level.  CO2 emissions by forest operations are
estimated based on the amounts and dimensions of the harvested timber.
Probabilities of damage events are taken into account.")
    (license license:gpl3+)))

(define-public r-care
  (package
    (name "r-care")
    (version "1.1.11")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "care" version))
       (sha256
        (base32 "0897v6acxf1myncd507by8zp7aga77pschyix1m4fzgpc6z35vlm"))))
    (properties `((upstream-name . "care")))
    (build-system r-build-system)
    (propagated-inputs (list r-corpcor))
    (home-page "https://strimmerlab.github.io/software/care/")
    (synopsis "High-Dimensional Regression and CAR Score Variable Selection")
    (description
     "This package implements the regression approach of Zuber and Strimmer (2011)
\"High-dimensional regression and variable selection using CAR scores\" SAGMB 10:
34, <DOI:10.2202/1544-6115.1730>.  CAR scores measure the correlation between
the response and the Mahalanobis-decorrelated predictors.  The squared CAR score
is a natural measure of variable importance and provides a canonical ordering of
variables.  This package provides functions for estimating CAR scores, for
variable selection using CAR scores, and for estimating corresponding regression
coefficients.  Both shrinkage as well as empirical estimators are available.")
    (license license:gpl3+)))

(define-public r-cardx
  (package
    (name "r-cardx")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cardx" version))
       (sha256
        (base32 "0p10sm10b4d7qnpn96yq4akvx3m5wrczg3zz12jlx8776x33m6vq"))))
    (properties `((upstream-name . "cardx")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rlang
                             r-lifecycle
                             r-glue
                             r-dplyr
                             r-cli
                             r-cards))
    (home-page "https://insightsengineering.github.io/cardx/")
    (synopsis "Extra Analysis Results Data Utilities")
    (description
     "Create extra Analysis Results Data (ARD) summary objects.  The package
supplements the simple ARD functions from the cards package, exporting functions
to put statistical results in the ARD format.  These objects are used and
re-used to construct summary tables, visualizations, and written reports.")
    (license license:asl2.0)))

(define-public r-cardinalr
  (package
    (name "r-cardinalr")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cardinalR" version))
       (sha256
        (base32 "1hqdvxialk41r6l0k7vllh4bxdqx2ci4rcppd7nl0w1d3lz9561i"))))
    (properties `((upstream-name . "cardinalR")))
    (build-system r-build-system)
    (propagated-inputs (list r-purrr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/JayaniLakshika/cardinalR")
    (synopsis "Collection of Data Structures")
    (description
     "This package provides a collection of simple simulation datasets designed for
generating Nonlinear Dimension Reduction representations techniques such as
t-distributed Stochastic Neighbor Embedding, and Uniform Manifold Approximation
and Projection.  These datasets serve as a valuable resource for understanding
the reliability of Nonlinear Dimension Reduction representations in various
contexts.")
    (license license:expat)))

(define-public r-cardidates
  (package
    (name "r-cardidates")
    (version "0.4.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cardidates" version))
       (sha256
        (base32 "0b52cmg870s6icq53c6v6zjgz6w1pv02p83r8k4q0sksq5fy0ik4"))))
    (properties `((upstream-name . "cardidates")))
    (build-system r-build-system)
    (propagated-inputs (list r-pastecs r-lattice r-boot))
    (home-page "http://cardidates.r-forge.r-project.org")
    (synopsis "Identification of Cardinal Dates in Ecological Time Series")
    (description
     "Identification of cardinal dates (begin, time of maximum, end of mass
developments) in ecological time series using fitted Weibull functions.")
    (license license:gpl2+)))

(define-public r-card-pro
  (package
    (name "r-card-pro")
    (version "2.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "card.pro" version))
       (sha256
        (base32 "1qhca4lyzqwwkf6q2kni3d8wns0wjm1dpxrj40dfnh76ixrpqldg"))))
    (properties `((upstream-name . "card.pro")))
    (build-system r-build-system)
    (arguments
     (list
      #:modules '((guix build r-build-system)
                  (guix build minify-build-system)
                  (guix build utils)
                  (ice-9 match))
      #:imported-modules `(,@%r-build-system-modules (guix build
                                                      minify-build-system))
      #:phases '(modify-phases %standard-phases
                  (add-after 'unpack 'process-javascript
                    (lambda* (#:key inputs #:allow-other-keys)
                      (with-directory-excursion "inst/"
                        (for-each (match-lambda
                                    ((source . target) (minify source
                                                               #:target target)))
                                  '())))))))
    (propagated-inputs (list r-shiny r-quickcode r-htmltools))
    (native-inputs (list r-knitr esbuild))
    (home-page "https://cardpro.rpkg.net")
    (synopsis "Lightweight Modern & Responsive Card Component for 'shiny'")
    (description
     "Responsive and modern HTML card essentials for shiny dashboard.  This novel card
component in Bootstrap provides a flexible and extensible content container with
multiple variants and options for building robust R based apps e.g for graph
build or machine learning projects.  The features rely on a combination of
JQuery <https://jquery.com> and CSS styles to improve the card functionality.")
    (license license:expat)))

(define-public r-card
  (package
    (name "r-card")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "card" version))
       (sha256
        (base32 "1api0j06fp5av5a48vnnm1wvwdcskynf0xsj9pb41njxdh9v8daf"))))
    (properties `((upstream-name . "card")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-survival
                             r-stringr
                             r-sf
                             r-rlang
                             r-recipes
                             r-readr
                             r-purrr
                             r-magrittr
                             r-lutz
                             r-lubridate
                             r-hmisc
                             r-hardhat
                             r-ggrepel
                             r-ggplot2
                             r-generics
                             r-dplyr
                             r-data-table
                             r-broom))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/asshah4/card")
    (synopsis "Cardiovascular and Autonomic Research Design")
    (description
     "This package provides tools that can aid in the assessment of the autonomic
regulation of cardiovascular physiology.  The aims of this package are to: 1)
study electrocardiography (both intervals and morphology) as extensions of
signal processing, 2) study circadian rhythms and how it effects autonomic
physiology, 3) assess clinical risk of autonomic dysfunction on cardiovascular
health through the perspective of epidemiology and causality.  The analysis of
circadian rhythms through cosinor analysis are built upon the methods by
Cornelissen (2014) <doi:10.1186/1742-4682-11-16> and Refinetti, Cornelissen,
Halberg (2014) <doi:10.1080/09291010600903692>.")
    (license license:expat)))

(define-public r-carcass
  (package
    (name "r-carcass")
    (version "1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "carcass" version))
       (sha256
        (base32 "09l9yk7knfjhrcpwfwmgla9ghnpg1b10aljmdl70j5kxdiafkfn7"))))
    (properties `((upstream-name . "carcass")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-mass r-lme4 r-expm r-arm))
    (home-page "https://cran.r-project.org/package=carcass")
    (synopsis "Estimation of the Number of Fatalities from Carcass Searches")
    (description
     "The number of bird or bat fatalities from collisions with buildings, towers or
wind energy turbines can be estimated based on carcass searches and
experimentally assessed carcass persistence times and searcher efficiency.
Functions for estimating the probability that a bird or bat that died is found
by a searcher are provided.  Further functions calculate the posterior
distribution of the number of fatalities based on the number of carcasses found
and the estimated detection probability.")
    (license license:gpl2)))

(define-public r-carbonr
  (package
    (name "r-carbonr")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "carbonr" version))
       (sha256
        (base32 "173yy0rf5sahncvghz1nh74k2qhzvx3mpa8gwyz6acnfg08m0ygj"))))
    (properties `((upstream-name . "carbonr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-sp
                             r-shinydashboard
                             r-shiny
                             r-rlang
                             r-readxl
                             r-magrittr
                             r-lubridate
                             r-htmltools
                             r-ggpp
                             r-ggplot2
                             r-emojifont
                             r-dplyr
                             r-cowplot
                             r-checkmate
                             r-airportr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=carbonr")
    (synopsis "Calculate Carbon-Equivalent Emissions")
    (description
     "This package provides a flexible tool for calculating carbon-equivalent
emissions.  Mostly using data from the UK Government's Greenhouse Gas Conversion
Factors report
<https://www.gov.uk/government/publications/greenhouse-gas-reporting-conversion-factors-2023>,
it facilitates transparent emissions calculations for various sectors, including
travel, accommodation, and clinical activities.  The package is designed for
easy integration into R workflows, with additional support for shiny
applications and community-driven extensions.")
    (license license:lgpl3+)))

(define-public r-carbondate
  (package
    (name "r-carbondate")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "carbondate" version))
       (sha256
        (base32 "03hsss66gxkxp8zpjg6qy6mvjlcy5bchw0idzmwj37ls79g0zczr"))))
    (properties `((upstream-name . "carbondate")))
    (build-system r-build-system)
    (propagated-inputs (list r-cpp11))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/TJHeaton/carbondate")
    (synopsis "Calibration and Summarisation of Radiocarbon Dates")
    (description
     "This package performs Bayesian non-parametric calibration of multiple related
radiocarbon determinations, and summarises the calendar age information to plot
their joint calendar age density (see Heaton (2022) <doi:10.1111/rssc.12599>).
Also models the occurrence of radiocarbon samples as a variable-rate
(inhomogeneous) Poisson process, plotting the posterior estimate for the
occurrence rate of the samples over calendar time, and providing information
about potential change points.")
    (license license:gpl3+)))

(define-public r-carbonate
  (package
    (name "r-carbonate")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "carbonate" version))
       (sha256
        (base32 "01k8c49v8ybgcwdr9ipw319lxw4p14w9bzl54j1ljbajdzgzcgwk"))))
    (properties `((upstream-name . "carbonate")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-wdman
                             r-rtweet
                             r-rselenium
                             r-r6
                             r-magick
                             r-jsonlite
                             r-httr
                             r-httpuv
                             r-details
                             r-clipr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/yonicd/carbonate")
    (synopsis "Interact with 'carbon.js'")
    (description "Create beautiful images of source code using
carbon.js'<https://carbon.now.sh/about>.")
    (license license:expat)))

(define-public r-carbayesst
  (package
    (name "r-carbayesst")
    (version "4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CARBayesST" version))
       (sha256
        (base32 "0wrxpx4zrlndyp74iwrr6bny2l31a333a6nmk3dzi7j3skaj7zf5"))))
    (properties `((upstream-name . "CARBayesST")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncnorm
                             r-truncdist
                             r-spdep
                             r-spam
                             r-sf
                             r-rcpp
                             r-mcmcpack
                             r-matrixstats
                             r-mass
                             r-leaflet
                             r-gtools
                             r-gridextra
                             r-ggplot2
                             r-ggally
                             r-dplyr
                             r-coda
                             r-carbayesdata))
    (home-page "https://github.com/duncanplee/CARBayesST")
    (synopsis
     "Spatio-Temporal Generalised Linear Mixed Models for Areal Unit Data")
    (description
     "This package implements a class of univariate and multivariate spatio-temporal
generalised linear mixed models for areal unit data, with inference in a
Bayesian setting using Markov chain Monte Carlo (MCMC) simulation.  The response
variable can be binomial, Gaussian, or Poisson, but for some models only the
binomial and Poisson data likelihoods are available.  The spatio-temporal
autocorrelation is modelled by random effects, which are assigned conditional
autoregressive (CAR) style prior distributions.  A number of different random
effects structures are available, including models similar to Rushworth et al.
(2014) <doi:10.1016/j.sste.2014.05.001>.  Full details are given in the vignette
accompanying this package.  The creation and development of this package was
supported by the Engineering and Physical Sciences Research Council (EPSRC)
grants EP/J017442/1 and EP/T004878/1 and the Medical Research Council (MRC)
grant MR/L022184/1.")
    (license license:gpl2+)))

(define-public r-carbayesdata
  (package
    (name "r-carbayesdata")
    (version "3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CARBayesdata" version))
       (sha256
        (base32 "03m0r6n10ssljhliipvslwxgcpv0whvlj27d7awa7sp37j3aafx5"))))
    (properties `((upstream-name . "CARBayesdata")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf))
    (home-page "https://cran.r-project.org/package=CARBayesdata")
    (synopsis
     "Data Used in the Vignettes Accompanying the CARBayes and CARBayesST Packages")
    (description
     "Spatio-temporal data from Scotland used in the vignettes accompanying the
CARBayes (spatial modelling) and CAR@code{BayesST} (spatio-temporal modelling)
packages.  Most of the data relate to the set of 271 Intermediate Zones (IZ)
that make up the 2001 definition of the Greater Glasgow and Clyde health board.")
    (license license:gpl2+)))

