(define-module (guix-cran packages d)
  #:use-module (guix packages)
  #:use-module (guix download)
  #:use-module (guix build-system r)
  #:use-module ((guix licenses)
                #:prefix license:)
  #:use-module (gnu packages gcc)
  #:use-module (gnu packages statistics)
  #:use-module (gnu packages cran)
  #:use-module (gnu packages bioconductor)
  #:use-module (gnu packages maths)
  #:use-module (gnu packages base)
  #:use-module (gnu packages video)
  #:use-module (gnu packages web)
  #:use-module (gnu packages libreoffice)
  #:use-module (gnu packages docker)
  #:use-module (gnu packages pkg-config)
  #:use-module (gnu packages python)
  #:use-module (gnu packages julia)
  #:use-module (gnu packages java)
  #:use-module (gnu packages tls)
  #:use-module (gnu packages compression)
  #:use-module (gnu packages geo)
  #:use-module (gnu packages sqlite)
  #:use-module (gnu packages haskell-xyz)
  #:use-module (gnu packages version-control)
  #:use-module (gnu packages tcl)
  #: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 c)
  #:use-module (guix-cran packages b)
  #:use-module (guix-cran packages a))

(define-public r-dyss
  (package
    (name "r-dyss")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DySS" version))
       (sha256
        (base32 "1aa67m224bhzzg089rhxwqgbmwwq5py8ikix8khwraz5cnjz2f83"))))
    (properties `((upstream-name . "DySS")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-gridextra r-ggplot2))
    (native-inputs (list r-knitr gfortran))
    (home-page "https://cran.r-project.org/package=DySS")
    (synopsis "Dynamic Screening Systems")
    (description
     "In practice, we will encounter problems where the longitudinal performance of
processes needs to be monitored over time.  Dynamic screening systems
(@code{DySS}) are methods that aim to identify and give signals to processes
with poor performance as early as possible.  This package is designed to
implement dynamic screening systems and the related methods.  References: Qiu,
P. and Xiang, D. (2014) <doi:10.1080/00401706.2013.822423>; Qiu, P. and Xiang,
D. (2015) <doi:10.1002/sim.6477>; Li, J. and Qiu, P. (2016)
<doi:10.1080/0740817X.2016.1146423>; Li, J. and Qiu, P. (2017)
<doi:10.1002/qre.2160>; You, L. and Qiu, P. (2019)
<doi:10.1080/00949655.2018.1552273>; Qiu, P., Xia, Z., and You, L. (2020)
<doi:10.1080/00401706.2019.1604434>; You, L., Qiu, A., Huang, B., and Qiu, P.
(2020) <doi:10.1002/bimj.201900127>; You, L. and Qiu, P. (2021)
<doi:10.1080/00224065.2020.1767006>.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-dyspiadata
  (package
    (name "r-dyspiadata")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DysPIAData" version))
       (sha256
        (base32 "1i4z9xhnzih7jnj3l1d6wpgfsayb452sh4q99w2npg1iipsjb1vl"))))
    (properties `((upstream-name . "DysPIAData")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DysPIAData")
    (synopsis "Background and Pathway Data Used in 'DysPIA'")
    (description
     "This dataset includes Background and Pathway data used in package
@code{DysPIA}'.")
    (license license:gpl2+)))

(define-public r-dyspia
  (package
    (name "r-dyspia")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DysPIA" version))
       (sha256
        (base32 "0ih8sl89h6xbmmjjsbxcvgp6wqk7f1wqzwkc43k3i5w7fgb0hlpc"))))
    (properties `((upstream-name . "DysPIA")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp
                             r-parmigene
                             r-fastmatch
                             r-dyspiadata
                             r-data-table
                             r-biocparallel))
    (home-page "https://cran.r-project.org/package=DysPIA")
    (synopsis "Dysregulated Pathway Identification Analysis")
    (description
     "It is used to identify dysregulated pathways based on a pre-ranked gene pair
list.  A fast algorithm is used to make the computation really fast.  The data
in package @code{DysPIAData} is needed.")
    (license license:gpl2+)))

(define-public r-dysem
  (package
    (name "r-dysem")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dySEM" version))
       (sha256
        (base32 "1akjda85sad4inw789wq0szqxrilkzf3lhmf7k3mhhjdix02fqrm"))))
    (properties `((upstream-name . "dySEM")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-semplot
                             r-rlang
                             r-magrittr
                             r-lifecycle
                             r-lavaan
                             r-gt
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jsakaluk/dySEM")
    (synopsis "Dyadic Structural Equation Modeling")
    (description
     "Scripting of structural equation models via lavaan for Dyadic Data Analysis, and
helper functions for supplemental calculations, tabling, and model
visualization.  Current models supported include Dyadic Confirmatory Factor
Analysis, the ActorâPartner Interdependence Model (observed and latent), the
Common Fate Model (observed and latent), Mutual Influence Model (latent), and
the Bifactor Dyadic Model (latent).")
    (license license:gpl3)))