(define-public r-carbayes
  (package
    (name "r-carbayes")
    (version "6.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CARBayes" version))
       (sha256
        (base32 "10dqplygp74mphf0mwv4c6d6c1lbi3k41djqrv2yglq799lkm7mi"))))
    (properties `((upstream-name . "CARBayes")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncnorm
                             r-spdep
                             r-spam
                             r-sf
                             r-rcpp
                             r-rcolorbrewer
                             r-mcmcpack
                             r-mass
                             r-mapview
                             r-igraph
                             r-glmnet
                             r-ggally
                             r-dplyr
                             r-coda
                             r-carbayesdata))
    (home-page "https://github.com/duncanplee/CARBayes")
    (synopsis "Spatial Generalised Linear Mixed Models for Areal Unit Data")
    (description
     "This package implements a class of univariate and multivariate spatial
generalised linear mixed models for areal unit data, with inference in a
Bayesian setting using Markov chain Monte Carlo (MCMC) simulation using a single
or multiple Markov chains.  The response variable can be binomial, Gaussian,
multinomial, Poisson or zero-inflated Poisson (ZIP), and spatial autocorrelation
is modelled by a set of random effects that are assigned a conditional
autoregressive (CAR) prior distribution.  A number of different models are
available for univariate spatial data, including models with no random effects
as well as random effects modelled by different types of CAR prior, including
the BYM model (Besag et al., 1991, <doi:10.1007/BF00116466>) and Leroux model
(Leroux et al., 2000, <doi:10.1007/978-1-4612-1284-3_4>).  Additionally, a
multivariate CAR (MCAR) model for multivariate spatial data is available, as is
a two-level hierarchical model for modelling data relating to individuals within
areas.  Full details are given in the vignette accompanying this package.  The
initial creation of this package was supported by the Economic and Social
Research Council (ESRC) grant RES-000-22-4256, and on-going development has been
supported by the Engineering and Physical Science Research Council (EPSRC) grant
EP/J017442/1, ESRC grant ES/K006460/1, Innovate UK / Natural Environment
Research Council (NERC) grant NE/N007352/1 and the TB Alliance.")
    (license license:gpl2+)))

(define-public r-carat
  (package
    (name "r-carat")
    (version "2.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "carat" version))
       (sha256
        (base32 "0h7l448b9vxmfdvi3zq3xgzprh0nrwvm1c2bg9d4yfbz92y2ndfc"))))
    (properties `((upstream-name . "carat")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-rcpparmadillo r-rcpp r-gridextra
                             r-ggplot2))
    (home-page "https://cran.r-project.org/package=carat")
    (synopsis "Covariate-Adaptive Randomization for Clinical Trials")
    (description
     "This package provides functions and command-line user interface to generate
allocation sequence by covariate-adaptive randomization for clinical trials.
The package currently supports six covariate-adaptive randomization procedures.
Three hypothesis testing methods that are valid and robust under
covariate-adaptive randomization are also available in the package to facilitate
the inference for treatment effect under the included randomization procedures.
Additionally, the package provides comprehensive and efficient tools to allow
one to evaluate and compare the performance of randomization procedures and
tests based on various criteria.  See Ma W, Ye X, Tu F, and Hu F (2023) <doi:
10.18637/jss.v107.i02> for details.")
    (license license:gpl2+)))

(define-public r-caramel
  (package
    (name "r-caramel")
    (version "1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "caRamel" version))
       (sha256
        (base32 "17g1y634a02819kw19kbvifzpsacifvgw2gifjmw99vf1mijyj9h"))))
    (properties `((upstream-name . "caRamel")))
    (build-system r-build-system)
    (propagated-inputs (list r-geometry))
    (native-inputs (list r-knitr gfortran))
    (home-page "https://github.com/fzao/caRamel")
    (synopsis
     "Automatic Calibration by Evolutionary Multi Objective Algorithm")
    (description
     "The @code{caRamel} optimizer has been developed to meet the requirement for an
automatic calibration procedure that delivers a family of parameter sets that
are optimal with regard to a multi-objective target (Monteil et al.
<doi:10.5194/hess-24-3189-2020>).")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-caracas
  (package
    (name "r-caracas")
    (version "2.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "caracas" version))
       (sha256
        (base32 "0q967hv6hr62sqhqk8vk313g16hg75igwb7idmd8w0zsqaqvac9v"))))
    (properties `((upstream-name . "caracas")))
    (build-system r-build-system)
    (inputs (list python))
    (propagated-inputs (list r-reticulate r-matrix r-magrittr r-doby))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/r-cas/caracas")
    (synopsis "Computer Algebra")
    (description
     "Computer algebra via the @code{SymPy} library (<https://www.sympy.org/>).  This
makes it possible to solve equations symbolically, find symbolic integrals,
symbolic sums and other important quantities.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-captr
  (package
    (name "r-captr")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "captr" version))
       (sha256
        (base32 "13j2nq9hm37g4h5fjdpz7kix0sqajdd7zssjfgil06ixfmnsijkx"))))
    (properties `((upstream-name . "captr")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-curl))
    (native-inputs (list r-knitr))
    (home-page "http://github.com/soodoku/captR")
    (synopsis "Client for the Captricity API")
    (description
     "Get text from images of text using Captricity Optical Character Recognition
(OCR) API. Captricity allows you to get text from handwritten forms --- think
surveys --- and other structured paper documents.  And it can output data in
form a delimited file keeping field information intact.  For more information,
read <https://shreddr.captricity.com/developer/overview/>.")
    (license license:expat)))

(define-public r-capo4sim
  (package
    (name "r-capo4sim")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CaPO4Sim" version))
       (sha256
        (base32 "1dnaskasjzhsvnxqfgww2nwy8ccciilgn1kd7jjj3mx9ksc2wnhr"))))
    (properties `((upstream-name . "CaPO4Sim")))
    (build-system r-build-system)
    (propagated-inputs (list r-visnetwork
                             r-shinywidgets
                             r-shinyjs
                             r-shinyjqui
                             r-shinycssloaders
                             r-shiny
                             r-rintrojs
                             r-purrr
                             r-plotly
                             r-magrittr
                             r-dt))
    (home-page "https://cran.r-project.org/package=CaPO4Sim")
    (synopsis
     "Virtual Patient Simulator in the Context of Calcium and Phosphate Homeostasis")
    (description
     "Explore calcium (Ca) and phosphate (Pi) homeostasis with two novel Shiny apps,
building upon on a previously published mathematical model written in C, to
ensure efficient computations.  The underlying model is accessible here
<https://pubmed.ncbi.nlm.nih.gov/28747359/)>.  The first application explores
the fundamentals of Ca-Pi homeostasis, while the second provides interactive
case studies for in-depth exploration of the topic, thereby seeking to foster
student engagement and an integrative understanding of Ca-Pi regulation.")
    (license license:gpl3)))

(define-public r-capn
  (package
    (name "r-capn")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "capn" version))
       (sha256
        (base32 "14vfk00xyx0az3whmxjpcv1785lf0gx81w7qc54i3wcfp3i22kcr"))))
    (properties `((upstream-name . "capn")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=capn")
    (synopsis "Capital Asset Pricing for Nature")
    (description
     "This package implements approximation methods for natural capital asset prices
suggested by Fenichel and Abbott (2014) <doi:10.1086/676034> in Journal of the
Associations of Environmental and Resource Economists (JAERE), Fenichel et al.
(2016) <doi:10.1073/pnas.1513779113> in Proceedings of the National Academy of
Sciences (PNAS), and Yun et al. (2017) in PNAS (accepted), and their extensions:
creating Chebyshev polynomial nodes and grids, calculating basis of Chebyshev
polynomials, approximation and their simulations for: V-approximation (single
and multiple stocks, PNAS), P-approximation (single stock, PNAS), and
Pdot-approximation (single stock, JAERE).  Development of this package was
generously supported by the Knobloch Family Foundation.")
    (license license:gpl2+)))

(define-public r-capm
  (package
    (name "r-capm")
    (version "0.14.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "capm" version))
       (sha256
        (base32 "0c3rnc1qd9c4v0jj8ihg6bdhpqvfnpafkqyqkar6fwnlvgw48z83"))))
    (properties `((upstream-name . "capm")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-survey
                             r-sf
                             r-magrittr
                             r-ggplot2
                             r-fme
                             r-dplyr
                             r-desolve
                             r-circlize))
    (home-page "http://oswaldosantos.github.io/capm")
    (synopsis "Companion Animal Population Management")
    (description
     "Quantitative analysis to support companion animal population management.  Some
functions assist survey sampling tasks (calculate sample size for simple and
complex designs, select sampling units and estimate population parameters) while
others assist the modelling of population dynamics.  For demographic
characterizations and population management evaluations see: \"Baquero, et al.\"
(2018), <doi:10.1016/j.prevetmed.2018.07.006>.  For modelling of population
dynamics see: \"Baquero et al.\" (2016), <doi:10.1016/j.prevetmed.2015.11.009>.
For sampling methods see: \"Levy PS & Lemeshow S\" (2013), \"ISBN-10: 0470040076\";
\"Lumley\" (2010), \"ISBN: 978-0-470-28430-8\".")
    (license license:gpl2+)))

(define-public r-caplot
  (package
    (name "r-caplot")
    (version "0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "caplot" version))
       (sha256
        (base32 "1dj62x7ibigrmrrnq3hxpc1rfq30zmng4qcki0k6ylil5gr3k0ii"))))
    (properties `((upstream-name . "caplot")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggrepel r-ggplot2 r-ca))
    (home-page "https://cran.r-project.org/package=caplot")
    (synopsis
     "Correspondence Analysis with Geometric Frequency Interpretation")
    (description
     "This package performs Correspondence Analysis on the given dataframe and plots
the results in a scatterplot that emphasizes the geometric interpretation aspect
of the analysis, following Borg-Groenen (2005) and Yelland (2010).  It is
particularly useful for highlighting the relationships between a selected row
(or column) category and the column (or row) categories.  See Borg-Groenen
(2005, ISBN:978-0-387-28981-6); Yelland (2010) <doi:10.3888/tmj.12-4>.")
    (license license:gpl2+)))

(define-public r-capl
  (package
    (name "r-capl")
    (version "1.42")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "capl" version))
       (sha256
        (base32 "0w0w8m4pcclmmk56cad3f2zdfxd5vh312aja8g0c59s9n1hkdw56"))))
    (properties `((upstream-name . "capl")))
    (build-system r-build-system)
    (propagated-inputs (list r-writexl
                             r-stringr
                             r-readxl
                             r-magrittr
                             r-lubridate
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/barnzilla/capl")
    (synopsis "Compute and Visualize CAPL-2 Scores and Interpretations")
    (description
     "This package provides a toolkit for computing and visualizing CAPL-2 (Canadian
Assessment of Physical Literacy, Second Edition; <https://www.capl-eclp.ca>)
scores and interpretations from raw data.")
    (license license:gpl3+)))

(define-public r-capitalr
  (package
    (name "r-capitalr")
    (version "1.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "capitalR" version))
       (sha256
        (base32 "08lvncia9mdrnw84zydf1k7336xawiirh2swziqfwx3z1n172n52"))))
    (properties `((upstream-name . "capitalR")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=capitalR")
    (synopsis
     "Capital Budgeting Analysis, Annuity Loan Calculations and Amortization Schedules")
    (description
     "This package provides Capital Budgeting Analysis functionality and the essential
Annuity loan functions.  Also computes Loan Amortization Schedules including
schedules with irregular payments.")
    (license license:gpl3)))

(define-public r-capesdata
  (package
    (name "r-capesdata")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "capesData" version))
       (sha256
        (base32 "0g1frx57ch0b80dbf08a5yba2zxbizdqb9xpjjdy0l0idkc0vxfm"))))
    (properties `((upstream-name . "capesData")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=capesData")
    (synopsis "Data on Scholarships in CAPES International Mobility Programs")
    (description
     "Information on activities to promote scholarships in Brazil and abroad for
international mobility programs, recorded in Capes computerized payment systems.
 The CAPES database refers to international mobility programs for the period
from 2010 to 2019 <https://dadosabertos.capes.gov.br/dataset/>.")
    (license license:cc0)))

(define-public r-caper
  (package
    (name "r-caper")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "caper" version))
       (sha256
        (base32 "1f1mw54gv1r40wrrsznhgffdj8ggrwihiwdd8wyqccyvqm49fxjg"))))
    (properties `((upstream-name . "caper")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-mass r-ape))
    (home-page "https://cran.r-project.org/package=caper")
    (synopsis "Comparative Analyses of Phylogenetics and Evolution in R")
    (description
     "This package provides functions for performing phylogenetic comparative
analyses.")
    (license license:gpl2+)))

(define-public r-cape
  (package
    (name "r-cape")
    (version "3.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cape" version))
       (sha256
        (base32 "01bxyhn0kk07yx4012px6cys0csqgrsf2n5abdg22vr7ky7phqja"))))
    (properties `((upstream-name . "cape")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-shape
                             r-regress
                             r-rcolorbrewer
                             r-r6
                             r-qtl2convert
                             r-qtl2
                             r-qtl
                             r-propagate
                             r-pracma
                             r-pheatmap
                             r-matrix
                             r-igraph
                             r-here
                             r-foreach
                             r-evd
                             r-doparallel
                             r-corpcor
                             r-catools
                             r-abind))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=cape")
    (synopsis
     "Combined Analysis of Pleiotropy and Epistasis for Diversity Outbred Mice")
    (description
     "Combined Analysis of Pleiotropy and Epistasis infers predictive networks between
genetic variants and phenotypes.  It can be used with standard two-parent
populations as well as multi-parent populations, such as the Diversity Outbred
(DO) mice, Collaborative Cross (CC) mice, or the multi-parent advanced
generation intercross (MAGIC) population of Arabidopsis thaliana.  It uses
complementary information of pleiotropic gene variants across different
phenotypes to resolve models of epistatic interactions between alleles.  To do
this, cape reparametrizes main effect and interaction coefficients from pairwise
variant regressions into directed influence parameters.  These parameters
describe how alleles influence each other, in terms of suppression and
enhancement, as well as how gene variants influence phenotypes.  All of the
final interactions are reported as directed interactions between pairs of
parental alleles.  For detailed descriptions of the methods used in this package
please see the following references.  Carter, G. W., Hays, M., Sherman, A. &
Galitski, T. (2012) <doi:10.1371/journal.pgen.1003010>.  Tyler, A. L., Lu, W.,
Hendrick, J. J., Philip, V. M. & Carter, G. W. (2013)
<doi:10.1371/journal.pcbi.1003270>.")
    (license license:gpl3)))

(define-public r-canvasxpress-data
  (package
    (name "r-canvasxpress-data")
    (version "1.34.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "canvasXpress.data" version))
       (sha256
        (base32 "10fdlb1yp5x9533jdammncfrrlxzpcz9as8i0209pwzjywvxby3s"))))
    (properties `((upstream-name . "canvasXpress.data")))
    (build-system r-build-system)
    (home-page "https://github.com/neuhausi/canvasXpress.data")
    (synopsis "Datasets for the 'canvasXpress' Package")
    (description
     "This package contains the prepared data that is needed for the shiny application
examples in the @code{canvasXpress} package.  This package also includes
datasets used for automated testthat tests.  Scotto L, Narayan G, Nandula SV,
Arias-Pulido H et al. (2008) <doi:10.1002/gcc.20577>.  Davis S, Meltzer PS
(2007) <doi:10.1093/bioinformatics/btm254>.")
    (license license:gpl3)))

(define-public r-canvasxpress
  (package
    (name "r-canvasxpress")
    (version "1.50.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "canvasXpress" version))
       (sha256
        (base32 "04ibr6ksqcn7kngxy65gqx8cc2p1a5acpwg2m800csnn0x7yk05x"))))
    (properties `((upstream-name . "canvasXpress")))
    (build-system r-build-system)
    (arguments
     (list
      #:modules '((guix build r-build-system)
                  (guix build minify-build-system)
                  (guix build utils)
                  (ice-9 match))
      #:imported-modules `(,@%r-build-system-modules (guix build
                                                      minify-build-system))
      #:phases '(modify-phases %standard-phases
                  (add-after 'unpack 'process-javascript
                    (lambda* (#:key inputs #:allow-other-keys)
                      (with-directory-excursion "inst/"
                        (for-each (match-lambda
                                    ((source . target) (minify source
                                                               #:target target)))
                                  '())))))))
    (propagated-inputs (list r-jsonlite r-httr r-htmlwidgets r-htmltools))
    (native-inputs (list r-knitr esbuild))
    (home-page "https://github.com/neuhausi/canvasXpress")
    (synopsis "Visualization Package for CanvasXpress in R")
    (description
     "Enables creation of visualizations using the @code{CanvasXpress} framework in R.
@code{CanvasXpress} is a standalone @code{JavaScript} library for reproducible
research with complete tracking of data and end-user modifications stored in a
single PNG image that can be played back.  See <https://www.canvasxpress.org>
for more information.")
    (license license:gpl3)))

(define-public r-cansim2r
  (package
    (name "r-cansim2r")
    (version "1.14.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CANSIM2R" version))
       (sha256
        (base32 "1dnzbd9lyqj3w80lx12qxcsbmv8wy6hxknyi5ijp99cfv7kaq1kc"))))
    (properties `((upstream-name . "CANSIM2R")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2 r-hmisc r-downloader))
    (home-page "https://cran.r-project.org/package=CANSIM2R")
    (synopsis "Directly Extracts Complete CANSIM Data Tables")
    (description
     "Extract CANSIM (Statistics Canada) tables and transform them into readily usable
data in panel (wide) format.  It can also extract more than one table at a time
and produce the resulting merge by time period and geographical region.")
    (license license:gpl3)))

(define-public r-cansim
  (package
    (name "r-cansim")
    (version "0.3.16")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cansim" version))
       (sha256
        (base32 "144p7zc44xb0szslsrxg1q1lhn5rizlgc0rvsinwzglnkzl478p2"))))
    (properties `((upstream-name . "cansim")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-tibble
                             r-stringr
                             r-rvest
                             r-rsqlite
                             r-rlang
                             r-readr
                             r-purrr
                             r-jsonlite
                             r-httr
                             r-dplyr
                             r-digest
                             r-dbi))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mountainMath/cansim")
    (synopsis "Accessing Statistics Canada Data Table and Vectors")
    (description
     "Searches for, accesses, and retrieves new-format and old-format Statistics
Canada data tables, as well as individual vectors, as tidy data frames.  This
package deals with encoding issues, allows for bilingual English or French
language data retrieval, and bundles convenience functions to make it easier to
work with retrieved table data.  Optional caching features are provided.")
    (license license:expat)))

(define-public r-canprot
  (package
    (name "r-canprot")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "canprot" version))
       (sha256
        (base32 "0b1jfrqdcn90r9ninc5l809vr586r1arbrf9w8dvrfh97gscb5dn"))))
    (properties `((upstream-name . "canprot")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi r-multcompview))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jedick/canprot")
    (synopsis "Chemical Analysis of Proteins")
    (description
     "Chemical analysis of proteins based on their amino acid compositions.  Amino
acid compositions can be read from FASTA files and used to calculate chemical
metrics including carbon oxidation state and stoichiometric hydration state, as
described in Dick et al. (2020) <doi:10.5194/bg-17-6145-2020>.  Other properties
that can be calculated include protein length, grand average of hydropathy
(GRAVY), isoelectric point (@code{pI}), molecular weight (MW), standard molal
volume (V0), and metabolic costs (Akashi and Gojobori, 2002
<doi:10.1073/pnas.062526999>; Wagner, 2005 <doi:10.1093/molbev/msi126>; Zhang et
al., 2018 <doi:10.1038/s41467-018-06461-1>).  A database of amino acid
compositions of human proteins derived from @code{UniProt} is provided.")
    (license license:gpl3)))

(define-public r-canopy
  (package
    (name "r-canopy")
    (version "1.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Canopy" version))
       (sha256
        (base32 "0979hpphzhf4v71jx0shh3l8nffmpsn9l6f8ip2wxzcyx571i1wd"))))
    (properties `((upstream-name . "Canopy")))
    (build-system r-build-system)
    (propagated-inputs (list r-scatterplot3d r-pheatmap r-fields r-ape))
    (home-page "https://github.com/yuchaojiang/Canopy")
    (synopsis
     "Accessing Intra-Tumor Heterogeneity and Tracking Longitudinal and Spatial Clonal Evolutionary History by Next-Generation Sequencing")
    (description
     "This package provides a statistical framework and computational procedure for
identifying the sub-populations within a tumor, determining the mutation
profiles of each subpopulation, and inferring the tumor's phylogenetic history.
The input are variant allele frequencies (VAFs) of somatic single nucleotide
alterations (SNAs) along with allele-specific coverage ratios between the tumor
and matched normal sample for somatic copy number alterations (CNAs).  These
quantities can be directly taken from the output of existing software.  Canopy
provides a general mathematical framework for pooling data across samples and
sites to infer the underlying parameters.  For SNAs that fall within CNA
regions, Canopy infers their temporal ordering and resolves their phase.  When
there are multiple evolutionary configurations consistent with the data, Canopy
outputs all configurations along with their confidence assessment.")
    (license license:gpl2)))

(define-public r-canek
  (package
    (name "r-canek")
    (version "0.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Canek" version))
       (sha256
        (base32 "1irzdhqgzn6kz79f80ri1iv8zlg8ik95bqcllj14ycma1c1mwzsy"))))
    (properties `((upstream-name . "Canek")))
    (build-system r-build-system)
    (propagated-inputs (list r-numbers
                             r-matrixstats
                             r-irlba
                             r-igraph
                             r-fpc
                             r-fnn
                             r-bluster))
    (native-inputs (list r-knitr))
    (home-page "https://martinloza.github.io/Canek/")
    (synopsis "Batch Correction of Single Cell Transcriptome Data")
    (description
     "Non-linear/linear hybrid method for batch-effect correction that uses Mutual
Nearest Neighbors (MNNs) to identify similar cells between datasets.  Reference:
Loza M. et al. (NAR Genomics and Bioinformatics, 2020)
<doi:10.1093/nargab/lqac022>.")
    (license license:expat)))

(define-public r-candisc
  (package
    (name "r-candisc")
    (version "0.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "candisc" version))
       (sha256
        (base32 "0wl5hmx0hb0d1rk9as989nfpvdj64s4kjxd6852qvh9i54dab254"))))
    (properties `((upstream-name . "candisc")))
    (build-system r-build-system)
    (propagated-inputs (list r-heplots r-car))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/friendly/candisc/")
    (synopsis
     "Visualizing Generalized Canonical Discriminant and Canonical Correlation Analysis")
    (description
     "This package provides functions for computing and visualizing generalized
canonical discriminant analyses and canonical correlation analysis for a
multivariate linear model.  Traditional canonical discriminant analysis is
restricted to a one-way MANOVA design and is equivalent to canonical correlation
analysis between a set of quantitative response variables and a set of dummy
variables coded from the factor variable.  The candisc package generalizes this
to higher-way MANOVA designs for all factors in a multivariate linear model,
computing canonical scores and vectors for each term.  The graphic functions
provide low-rank (1D, 2D, 3D) visualizations of terms in an mlm via the
plot.candisc and heplot.candisc methods.  Related plots are now provided for
canonical correlation analysis when all predictors are quantitative.")
    (license license:gpl2+)))

(define-public r-cancerscreening
  (package
    (name "r-cancerscreening")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cancerscreening" version))
       (sha256
        (base32 "1lrdbf2bz6arh9s7x9k10vs986yxrhv23fahrwnl38172ggwv3f9"))))
    (properties `((upstream-name . "cancerscreening")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr
                             r-tidyr
                             r-stringr
                             r-rlang
                             r-magrittr
                             r-lubridate
                             r-khisr
                             r-dplyr
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://cancerscreening.damurka.com")
    (synopsis "Streamline Access to Cancer Screening Data")
    (description
     "Retrieve cancer screening data for cervical, breast and colorectal cancers from
the Kenya Health Information System <https://hiskenya.org> in a consistent way.")
    (license license:expat)))

(define-public r-cancerr
  (package
    (name "r-cancerr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cancerR" version))
       (sha256
        (base32 "02k4d7z565xlmwv5kl7dqqdm27zvmwm2pyfqpp7czdji17agkji0"))))
    (properties `((upstream-name . "cancerR")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/giancarlodigi/cancerR")
    (synopsis "Classification of Cancer Using Administrative Data")
    (description
     "Classifies the type of cancer using routinely collected data commonly found in
cancer registries from pathology reports.  The package implements the
International Classification of Diseases for Oncology, 3rd Edition site
(topography), histology (morphology), and behaviour codes of neoplasms to
classify cancer type
<https://www.who.int/standards/classifications/other-classifications/international-classification-of-diseases-for-oncology>.
 Classification in children utilize the International Classification of
Childhood Cancer by Steliarova-Foucher et al. (2005) <doi:10.1002/cncr.20910>.
Adolescent and young adult cancer classification is based on Barr et al. (2020)
<doi:10.1002/cncr.33041>.")
    (license license:gpl2+)))

(define-public r-cancergram
  (package
    (name "r-cancergram")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CancerGram" version))
       (sha256
        (base32 "1p612dbn6dxn3nz8m0pzlsbczg3f8gwqk9q0fnxbcdlbll0vf2k0"))))
    (properties `((upstream-name . "CancerGram")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi
                             r-shiny
                             r-ranger
                             r-pbapply
                             r-dplyr
                             r-devtools
                             r-biogram))
    (home-page "https://github.com/BioGenies/CancerGram")
    (synopsis "Prediction of Anticancer Peptides")
    (description
     "Predicts anticancer peptides using random forests trained on the n-gram encoded
peptides.  The implemented algorithm can be accessed from both the command line
and shiny-based GUI. The @code{CancerGram} model is too large for CRAN and it
has to be downloaded separately from the repository:
<https://github.com/@code{BioGenies/CancerGramModel>}.  For more information
see: Burdukiewicz et al. (2020) <doi:10.3390/pharmaceutics12111045>.")
    (license license:gpl3)))

(define-public r-cancergi
  (package
    (name "r-cancergi")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cancerGI" version))
       (sha256
        (base32 "1cbpxw6l09sdnf6nyw0hvhrc97awnidi72a2jsjf3v8ml012xd5f"))))
    (properties `((upstream-name . "cancerGI")))
    (build-system r-build-system)
    (propagated-inputs (list r-systemfit r-survival r-reshape2 r-qvalue
                             r-igraph))
    (home-page "https://cran.r-project.org/package=cancerGI")
    (synopsis "Analyses of Cancer Gene Interaction")
    (description
     "This package provides functions to perform the following analyses: i) inferring
epistasis from RNAi double knockdown data; ii) identifying gene pairs of
multiple mutation patterns; iii) assessing association between gene pairs and
survival; and iv) calculating the smallworldness of a graph (e.g., a gene
interaction network).  Data and analyses are described in Wang, X., Fu, A. Q.,
@code{McNerney}, M. and White, K. P. (2014).  Widespread genetic epistasis among
breast cancer genes.  Nature Communications.  5 4828. <doi:10.1038/ncomms5828>.")
    (license license:gpl2+)))

(define-public r-cancerevolutionvisualization
  (package
    (name "r-cancerevolutionvisualization")
    (version "2.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CancerEvolutionVisualization" version))
       (sha256
        (base32 "1iizcr43wrmz099341knzn5jd1h1s0nh0hw64g1r18k6d39swcwd"))))
    (properties `((upstream-name . "CancerEvolutionVisualization")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-plyr r-gtable r-gridextra
                             r-boutroslab-plotting-general))
    (native-inputs (list r-knitr))
    (home-page
     "https://github.com/uclahs-cds/package-CancerEvolutionVisualization")
    (synopsis "Publication Quality Phylogenetic Tree Plots")
    (description
     "Generates tree plots with precise branch lengths, gene annotations, and cellular
prevalence.  The package handles complex tree structures (angles, lengths, etc.)
and can be further refined as needed by the user.")
    (license license:gpl2)))

(define-public r-cancensus
  (package
    (name "r-cancensus")
    (version "0.5.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cancensus" version))
       (sha256
        (base32 "02392bbyzdn2nacjsc3rjv6f3y0mczacpa96azrm300l1j6zsszr"))))
    (properties `((upstream-name . "cancensus")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-jsonlite r-httr r-dplyr r-digest))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mountainMath/cancensus")
    (synopsis
     "Access, Retrieve, and Work with Canadian Census Data and Geography")
    (description
     "Integrated, convenient, and uniform access to Canadian Census data and geography
retrieved using the @code{CensusMapper} API. This package produces
analysis-ready tidy data frames and spatial data in multiple formats, as well as
convenience functions for working with Census variables, variable hierarchies,
and region selection.  API keys are freely available with free registration at
<https://censusmapper.ca/api>.  Census data and boundary geometries are
reproduced and distributed on an \"as is\" basis with the permission of Statistics
Canada (Statistics Canada 2001; 2006; 2011; 2016; 2021).")
    (license license:expat)))

(define-public r-canaper
  (package
    (name "r-canaper")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "canaper" version))
       (sha256
        (base32 "12is3x3srmdf39csf8q09n2377h9my2qwy0knwc3kfjdg6f9yzs7"))))
    (properties `((upstream-name . "canaper")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-tibble
                             r-purrr
                             r-progressr
                             r-phyloregion
                             r-future-apply
                             r-dplyr
                             r-assertthat
                             r-assertr
                             r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ropensci/canaper")
    (synopsis "Categorical Analysis of Neo- And Paleo-Endemism")
    (description
     "This package provides functions to analyze the spatial distribution of
biodiversity, in particular categorical analysis of neo- and paleo-endemism
(CANAPE) as described in Mishler et al (2014) <doi:10.1038/ncomms5473>.  canaper
conducts statistical tests to determine the types of endemism that occur in a
study area while accounting for the evolutionary relationships of species.")
    (license license:expat)))

(define-public r-canadianmaps
  (package
    (name "r-canadianmaps")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "canadianmaps" version))
       (sha256
        (base32 "08kf6jxvqh6kyfb639kdqpq33qlrpaz94ayknbj13hm4asgsn3w5"))))
    (properties `((upstream-name . "canadianmaps")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp
                             r-sf
                             r-rcolorbrewer
                             r-ggrepel
                             r-ggplot2
                             r-dplyr))
    (home-page "https://github.com/joellecayen/canadianmaps")
    (synopsis "Effortlessly Create Stunning Canadian Maps")
    (description
     "Simple and seamless access to a variety of @code{StatCan} shapefiles for mapping
Canadian provinces, regions, forward sortation areas, census divisions, and
subdivisions using the popular ggplot2 package.")
    (license license:expat)))

(define-public r-canadamaps
  (package
    (name "r-canadamaps")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "canadamaps" version))
       (sha256
        (base32 "1i3yjhr5p06k6id3gws5dzdhf4jy143brbfhi2z4srq67xlz5agl"))))
    (properties `((upstream-name . "canadamaps")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf r-rmapshaper r-rlang r-magrittr r-dplyr))
    (home-page "https://github.com/pachadotdev/canadamaps/")
    (synopsis "Maps of the Political and Administrative Divisions of Canada")
    (description
     "Terrestrial maps with simplified topologies for Census Divisions, Agricultural
Regions, Economic Regions, Federal Electoral Divisions and Provinces.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-camtrapr
  (package
    (name "r-camtrapr")
    (version "2.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "camtrapR" version))
       (sha256
        (base32 "02y4y19v2kgc0mazpk4dxfivln7bylgqqwllz2rw7x0wgjab3l3y"))))
    (properties `((upstream-name . "camtrapR")))
    (build-system r-build-system)
    (inputs (list perl-image-exiftool))
    (propagated-inputs (list r-sf
                             r-secr
                             r-lubridate
                             r-ggplot2
                             r-generics
                             r-data-table))
    (native-inputs (list r-r-rsp))
    (home-page "https://github.com/jniedballa/camtrapR")
    (synopsis
     "Camera Trap Data Management and Preparation of Occupancy and Spatial Capture-Recapture Analyses")
    (description
     "Management of and data extraction from camera trap data in wildlife studies.
The package provides a workflow for storing and sorting camera trap photos (and
videos), tabulates records of species and individuals, and creates
detection/non-detection matrices for occupancy and spatial capture-recapture
analyses with great flexibility.  In addition, it can visualise species activity
data and provides simple mapping functions with GIS export.")
    (license license:gpl2+)))

(define-public r-camtrapdp
  (package
    (name "r-camtrapdp")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "camtrapdp" version))
       (sha256
        (base32 "0aspfqjiv5xq8p7rchg4aqsnl0s7692pgq1bvgiq3i0vhlwizcd5"))))
    (properties `((upstream-name . "camtrapdp")))
    (build-system r-build-system)
    (propagated-inputs (list r-readr
                             r-purrr
                             r-memoise
                             r-frictionless
                             r-dplyr
                             r-cli))
    (home-page "https://github.com/inbo/camtrapdp")
    (synopsis "Read and Manipulate Camera Trap Data Packages")
    (description
     "Read and manipulate Camera Trap Data Packages ('Camtrap DP').  Camtrap DP
(<https://camtrap-dp.tdwg.org>) is a data exchange format for camera trap data.
With camtrapdp you can read, filter and transform data (including to Darwin
Core) before further analysis in e.g. camtraptor or @code{camtrapR}'.")
    (license license:expat)))

(define-public r-camsrad
  (package
    (name "r-camsrad")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "camsRad" version))
       (sha256
        (base32 "06gar6qan1ka01ngjvbpcv649yvfga697mplwn1x6qnfr4ngb7cs"))))
    (properties `((upstream-name . "camsRad")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2 r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ropenscilabs/camsRad")
    (synopsis "Client for CAMS Radiation Service")
    (description
     "Copernicus Atmosphere Monitoring Service (CAMS) radiations service provides time
series of global, direct, and diffuse irradiations on horizontal surface, and
direct irradiation on normal plane for the actual weather conditions as well as
for clear-sky conditions.  The geographical coverage is the field-of-view of the
Meteosat satellite, roughly speaking Europe, Africa, Atlantic Ocean, Middle
East.  The time coverage of data is from 2004-02-01 up to 2 days ago.  Data are
available with a time step ranging from 15 min to 1 month.  For license terms
and to create an account, please see
<http://www.soda-pro.com/web-services/radiation/cams-radiation-service>.")
    (license license:expat)))

(define-public r-campsismod
  (package
    (name "r-campsismod")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "campsismod" version))
       (sha256
        (base32 "0d3bdfx4jcnpzbnz6ymgz10s4137van6bcg5s4a3yzf90f02lbns"))))
    (properties `((upstream-name . "campsismod")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-readr
                             r-purrr
                             r-plyr
                             r-magrittr
                             r-dplyr
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Calvagone/campsismod")
    (synopsis "Generic Implementation of a PK/PD Model")
    (description
     "This package provides a generic, easy-to-use and expandable implementation of a
pharmacokinetic (PK) / pharmacodynamic (PD) model based on the S4 class system.
This package allows the user to read/write a pharmacometric model from/to files
and adapt it further on the fly in the R environment.  For this purpose, this
package provides an intuitive API to add, modify or delete equations, ordinary
differential equations (ODE's), model parameters or compartment properties (like
infusion duration or rate, bioavailability and initial values).  Finally, this
package also provides a useful export of the model for use with simulation
packages rxode2 and mrgsolve'.  This package is designed and intended to be used
with package campsis', a PK/PD simulation platform built on top of rxode2 and
mrgsolve'.")
    (license license:gpl3+)))

(define-public r-campsis
  (package
    (name "r-campsis")
    (version "1.5.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "campsis" version))
       (sha256
        (base32 "05ls3vgaplfjqs91gpzpwy5nhv7falxr14p1vz1waaqlj1qphyq9"))))
    (properties `((upstream-name . "campsis")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-rlang
                             r-purrr
                             r-progressr
                             r-plyr
                             r-mass
                             r-ggplot2
                             r-future
                             r-furrr
                             r-dplyr
                             r-digest
                             r-campsismod
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Calvagone/campsis")
    (synopsis "Generic PK/PD Simulation Platform CAMPSIS")
    (description
     "This package provides a generic, easy-to-use and intuitive
pharmacokinetic/pharmacodynamic (PK/PD) simulation platform based on R packages
rxode2 and mrgsolve'.  CAMPSIS provides an abstraction layer over the underlying
processes of writing a PK/PD model, assembling a custom dataset and running a
simulation.  CAMPSIS has a strong dependency to the R package campsismod', which
allows to read/write a model from/to files and adapt it further on the fly in
the R environment.  Package campsis allows the user to assemble a dataset in an
intuitive manner.  Once the userâs dataset is ready, the package is in charge
of preparing the simulation, calling rxode2 or mrgsolve (at the user's choice)
and returning the results, for the given model, dataset and desired simulation
settings.")
    (license license:gpl3+)))

(define-public r-campfin
  (package
    (name "r-campfin")
    (version "1.0.11")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "campfin" version))
       (sha256
        (base32 "10mry0zn9h6dx79vqxpifn5bnxc9h500x7m3yh1vx4jshbvmgvnk"))))
    (properties `((upstream-name . "campfin")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-stringdist
                             r-scales
                             r-rlang
                             r-readr
                             r-purrr
                             r-magrittr
                             r-lubridate
                             r-httr
                             r-glue
                             r-ggplot2
                             r-fs
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/irworkshop/campfin")
    (synopsis "Wrangle Campaign Finance Data")
    (description
     "Explore and normalize American campaign finance data.  Created by the
Investigative Reporting Workshop to facilitate work on The Accountability
Project, an effort to collect public data into a central, standard database that
is more easily searched: <https://publicaccountability.org/>.")
    (license (license:fsdg-compatible "CC BY 4.0"))))

(define-public r-campaignmanager
  (package
    (name "r-campaignmanager")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "campaignmanageR" version))
       (sha256
        (base32 "1x240l0jlyg4ldb4j9pa2v2nryxnyg8y14ywcdcpfnw4056ms3f5"))))
    (properties `((upstream-name . "campaignmanageR")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite))
    (native-inputs (list r-knitr))
    (home-page "https://windsor.ai/")
    (synopsis "Connect to Campaign Manager via the 'Windsor.ai' API")
    (description
     "Collect marketing data from Campaign Manager using the Windsor.ai API
<https://windsor.ai/api-fields/>.")
    (license license:gpl3)))

(define-public r-camml
  (package
    (name "r-camml")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CAMML" version))
       (sha256
        (base32 "0h2wfbafgcci1rrdq6qc634nf0d1h47ccajziifg1fhk7m8s56i7"))))
    (properties `((upstream-name . "CAMML")))
    (build-system r-build-system)
    (propagated-inputs (list r-vam
                             r-seuratobject
                             r-seurat
                             r-org-mm-eg-db
                             r-org-hs-eg-db
                             r-org-dr-eg-db
                             r-matrix
                             r-mass
                             r-edger
                             r-biocmanager
                             r-annotationdbi))
    (home-page "https://cran.r-project.org/package=CAMML")
    (synopsis
     "Cell-Typing using Variance Adjusted Mahalanobis Distances with Multi-Labeling")
    (description
     "This package creates multi-label cell-types for single-cell RNA-sequencing data
based on weighted VAM scoring of cell-type specific gene sets.  Schiebout, Frost
(2022) <https://psb.stanford.edu/psb-online/proceedings/psb22/schiebout.pdf>.")
    (license license:gpl2+)))

(define-public r-camerondata
  (package
    (name "r-camerondata")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "camerondata" version))
       (sha256
        (base32 "0nj9dxwklhqyqrqfq88vpi4mdd6gvd3mzi80h8fi7hjzv5pmgqad"))))
    (properties `((upstream-name . "camerondata")))
    (build-system r-build-system)
    (home-page "https://github.com/juvlac/camerondata")
    (synopsis
     "Datasets from \"Microeconometrics: Methods and Applications\" by Cameron and Trivedi")
    (description
     "Quick and easy access to datasets that let you replicate the empirical examples
in Cameron and Trivedi (2005) \"Microeconometrics: Methods and Applications\"
(ISBN: 9780521848053).The data are available as soon as you install and load the
package (lazy-loading) as data frames.  The documentation includes reference to
chapter sections and page numbers where the datasets are used.")
    (license (license:fsdg-compatible "CC BY 4.0"))))

(define-public r-camelup
  (package
    (name "r-camelup")
    (version "2.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CamelUp" version))
       (sha256
        (base32 "1d3ywb4bxnn149api6lqry8q9lasng79hzka9ndr5cv38pkbvva9"))))
    (properties `((upstream-name . "CamelUp")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny
                             r-rcpp
                             r-magrittr
                             r-ggplot2
                             r-dplyr
                             r-data-table))
    (home-page "https://cran.r-project.org/package=CamelUp")
    (synopsis
     "'CamelUp' Board Game as a Teaching Aid for Introductory Statistics")
    (description
     "This package implements the board game @code{CamelUp} for use in introductory
statistics classes using a Shiny app.")
    (license license:gpl3)))

(define-public r-camcorder
  (package
    (name "r-camcorder")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "camcorder" version))
       (sha256
        (base32 "10w93897708rcbab4l8942h3grlsw822mqkj7hcp1p8fakgnrxkd"))))
    (properties `((upstream-name . "camcorder")))
    (build-system r-build-system)
    (propagated-inputs (list r-svglite
                             r-rsvg
                             r-rlang
                             r-magick
                             r-jsonlite
                             r-gifski
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=camcorder")
    (synopsis "Record Your Plot History")
    (description
     "Record and generate a gif of your R sessions plots.  When creating a
visualization, there is inevitably iteration and refinement that occurs.
Automatically save the plots made to a specified directory, previewing them as
they would be saved.  Then combine all plots generated into a gif to show the
plot refinement over time.")
    (license license:expat)))

(define-public r-calsim
  (package
    (name "r-calsim")
    (version "0.5.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CalSim" version))
       (sha256
        (base32 "1ij3xaizq1lpq5vg25i8pz4khm7ab81kzfayp6a914n0jgxvprj7"))))
    (properties `((upstream-name . "CalSim")))
    (build-system r-build-system)
    (propagated-inputs (list r-spatstat-geom r-spatstat r-exactmultinom))
    (home-page "https://cran.r-project.org/package=CalSim")
    (synopsis "The Calibration Simplex")
    (description
     "Generates the calibration simplex (a generalization of the reliability diagram)
for three-category probability forecasts, as proposed by Wilks (2013)
<doi:10.1175/WAF-D-13-00027.1>.")
    (license license:gpl2)))

(define-public r-calpassapi
  (package
    (name "r-calpassapi")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "calpassapi" version))
       (sha256
        (base32 "1vhx5h7ah75cs1mlw25x7hal90m47596kr7fx2pd8fslq7il7p1b"))))
    (properties `((upstream-name . "calpassapi")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-jsonlite r-httr r-dplyr r-digest))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/vinhdizzo/calpassapi")
    (synopsis "R Interface to Access CalPASS API")
    (description
     "This package implements methods for querying data from @code{CalPASS} using its
API. @code{CalPASS} Plus.  MMAP API V1.
<https://mmap.calpassplus.org/docs/index.html>.")
    (license license:gpl3)))

(define-public r-calmr
  (package
    (name "r-calmr")
    (version "0.6.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "calmr" version))
       (sha256
        (base32 "11hb2d9a5vzda94qb3pg440vgch2pfn8jhkw71hj6xzw8aqylhs3"))))
    (properties `((upstream-name . "calmr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-progressr
                             r-patchwork
                             r-network
                             r-ggplot2
                             r-ggnetwork
                             r-ga
                             r-future-apply
                             r-future
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/victor-navarro/calmr")
    (synopsis
     "Canonical Associative Learning Models and their Representations")
    (description
     "Implementations of canonical associative learning models, with tools to run
experiment simulations, estimate model parameters, and compare model
representations.  Experiments and results are represented using S4 classes and
methods.")
    (license license:gpl3+)))

(define-public r-calmate
  (package
    (name "r-calmate")
    (version "0.13.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "calmate" version))
       (sha256
        (base32 "17gfk3am8frj9pqx31pmjswm5nvca9nqbanl0qj4ypsr8wymix7w"))))
    (properties `((upstream-name . "calmate")))
    (build-system r-build-system)
    (propagated-inputs (list r-r-utils
                             r-r-oo
                             r-r-methodss3
                             r-r-filesets
                             r-matrixstats
                             r-mass
                             r-aroma-core))
    (home-page "https://github.com/HenrikBengtsson/calmate/")
    (synopsis
     "Improved Allele-Specific Copy Number of SNP Microarrays for Downstream Segmentation")
    (description
     "The @code{CalMaTe} method calibrates preprocessed allele-specific copy number
estimates (ASCNs) from DNA microarrays by controlling for single-nucleotide
polymorphism-specific allelic crosstalk.  The resulting ASCNs are on average
more accurate, which increases the power of segmentation methods for detecting
changes between copy number states in tumor studies including copy neutral loss
of heterozygosity. @code{CalMaTe} applies to any ASCNs regardless of
preprocessing method and microarray technology, e.g. Affymetrix and Illumina.")
    (license license:lgpl2.1+)))

(define-public r-callsync
  (package
    (name "r-callsync")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "callsync" version))
       (sha256
        (base32 "03ks7wspkvr6fy54ggxj1rzxsdqraq1dlv384v0b4b7x4z7kj73l"))))
    (properties `((upstream-name . "callsync")))
    (build-system r-build-system)
    (propagated-inputs (list r-tuner
                             r-stringr
                             r-signal
                             r-seewave
                             r-scales
                             r-oce
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/simeonqs/callsync")
    (synopsis
     "Recording Synchronisation, Call Detection and Assignment, Audio Analysis")
    (description
     "Intended to analyse recordings from multiple microphones (e.g., backpack
microphones in captive setting).  It allows users to align recordings even if
there is non-linear drift of several minutes between them.  A call detection and
assignment pipeline can be used to find vocalisations and assign them to the
vocalising individuals (even if the vocalisation is picked up on multiple
microphones).  The tracing and measurement functions allow for detailed analysis
of the vocalisations and filtering of noise.  Finally, the package includes a
function to run spectrographic cross correlation, which can be used to compare
vocalisations.  It also includes multiple other functions related to analysis of
vocal behaviour.")
    (license license:gpl3)))

(define-public r-callme
  (package
    (name "r-callme")
    (version "0.1.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "callme" version))
       (sha256
        (base32 "1agyflf9ch5xyxmfdcv6shxz8h7ibp6rd3d6x1g7gk1cblvshlar"))))
    (properties `((upstream-name . "callme")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/coolbutuseless/callme")
    (synopsis "Easily Compile and Call Inline C Functions")
    (description
     "Compile inline C code and easily call with automatically generated wrapper
functions.  By allowing user-defined headers and compilation flags
(preprocessor, compiler and linking flags) the user can configure optimization
options and linking to third party libraries.  Multiple functions may be defined
in a single block of code - which may be defined in a string or a path to a
source file.")
    (license license:expat)))

(define-public r-callback
  (package
    (name "r-callback")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "callback" version))
       (sha256
        (base32 "04j00c8i14i3ic3ccdglj8fyaa9924dsgmichidk8jh2qj7c22ny"))))
    (properties `((upstream-name . "callback")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=callback")
    (synopsis "Computes Statistics from Discrimination Experimental Data")
    (description
     "In discrimination experiments candidates are sent on the same test (e.g. job,
house rental) and one examines whether they receive the same outcome.  The
number of non negative answers are first examined in details looking for outcome
differences.  Then various answering rates and their exacts confidence intervals
are computed.  Last, exact and asymptotic discrimination tests are performed.
Graphical methods are also available.")
    (license license:gpl3)))

(define-public r-calidad
  (package
    (name "r-calidad")
    (version "0.6.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "calidad" version))
       (sha256
        (base32 "1i69m14xzls4wgvq4ids6f61mwkygz92h72sxhc0cwwiha6231ry"))))
    (properties `((upstream-name . "calidad")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-survey
                             r-stringr
                             r-rlang
                             r-purrr
                             r-kableextra
                             r-haven
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=calidad")
    (synopsis
     "Assesses the Quality of Estimates Made by Complex Sample Designs")
    (description
     "Assesses the quality of estimates made by complex sample designs, following the
methodology developed by the National Institute of Statistics Chile (2020,
<https://www.ine.cl/docs/default-source/institucionalidad/buenas-pr%C3%A1cticas/clasificaciones-y-estandares/est%C3%A1ndar-evaluaci%C3%B3n-de-calidad-de-estimaciones-publicaci%C3%B3n-27022020.pdf>)
and by Economic Commission for Latin America and Caribbean (2024,
chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://repositorio.cepal.org/server/api/core/bitstreams/f04569e6-4f38-42e7-a32b-e0b298e0ab9c/content).")
    (license license:gpl3)))

(define-public r-calibratr
  (package
    (name "r-calibratr")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CalibratR" version))
       (sha256
        (base32 "1hnmhijckxd35h8mhpzqpglk1ykdih2c5kg17myc7cci5xjk9nfr"))))
    (properties `((upstream-name . "CalibratR")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2
                             r-proc
                             r-ggplot2
                             r-foreach
                             r-fitdistrplus
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=CalibratR")
    (synopsis "Mapping ML Scores to Calibrated Predictions")
    (description
     "Transforms your uncalibrated Machine Learning scores to well-calibrated
prediction estimates that can be interpreted as probability estimates.  The
implemented BBQ (Bayes Binning in Quantiles) model is taken from Naeini (2015,
ISBN:0-262-51129-0).  Please cite this paper: Schwarz J and Heider D,
Bioinformatics 2019, 35(14):2458-2465.")
    (license license:lgpl3)))

(define-public r-calibrator
  (package
    (name "r-calibrator")
    (version "1.2-8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "calibrator" version))
       (sha256
        (base32 "1m9g1pmnr6d9jkg5ab0l0cbqfj7kmx7sdmcdqdhn9ifyhhn7812y"))))
    (properties `((upstream-name . "calibrator")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-emulator r-cubature))
    (home-page "https://github.com/RobinHankin/calibrator.git")
    (synopsis "Bayesian Calibration of Complex Computer Codes")
    (description
     "This package performs Bayesian calibration of computer models as per Kennedy and
O'Hagan 2001.  The package includes routines to find the hyperparameters and
parameters; see the help page for stage1() for a worked example using the toy
dataset.  A tutorial is provided in the calex.Rnw vignette; and a suite of
especially simple one dimensional examples appears in inst/doc/one.dim/.")
    (license license:gpl2)))

(define-public r-calibrationcurves
  (package
    (name "r-calibrationcurves")
    (version "2.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CalibrationCurves" version))
       (sha256
        (base32 "102kpgjfasyyrfpxrv1mzrl40fhh6blml6lbiha4s6p0fav7dj8n"))))
    (properties `((upstream-name . "CalibrationCurves")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-rstudioapi
                             r-rms
                             r-hmisc
                             r-ggplot2
                             r-bookdown))
    (native-inputs (list r-knitr))
    (home-page "https://bavodc.github.io/websiteCalibrationCurves/")
    (synopsis "Calibration Performance")
    (description
     "Plots calibration curves and computes statistics for assessing calibration
performance.  See De Cock Campo (2023) <doi:10.48550/@code{arXiv.2309.08559>}
and Van Calster et al. (2016) <doi:10.1016/j.jclinepi.2015.12.005>.")
    (license license:gpl3+)))

(define-public r-calibrationband
  (package
    (name "r-calibrationband")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "calibrationband" version))
       (sha256
        (base32 "1m3dp7h9dy1ipji3vinknqyhbw1gbv48473rbhpykps8hzrqg206"))))
    (properties `((upstream-name . "calibrationband")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-sp
                             r-rlang
                             r-rcpp
                             r-magrittr
                             r-ggplot2
                             r-dplyr))
    (home-page "https://github.com/marius-cp/calibrationband")
    (synopsis "Calibration Bands")
    (description
     "Package to assess the calibration of probabilistic classifiers using confidence
bands for monotonic functions.  Besides testing the classical goodness-of-fit
null hypothesis of perfect calibration, the confidence bands calculated within
that package facilitate inverted goodness-of-fit tests whose rejection allows
for a sought-after conclusion of a sufficiently well-calibrated model.  The
package creates flexible graphical tools to perform these tests.  For
construction details see also Dimitriadis, DÃ¼mbgen, Henzi, Puke, Ziegel (2022)
<@code{arXiv:2203.04065>}.")
    (license license:gpl3)))

(define-public r-calibratessb
  (package
    (name "r-calibratessb")
    (version "1.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CalibrateSSB" version))
       (sha256
        (base32 "0qwqvyrpprxc5v0ng6qjp9gmdf0n0iiv46z14d8h303xpi84g42x"))))
    (properties `((upstream-name . "CalibrateSSB")))
    (build-system r-build-system)
    (propagated-inputs (list r-survey))
    (home-page "https://github.com/statisticsnorway/CalibrateSSB")
    (synopsis "Weighting and Estimation for Panel Data with Non-Response")
    (description
     "This package provides functions to calculate weights, estimates of changes and
corresponding variance estimates for panel data with non-response.  Partially
overlapping samples are handled.  Initially, weights are calculated by linear
calibration.  By default, the survey package is used for this purpose.  It is
also possible to use @code{ReGenesees}, which can be installed from
<https://github.com/@code{DiegoZardetto/ReGenesees>}.  Variances of linear
combinations (changes and averages) and ratios are calculated from a covariance
matrix based on residuals according to the calibration model.  The methodology
was presented at the conference, The Use of R in Official Statistics, and is
described in Langsrud (2016)
<http://www.revistadestatistica.ro/wp-content/uploads/2016/06/RRS2_2016_A021.pdf>.")
    (license license:gpl2)))

(define-public r-calibratebinary
  (package
    (name "r-calibratebinary")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "calibrateBinary" version))
       (sha256
        (base32 "1k6sl4bg05piyczpk6wsva914gcmy8viyz4423gx9i6ddflb7xdb"))))
    (properties `((upstream-name . "calibrateBinary")))
    (build-system r-build-system)
    (propagated-inputs (list r-randtoolbox r-kernlab r-gpfit r-gelnet))
    (home-page "https://cran.r-project.org/package=calibrateBinary")
    (synopsis "Calibration for Computer Experiments with Binary Responses")
    (description
     "This package performs the calibration procedure proposed by Sung et al. (2018+)
<@code{arXiv:1806.01453>}.  This calibration method is particularly useful when
the outputs of both computer and physical experiments are binary and the
estimation for the calibration parameters is of interest.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-calibrar
  (package
    (name "r-calibrar")
    (version "0.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "calibrar" version))
       (sha256
        (base32 "10ig891vbxc9wqpmf5pmqyz9pi7mp4nicipmwgjbsygrqkqy0m0v"))))
    (properties `((upstream-name . "calibrar")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-soma
                             r-rgenoud
                             r-pso
                             r-optimx
                             r-minqa
                             r-lbfgsb3c
                             r-gensa
                             r-foreach
                             r-dfoptim
                             r-deoptim
                             r-cmaes
                             r-bb))
    (native-inputs (list r-knitr))
    (home-page "https://roliveros-ramos.github.io/calibrar/")
    (synopsis "Automated Parameter Estimation for Complex Models")
    (description
     "General optimisation and specific tools for the parameter estimation (i.e.
calibration) of complex models, including stochastic ones.  It implements
generic functions that can be used for fitting any type of models, especially
those with non-differentiable objective functions, with the same syntax as
base::optim.  It supports multiple phases estimation (sequential parameter
masking), constrained optimization (bounding box restrictions) and automatic
parallel computation of numerical gradients.  Some common maximum likelihood
estimation methods and automated construction of the objective function from
simulated model outputs is provided.  See
<https://roliveros-ramos.github.io/calibrar/> for more details.")
    (license license:gpl2)))

(define-public r-calibmsm
  (package
    (name "r-calibmsm")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "calibmsm" version))
       (sha256
        (base32 "1yg5m2zsiw005fdihlilk43h27c7yyzlnbsb32qr9k67q010rk00"))))
    (properties `((upstream-name . "calibmsm")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam
                             r-tidyr
                             r-survival
                             r-rms
                             r-mstate
                             r-hmisc
                             r-gridextra
                             r-ggpubr
                             r-ggplot2
                             r-ggextra
                             r-dplyr
                             r-boot))
    (native-inputs (list r-r-rsp r-knitr))
    (home-page "https://alexpate30.github.io/calibmsm/")
    (synopsis
     "Calibration Plots for the Transition Probabilities from Multistate Models")
    (description
     "Assess the calibration of an existing (i.e.  previously developed) multistate
model through calibration plots.  Calibration is assessed using one of three
methods.  1) Calibration methods for binary logistic regression models applied
at a fixed time point in conjunction with inverse probability of censoring
weights.  2) Calibration methods for multinomial logistic regression models
applied at a fixed time point in conjunction with inverse probability of
censoring weights.  3) Pseudo-values estimated using the Aalen-Johansen
estimator of observed risk.  All methods are applied in conjunction with
landmarking when required.  These calibration plots evaluate the calibration (in
a validation cohort of interest) of the transition probabilities estimated from
an existing multistate model.  While package development has focused on
multistate models, calibration plots can be produced for any model which
utilises information post baseline to update predictions (e.g. dynamic models);
competing risks models; or standard single outcome survival models, where
predictions can be made at any landmark time.  Please see Pate et al. (2024)
<doi:10.1002/sim.10094> and Pate et al. (2024)
<https://alexpate30.github.io/calibmsm/articles/Overview.html>.")
    (license license:expat)))

(define-public r-caliberrfimpute
  (package
    (name "r-caliberrfimpute")
    (version "1.0-7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CALIBERrfimpute" version))
       (sha256
        (base32 "1fspn6wgr0kc7j4ixx24c706kzrgjhi1b1w28izpfxm4r89zk08s"))))
    (properties `((upstream-name . "CALIBERrfimpute")))
    (build-system r-build-system)
    (propagated-inputs (list r-randomforest r-mvtnorm r-mice))
    (home-page "https://cran.r-project.org/package=CALIBERrfimpute")
    (synopsis "Multiple Imputation Using MICE and Random Forest")
    (description
     "This package provides functions to impute using random forest under full
conditional specifications (multivariate imputation by chained equations).  The
methods are described in Shah and others (2014) <doi:10.1093/aje/kwt312>.")
    (license license:gpl3)))

(define-public r-calf
  (package
    (name "r-calf")
    (version "1.0.17")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CALF" version))
       (sha256
        (base32 "021x1gp0493g6qnfih755c0xcddz77i3p22bgjlx1lpzgqmrgrki"))))
    (properties `((upstream-name . "CALF")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2 r-data-table))
    (home-page "https://cran.r-project.org/package=CALF")
    (synopsis "Coarse Approximation Linear Function")
    (description
     "This package contains greedy algorithms for coarse approximation linear
functions.")
    (license license:gpl2)))

(define-public r-calendrio
  (package
    (name "r-calendrio")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "calendRio" version))
       (sha256
        (base32 "152fb5yaazb2hh99ag1aq675gc5f8xw990w55nkhxqhg6w5p0ln9"))))
    (properties `((upstream-name . "calendRio")))
    (build-system r-build-system)
    (propagated-inputs (list r-suncalc
                             r-ggplot2
                             r-ggimage
                             r-gggibbous
                             r-forcats
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=calendRio")
    (synopsis "'calendR' Fork with Additional Features (Backwards Compatible)")
    (description
     "Fork of @code{calendR} R package to generate ready to print calendars with
ggplot2 (see <https://r-coder.com/calendar-plot-r/>) with additional features
(backwards compatible). @code{calendRio} provides a @code{calendR}() function
that serves as a drop-in replacement for the upstream version but allows for
additional parameters unlocking extra functionality.")
    (license license:agpl3+)))

(define-public r-calendr
  (package
    (name "r-calendr")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "calendR" version))
       (sha256
        (base32 "1fkzsibjawshb4i5q941bjjn4yxkj8wcblw5ckmig3s31sjrb1yc"))))
    (properties `((upstream-name . "calendR")))
    (build-system r-build-system)
    (propagated-inputs (list r-suncalc
                             r-ggplot2
                             r-ggimage
                             r-gggibbous
                             r-forcats
                             r-dplyr))
    (home-page "https://r-coder.com/")
    (synopsis
     "Ready to Print Monthly and Yearly Calendars Made with 'ggplot2'")
    (description
     "This package contains the function @code{calendR}() for creating fully
customizable monthly and yearly calendars (colors, fonts, formats, ...) and even
heatmap calendars.  In addition, it allows saving the calendars in ready to
print A4 format PDF files.")
    (license license:gpl2)))

(define-public r-calendar
  (package
    (name "r-calendar")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "calendar" version))
       (sha256
        (base32 "0gci7xlws9l93xrl3ksx85vqv9c2z86bmarivqjpigs40ppnsyn2"))))
    (properties `((upstream-name . "calendar")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-lubridate r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/atfutures/calendar")
    (synopsis
     "Create, Read, Write, and Work with 'iCalendar' Files, Calendars and Scheduling Data")
    (description
     "This package provides function to create, read, write, and work with
@code{iCalendar} files (which typically have .ics or .ical extensions), and the
scheduling data, calendars and timelines of people, organisations and other
entities that they represent. @code{iCalendar} is an open standard for
exchanging calendar and scheduling information between users and computers,
described at <https://icalendar.org/>.")
    (license license:asl2.0)))

(define-public r-calcunique
  (package
    (name "r-calcunique")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "calcUnique" version))
       (sha256
        (base32 "012mjayj90m5gsd8mhm2ic00pa0bnrjiidq9mv4vxj8slwp641rz"))))
    (properties `((upstream-name . "calcUnique")))
    (build-system r-build-system)
    (home-page "https://github.com/stephenbfroehlich/calcUnique")
    (synopsis "Simple Wrapper for Computationally Expensive Functions")
    (description
     "This is a one-function package that will pass only unique values to a
computationally-expensive function that returns an output of the same length as
the input.  In importing and working with tidy data, it is common to have index
columns, often including time stamps that are far from unique.  Some functions
to work with these such as text conversion to other variable types (e.g.
as.POSIXct()), various grep()-based functions, and often the cut() function are
relatively slow when working with tens of millions of rows or more.")
    (license license:expat)))

(define-public r-calculator-lr-fns
  (package
    (name "r-calculator-lr-fns")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Calculator.LR.FNs" version))
       (sha256
        (base32 "03qg9rnz623dwnp68xhhsh9788s49n6xp0migg1nnjaqhrahlgdd"))))
    (properties `((upstream-name . "Calculator.LR.FNs")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=Calculator.LR.FNs")
    (synopsis "Calculator for LR Fuzzy Numbers")
    (description
     "Arithmetic operations scalar multiplication, addition, subtraction,
multiplication and division of LR fuzzy numbers (which are on the basis of
extension principle) have a complicate form for using in fuzzy Statistics, fuzzy
Mathematics, machine learning, fuzzy data analysis and etc.  Calculator for LR
Fuzzy Numbers package relieve and aid applied users to achieve a simple and
closed form for some complicated operator based on LR fuzzy numbers and also the
user can easily draw the membership function of the obtained result by this
package.")
    (license license:lgpl3+)))

(define-public r-calcthemall-prm
  (package
    (name "r-calcthemall-prm")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CalcThemAll.PRM" version))
       (sha256
        (base32 "1jm2b4sy1vhzsr2hhl219h65yzx30n7pl0h3w1v3fmfd0hamd1s8"))))
    (properties `((upstream-name . "CalcThemAll.PRM")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-vgam
                             r-plotly
                             r-mass
                             r-magrittr
                             r-lubridate
                             r-dt
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=CalcThemAll.PRM")
    (synopsis
     "Calculate Pesticide Risk Metric (PRM) Values from Multiple Pesticides...Calc Them All")
    (description
     "This package contains functions which can be used to calculate Pesticide Risk
Metric values in aquatic environments from concentrations of multiple pesticides
with known species sensitive distributions (SSDs).  Pesticides provided by this
package have all be validated however if the user has their own pesticides with
SSD values they can append them to the pesticide_info table to include them in
estimates.")
    (license license:gpl3+)))

(define-public r-calango
  (package
    (name "r-calango")
    (version "1.0.20")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CALANGO" version))
       (sha256
        (base32 "1fh42my2fs142qzq5b1q5b2zr8pbw12h1pp8c53z0ii0g5pz075h"))))
    (properties `((upstream-name . "CALANGO")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmarkdown
                             r-plotly
                             r-pkgdown
                             r-pbmcapply
                             r-nlme
                             r-knitr
                             r-htmlwidgets
                             r-htmltools
                             r-heatmaply
                             r-ggplot2
                             r-dt
                             r-dendextend
                             r-biocmanager
                             r-assertthat
                             r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://labpackages.github.io/CALANGO/")
    (synopsis "Comparative Analysis with Annotation-Based Genomic Components")
    (description
     "This package provides a first-principle, phylogeny-aware comparative genomics
tool for investigating associations between terms used to annotate genomic
components (e.g., Pfam IDs, Gene Ontology terms,) with quantitative or rank
variables such as number of cell types, genome size, or density of specific
genomic elements.  See the project website for more information, documentation
and examples, and <doi:10.1016/j.patter.2023.100728> for the full paper.")
    (license license:gpl2)))

(define-public r-calacs
  (package
    (name "r-calacs")
    (version "2.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "calACS" version))
       (sha256
        (base32 "0a53k2rzyjksb0ypr5zrask4a6mgiyrqx0l2z3lm218y8pk2jf1w"))))
    (properties `((upstream-name . "calACS")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=calACS")
    (synopsis "Calculations for All Common Subsequences")
    (description
     "This package implements several string comparison algorithms, including
@code{calACS} (count all common subsequences), @code{lenACS} (calculate the
lengths of all common subsequences), and @code{lenLCS} (calculate the length of
the longest common subsequence).  Some algorithms differentiate between the more
strict definition of subsequence, where a common subsequence cannot be separated
by any other items, from its looser counterpart, where a common subsequence can
be interrupted by other items.  This difference is shown in the suffix of the
algorithm (-Strict vs -Loose).  For example, q-w is a common subsequence of
q-w-e-r and q-e-w-r on the looser definition, but not on the more strict
definition. @code{calACSLoose} Algorithm from Wang, H. All common subsequences
(2007) IJCAI International Joint Conference on Artificial Intelligence, pp.
635-640.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-caiser
  (package
    (name "r-caiser")
    (version "1.0.17")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CAISEr" version))
       (sha256
        (base32 "01gxxq9bfrrishzawmqh47byhc3szfss9bmcsh1p2gi9ml6aqcay"))))
    (properties `((upstream-name . "CAISEr")))
    (build-system r-build-system)
    (propagated-inputs (list r-pbmcapply r-gridextra r-ggplot2 r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://fcampelo.github.io/CAISEr/")
    (synopsis "Comparison of Algorithms with Iterative Sample Size Estimation")
    (description
     "This package provides functions for performing experimental comparisons of
algorithms using adequate sample sizes for power and accuracy.  Implements the
methodology originally presented in Campelo and Takahashi (2019)
<doi:10.1007/s10732-018-9396-7> for the comparison of two algorithms, and later
generalised in Campelo and Wanner (Submitted, 2019) <arxiv:1908.01720>.")
    (license license:gpl2)))

(define-public r-cainterprtools
  (package
    (name "r-cainterprtools")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CAinterprTools" version))
       (sha256
        (base32 "07rvi91ysqyfwagmip0cnqjahv1n8slicd5hznqf5v3l841xh7p7"))))
    (properties `((upstream-name . "CAinterprTools")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2
                             r-rcmdrmisc
                             r-hmisc
                             r-ggrepel
                             r-ggplot2
                             r-factominer
                             r-cluster
                             r-classint
                             r-ca))
    (home-page "https://cran.r-project.org/package=CAinterprTools")
    (synopsis
     "Graphical Aid in Correspondence Analysis Interpretation and Significance Testings")
    (description
     "Allows to plot a number of information related to the interpretation of
Correspondence Analysis results.  It provides the facility to plot the
contribution of rows and columns categories to the principal dimensions, the
quality of points display on selected dimensions, the correlation of row and
column categories to selected dimensions, etc.  It also allows to assess which
dimension(s) is important for the data structure interpretation by means of
different statistics and tests.  The package also offers the facility to plot
the permuted distribution of the table total inertia as well as of the inertia
accounted for by pairs of selected dimensions.  Different facilities are also
provided that aim to produce interpretation-oriented scatterplots.  Reference:
Alberti 2015 <doi:10.1016/j.softx.2015.07.001>.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-cagr
  (package
    (name "r-cagr")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CAGR" version))
       (sha256
        (base32 "1qyk43x8i0z2bl0ahj34d02zinsnp11716385y209l7c0ws9ynaa"))))
    (properties `((upstream-name . "CAGR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=CAGR")
    (synopsis "Compound Annual Growth Rate")
    (description
     "This package provides a time series usually does not have a uniform growth rate.
 Compound Annual Growth Rate measures the average annual growth over a given
period.  More details can be found in Bardhan et al. (2022)
<DOI:10.18805/ag.D-5418>.")
    (license license:gpl3)))

(define-public r-caffsim
  (package
    (name "r-caffsim")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "caffsim" version))
       (sha256
        (base32 "00bkgmmqrydpji2pvhcchgl2p8w5ksby4g80i3h76q0bm2325w9h"))))
    (properties `((upstream-name . "caffsim")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-shiny
                             r-mgcv
                             r-markdown
                             r-ggplot2
                             r-dplyr))
    (home-page "https://github.com/asancpt/caffsim")
    (synopsis
     "Simulation of Plasma Caffeine Concentrations by Using Population Pharmacokinetic Model")
    (description
     "Simulate plasma caffeine concentrations using population pharmacokinetic model
described in Lee, Kim, Perera, @code{McLachlan} and Bae (2015)
<doi:10.1007/s00431-015-2581-x>.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-caesar-suite
  (package
    (name "r-caesar-suite")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CAESAR.Suite" version))
       (sha256
        (base32 "1ijyza7i7pw2mpqlg502crd7kmk0xg8ksbj0d9dnsddi87d7wy0y"))))
    (properties `((upstream-name . "CAESAR.Suite")))
    (build-system r-build-system)
    (propagated-inputs (list r-seurat
                             r-scater
                             r-rcpparmadillo
                             r-rcpp
                             r-progress
                             r-profast
                             r-pbapply
                             r-matrix
                             r-irlba
                             r-ggrepel
                             r-ggplot2
                             r-future
                             r-furrr
                             r-desctools
                             r-ade4))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://github.com/XiaoZhangryy/CAESAR.Suite")
    (synopsis
     "CAESAR: a Cross-Technology and Cross-Resolution Framework for Spatial Omics Annotation")
    (description
     "Biotechnology in spatial omics has advanced rapidly over the past few years,
enhancing both throughput and resolution.  However, existing annotation
pipelines in spatial omics predominantly rely on clustering methods, lacking the
flexibility to integrate extensive annotated information from single-cell RNA
sequencing (@code{scRNA-seq}) due to discrepancies in spatial resolutions,
species, or modalities.  Here we introduce the CAESAR suite, an open-source
software package that provides image-based spatial co-embedding of locations and
genomic features.  It uniquely transfers labels from @code{scRNA-seq} reference,
enabling the annotation of spatial omics datasets across different technologies,
resolutions, species, and modalities, based on the conserved relationship
between signature genes and cells/locations at an appropriate level of
granularity.  Notably, CAESAR enriches location-level pathways, allowing for the
detection of gradual biological pathway activation within spatially defined
domain types.  More details on the methods related to our paper currently under
submission.  A full reference to the paper will be provided in future versions
once the paper is published.")
    (license license:gpl2+)))

(define-public r-caesar
  (package
    (name "r-caesar")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "caesar" version))
       (sha256
        (base32 "17w19m1c4a8x68bfbll71r9d3d34xnqw7lkhvqbnajd0cdm9xpa2"))))
    (properties `((upstream-name . "caesar")))
    (build-system r-build-system)
    (propagated-inputs (list r-binhf))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jacobkap/caesar")
    (synopsis "Encrypts and Decrypts Strings")
    (description
     "Encrypts and decrypts strings using either the Caesar cipher or a pseudorandom
number generation (using set.seed()) method.")
    (license license:expat)))

(define-public r-cadftest
  (package
    (name "r-cadftest")
    (version "0.3-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CADFtest" version))
       (sha256
        (base32 "06bwv728ckalzibxginzfica24w18m4g87i0i064m3q89ghmnlqm"))))
    (properties `((upstream-name . "CADFtest")))
    (build-system r-build-system)
    (propagated-inputs (list r-urca r-tseries r-sandwich r-dynlm))
    (home-page "http://www.jstatsoft.org/v32/i02")
    (synopsis
     "Package to Perform Covariate Augmented Dickey-Fuller Unit Root Tests")
    (description
     "Hansen's (1995) Covariate-Augmented Dickey-Fuller (CADF) test.  The only
required argument is y, the Tx1 time series to be tested.  If no stationary
covariate X is passed to the procedure, then an ordinary ADF test is performed.
The p-values of the test are computed using the procedure illustrated in Lupi
(2009).")
    (license license:gpl2+)))

(define-public r-cadence
  (package
    (name "r-cadence")
    (version "1.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CaDENCE" version))
       (sha256
        (base32 "1z3p5y1l67r470x6wrhnyjvw1ndppcm08fpj99x122j7kn6byff2"))))
    (properties `((upstream-name . "CaDENCE")))
    (build-system r-build-system)
    (propagated-inputs (list r-pso))
    (home-page "https://cran.r-project.org/package=CaDENCE")
    (synopsis
     "Conditional Density Estimation Network Construction and Evaluation")
    (description
     "Parameters of a user-specified probability distribution are modelled by a
multi-layer perceptron artificial neural network.  This framework can be used to
implement probabilistic nonlinear models including mixture density networks,
heteroscedastic regression models, zero-inflated models, etc.  following Cannon
(2012) <doi:10.1016/j.cageo.2011.08.023>.")
    (license license:gpl2)))

(define-public r-cacirt
  (package
    (name "r-cacirt")
    (version "1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cacIRT" version))
       (sha256
        (base32 "145j6isqa8yj2nvlqkxagd076zs10ng3n44khi5p4jj77fjc8gh6"))))
    (properties `((upstream-name . "cacIRT")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=cacIRT")
    (synopsis
     "Classification Accuracy and Consistency under Item Response Theory")
    (description
     "Computes classification accuracy and consistency indices under Item Response
Theory.  Implements the total score IRT-based methods in Lee, Hanson & Brennen
(2002) and Lee (2010), the IRT-based methods in Rudner (2001, 2005), and the
total score nonparametric methods in Lathrop & Cheng (2014).  For dichotomous
and polytomous tests.")
    (license license:gpl2+)))

(define-public r-cacimar
  (package
    (name "r-cacimar")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CACIMAR" version))
       (sha256
        (base32 "0fdi2ls0j10fky3jygqx93h8m1957cdbn1vxdi69bq08xf2c5n5h"))))
    (properties `((upstream-name . "CACIMAR")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridislite
                             r-seurat
                             r-rocr
                             r-reshape2
                             r-psych
                             r-pheatmap
                             r-pbapply
                             r-dplyr))
    (home-page "https://github.com/jiang-junyao/CACIMAR")
    (synopsis
     "Cross-Species Analysis of Cell Identities, Markers and Regulations")
    (description
     "This package provides a toolkit to perform cross-species analysis based on
@code{scRNA-seq} data.  This package contains 5 main features. (1) identify
Markers in each cluster. (2) Cell type annotation (3) identify conserved
markers. (4) identify conserved cell types. (5) identify conserved modules of
regulatory networks.")
    (license license:expat)))

(define-public r-cache
  (package
    (name "r-cache")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cache" version))
       (sha256
        (base32 "0ix8z9zxslnycqn75rlz7f059jwfcclpxbas5sihcdmrdavz5ggj"))))
    (properties `((upstream-name . "cache")))
    (build-system r-build-system)
    (propagated-inputs (list r-here r-digest r-cli r-assert))
    (home-page "https://github.com/OlivierBinette/cache")
    (synopsis "Cache and Retrieve Computation Results")
    (description
     "Easily cache and retrieve computation results.  The package works seamlessly
across interactive R sessions, R scripts and Rmarkdown documents.")
    (license license:expat)))

(define-public r-cacc
  (package
    (name "r-cacc")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cacc" version))
       (sha256
        (base32 "0lyczm8zdd80np7xljvvgakscbivxvpdr0vp71f40l04nx3aijxg"))))
    (properties `((upstream-name . "cacc")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-tibble r-rlang r-ggplot2 r-dplyr))
    (home-page "https://github.com/amoneva/cacc")
    (synopsis "Conjunctive Analysis of Case Configurations")
    (description
     "This package provides a set of functions to conduct Conjunctive Analysis of Case
Configurations (CACC) as described in Miethe, Hart, and Regoeczi (2008)
<doi:10.1007/s10940-008-9044-8>, and identify and quantify situational
clustering in dominant case configurations as described in Hart (2019)
<doi:10.1177/0011128719866123>.  Initially conceived as an exploratory technique
for multivariate analysis of categorical data, CACC has developed to include
formal statistical tests that can be applied in a wide variety of contexts.
This technique allows examining composite profiles of different units of
analysis in an alternative way to variable-oriented methods.")
    (license license:expat)))

(define-public r-cabootcrs
  (package
    (name "r-cabootcrs")
    (version "2.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cabootcrs" version))
       (sha256
        (base32 "0aqp8ip0s9raz4minhaw7vcn253xld4dgr957wsl2sp2nd8z66rq"))))
    (properties `((upstream-name . "cabootcrs")))
    (build-system r-build-system)
    (propagated-inputs (list r-lpsolve r-colorspace))
    (home-page "https://cran.r-project.org/package=cabootcrs")
    (synopsis
     "Bootstrap Confidence Regions for Simple and Multiple Correspondence Analysis")
    (description
     "This package performs simple correspondence analysis on a two-way contingency
table, or multiple correspondence analysis (homogeneity analysis) on data with p
categorical variables, and produces bootstrap-based elliptical confidence
regions around the projected coordinates for the category points.  Includes
routines to plot the results in a variety of styles.  Also reports the standard
numerical output for correspondence analysis.")
    (license license:gpl3)))

(define-public r-cabinets
  (package
    (name "r-cabinets")
    (version "0.6.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "cabinets" version))
       (sha256
        (base32 "1pypn29v91zqncv5kxinfz0f633qmic7n87rf4amjrq83iiid6md"))))
    (properties `((upstream-name . "cabinets")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-rstudioapi
                             r-renv
                             r-r6
                             r-glue
                             r-git2r
                             r-fs
                             r-crayon
                             r-cli))
    (home-page "https://github.com/nt-williams/cabinets")
    (synopsis "Project Specific Workspace Organization Templates")
    (description
     "This package creates project specific directory and file templates that are
written to a .Rprofile file.  Upon starting a new R session, these templates can
be used to streamline the creation of new directories that are standardized to
the user's preferences and can include the initiation of a git repository, an
RStudio R project, and project-local dependency management with the renv
package.")
    (license license:expat)))

(define-public r-ca3variants
  (package
    (name "r-ca3variants")
    (version "3.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "CA3variants" version))
       (sha256
        (base32 "0nc82xw341bv01knr2ksyifl0bkriwg4dfkw0fdkzh0b6dw2wfzr"))))
    (properties `((upstream-name . "CA3variants")))
    (build-system r-build-system)
    (propagated-inputs (list r-plotly
                             r-multichull
                             r-gridextra
                             r-ggrepel
                             r-ggplot2
                             r-ggforce))
    (home-page "https://www.R-project.org")
    (synopsis "Three-Way Correspondence Analysis Variants")
    (description
     "This package provides four variants of three-way correspondence analysis (ca):
three-way symmetrical ca, three-way non-symmetrical ca, three-way ordered
symmetrical ca and three-way ordered non-symmetrical ca.")
    (license license:gpl3+)))

(define-public r-c50
  (package
    (name "r-c50")
    (version "0.1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "C50" version))
       (sha256
        (base32 "05cwvapd84b40v90kfkhjhawhhaq5bm7nscnjd95flpds1gbvldv"))))
    (properties `((upstream-name . "C50")))
    (build-system r-build-system)
    (propagated-inputs (list r-partykit r-cubist))
    (native-inputs (list r-knitr))
    (home-page "https://topepo.github.io/C5.0/")
    (synopsis "C5.0 Decision Trees and Rule-Based Models")
    (description
     "C5.0 decision trees and rule-based models for pattern recognition that extend
the work of Quinlan (1993, ISBN:1-55860-238-0).")
    (license license:gpl3)))

(define-public r-c443
  (package
    (name "r-c443")
    (version "3.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "C443" version))
       (sha256
        (base32 "021i36gmayvc1qqxjy59b2m7z299yaj0wxcaqhb0j2kbaj439p8w"))))
    (properties `((upstream-name . "C443")))
    (build-system r-build-system)
    (propagated-inputs (list r-rpart
                             r-rcolorbrewer
                             r-ranger
                             r-randomforest
                             r-plyr
                             r-partykit
                             r-mass
                             r-igraph
                             r-gridextra
                             r-ggplot2
                             r-foreach
                             r-doparallel
                             r-cluster))
    (home-page "https://github.com/KULeuven-PPW-OKPIV/C443")
    (synopsis "See a Forest for the Trees")
    (description
     "Get insight into a forest of classification trees, by calculating similarities
between the trees, and subsequently clustering them.  Each cluster is
represented by it's most central cluster member.  The package implements the
methodology described in Sies & Van Mechelen (2020)
<doi:10.1007/s00357-019-09350-4>.")
    (license license:gpl2+)))

(define-public r-c3net
  (package
    (name "r-c3net")
    (version "1.1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "c3net" version))
       (sha256
        (base32 "0xhl6spii8kwyqdc86wbp6zn1727xq7xnscx4ld0a6hgbra348pf"))))
    (properties `((upstream-name . "c3net")))
    (build-system r-build-system)
    (propagated-inputs (list r-igraph))
    (home-page "https://cran.r-project.org/package=c3net")
    (synopsis "Inferring Large-Scale Gene Networks with C3NET")
    (description
     "Allows inferring gene regulatory networks with direct physical interactions from
microarray expression data using C3NET.")
    (license license:gpl3+)))

(define-public r-c3
  (package
    (name "r-c3")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "c3" version))
       (sha256
        (base32 "1c2k7ml153bby749qi3a6nckhwwr71mvvps9dkbzkxkwnmlwpz1h"))))
    (properties `((upstream-name . "c3")))
    (build-system r-build-system)
    (arguments
     (list
      #:modules '((guix build r-build-system)
                  (guix build minify-build-system)
                  (guix build utils)
                  (ice-9 match))
      #:imported-modules `(,@%r-build-system-modules (guix build
                                                      minify-build-system))
      #:phases '(modify-phases %standard-phases
                  (add-after 'unpack 'process-javascript
                    (lambda* (#:key inputs #:allow-other-keys)
                      (with-directory-excursion "inst/"
                        (for-each (match-lambda
                                    ((source . target) (minify source
                                                               #:target target)))
                                  '())))))))
    (propagated-inputs (list r-viridis
                             r-lazyeval
                             r-jsonlite
                             r-htmlwidgets
                             r-dplyr
                             r-data-table))
    (native-inputs (list r-knitr esbuild))
    (home-page "https://github.com/mrjoh3/c3")
    (synopsis "'C3.js' Chart Library")
    (description
     "Create interactive charts with the C3.js <http://c3js.org/> charting library.
All plot types in C3.js are available and include line, bar, scatter, and mixed
geometry plots.  Plot annotations, labels and axis are highly adjustable.
Interactive web based charts can be embedded in R Markdown documents or Shiny
web applications.")
    (license license:gpl3+)))

(define-public r-c2z
  (package
    (name "r-c2z")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "c2z" version))
       (sha256
        (base32 "0nrgyr6m8n710xl7bgv16p4cq4h920n4irjzf944b9sv8l6z72x1"))))
    (properties `((upstream-name . "c2z")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-rvest
                             r-rlang
                             r-purrr
                             r-jsonlite
                             r-httr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/oeysan/c2z/")
    (synopsis "Reference Manager")
    (description
     "Cristin to Zotero ('c2z') aims at obtaining total dominion over Cristin
('Current Research Information @code{SysTem} in Norway') and Zotero'.  The
package enables manipulating Zotero libraries using R'.  Import references from
Cristin', Regjeringen', CRAN', ISBN ('Alma', @code{LoC}'), and DOI
('@code{CrossRef}', @code{DataCite}') to a Zotero library.  Add, edit, copy, or
delete items, including attachments and collections, and export references to
@code{BibLaTeX} (and other formats).")
    (license license:expat)))

(define-public r-c2c
  (package
    (name "r-c2c")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "c2c" version))
       (sha256
        (base32 "149np512wjnlr9glmqxpiamf6c31v0bh6ym95jpdhk0iw3ic9kvh"))))
    (properties `((upstream-name . "c2c")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mitchest/c2c/")
    (synopsis
     "Compare Two Classifications or Clustering Solutions of Varying Structure")
    (description
     "Compare two classifications or clustering solutions that may or may not have the
same number of classes, and that might have hard or soft (fuzzy, probabilistic)
membership.  Calculate various metrics to assess how the clusters compare to
each other.  The calculations are simple, but provide a handy tool for users
unfamiliar with matrix multiplication.  This package is not geared towards
traditional accuracy assessment for classification/ mapping applications - the
motivating use case is for comparing a probabilistic clustering solution to a
set of reference or existing class labels that could have any number of classes
(that is, without having to degrade the probabilistic clustering to hard
classes).")
    (license license:gpl3)))

(define-public r-c212
  (package
    (name "r-c212")
    (version "0.98")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "c212" version))
       (sha256
        (base32 "0pzg239602iq56nhxfdvlk26z58lz6vvlbwsdpwhmich0by4gx4x"))))
    (properties `((upstream-name . "c212")))
    (build-system r-build-system)
    (propagated-inputs (list r-coda))
    (home-page "https://cran.r-project.org/package=c212")
    (synopsis
     "Methods for Detecting Safety Signals in Clinical Trials Using Body-Systems (System Organ Classes)")
    (description
     "This package provides methods for detecting safety signals in clinical trials
using groupings of adverse events by body-system or system organ class.  This
work was supported by the Engineering and Physical Sciences Research Council
(UK) (EPSRC) [award reference 1521741] and Frontier Science (Scotland) Ltd.  The
package title c212 is in reference to the original Engineering and Physical
Sciences Research Council (UK) funded project which was named CASE 2/12.")
    (license license:gpl2+)))

(define-public r-c19dnuts
  (package
    (name "r-c19dnuts")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "C19dNUTS" version))
       (sha256
        (base32 "09iclbkgaxz946nj4ppdzyr5ssipcip4nscxs10j0209frjgjhap"))))
    (properties `((upstream-name . "C19dNUTS")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=C19dNUTS")
    (synopsis "Dataset of Regional COVID-19 Deaths per 100,000 Pop (NUTS)")
    (description
     "Dataset containing cumulative COVID-19 deaths (absolute and per 100,000 pop) at
the regional level (mostly NUTS 3) for 31 EU/EFTA countries.")
    (license license:gpl2+)))

(define-public r-c060
  (package
    (name "r-c060")
    (version "0.3-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "c060" version))
       (sha256
        (base32 "0dmr9xyml69a3xggjahpc5r6kg2qf9h7hkl7kdz7qkl8aslca0zn"))))
    (properties `((upstream-name . "c060")))
    (build-system r-build-system)
    (propagated-inputs (list r-tgp
                             r-survival
                             r-peperr
                             r-penalizedsvm
                             r-penalized
                             r-mlegp
                             r-lattice
                             r-glmnet))
    (home-page "https://github.com/fbertran/c060/")
    (synopsis
     "Extended Inference for Lasso and Elastic-Net Regularized Cox and Generalized Linear Models")
    (description
     "The c060 package provides additional functions to perform stability selection,
model validation and parameter tuning for glmnet models.")
    (license license:gpl2)))