(define-public r-dynwrap
  (package
    (name "r-dynwrap")
    (version "1.2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynwrap" version))
       (sha256
        (base32 "1jls01flvr91vyipilaqv2n3irniq678bm6f1jlxr2apr7w0rlyx"))))
    (properties `((upstream-name . "dynwrap")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-reshape2
                             r-readr
                             r-purrr
                             r-processx
                             r-matrix
                             r-magrittr
                             r-igraph
                             r-glue
                             r-dynutils
                             r-dynparam
                             r-dplyr
                             r-crayon
                             r-babelwhale
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/dynverse/dynwrap")
    (synopsis "Representing and Inferring Single-Cell Trajectories")
    (description
     "This package provides functionality to infer trajectories from single-cell data,
represent them into a common format, and adapt them.  Other biological
information can also be added, such as cellular grouping, RNA velocity and
annotation.  Saelens et al. (2019) <doi:10.1038/s41587-019-0071-9>.")
    (license license:expat)))

(define-public r-dyntxregime
  (package
    (name "r-dyntxregime")
    (version "4.15")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DynTxRegime" version))
       (sha256
        (base32 "18hk5bc6bsdjdl4736sdk896zblyc8l3ipjii4x2jksngcjvszbb"))))
    (properties `((upstream-name . "DynTxRegime")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgenoud r-modelobj r-kernlab r-dfoptim))
    (home-page "https://cran.r-project.org/package=DynTxRegime")
    (synopsis "Methods for Estimating Optimal Dynamic Treatment Regimes")
    (description
     "This package provides methods to estimate dynamic treatment regimes using
Interactive Q-Learning, Q-Learning, weighted learning, and value-search methods
based on Augmented Inverse Probability Weighted Estimators and Inverse
Probability Weighted Estimators.  Dynamic Treatment Regimes: Statistical Methods
for Precision Medicine, Tsiatis, A. A., Davidian, M. D., Holloway, S. T., and
Laber, E. B., Chapman & Hall/CRC Press, 2020, ISBN:978-1-4987-6977-8.")
    (license license:gpl2)))

(define-public r-dyntaper
  (package
    (name "r-dyntaper")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dyntaper" version))
       (sha256
        (base32 "0i8snv70hzsywijivkxphm7xcp64r7kh8v6hiy0hh4hh624i120i"))))
    (properties `((upstream-name . "dyntaper")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ogarciav/dyntaper")
    (synopsis "Dynamic Stem Profile Models, AKA Tree Taper Equations")
    (description
     "This package performs calculations with tree taper (or stem profile) equations,
including model fitting.  The package implements the methods from GarcÃ­a, O.
(2015) \"Dynamic modelling of tree form\"
<http://mcfns.net/index.php/Journal/article/view/MCFNS7.1_2>.  The models are
parsimonious, describe well the tree bole shape over its full length, and are
consistent with wood formation mechanisms through time.")
    (license license:expat)))

(define-public r-dynsurv
  (package
    (name "r-dynsurv")
    (version "0.4-7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynsurv" version))
       (sha256
        (base32 "0rp51kr6rsfqdcl4gswqz56ppnxa81ak023x3gdxsdf4p9jjhdcy"))))
    (properties `((upstream-name . "dynsurv")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-splines2
                             r-nleqslv
                             r-ggplot2
                             r-data-table
                             r-bh))
    (home-page "https://github.com/wenjie2wang/dynsurv")
    (synopsis "Dynamic Models for Survival Data")
    (description
     "Time-varying coefficient models for interval censored and right censored
survival data including 1) Bayesian Cox model with time-independent,
time-varying or dynamic coefficients for right censored and interval censored
data studied by Sinha et al. (1999) <doi:10.1111/j.0006-341X.1999.00585.x> and
Wang et al. (2013) <doi:10.1007/s10985-013-9246-8>, 2) Spline based time-varying
coefficient Cox model for right censored data proposed by Perperoglou et al.
(2006) <doi:10.1016/j.cmpb.2005.11.006>, and 3) Transformation model with
time-varying coefficients for right censored data using estimating equations
proposed by Peng and Huang (2007) <doi:10.1093/biomet/asm058>.")
    (license license:gpl3+)))

(define-public r-dynsim
  (package
    (name "r-dynsim")
    (version "1.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynsim" version))
       (sha256
        (base32 "1fk23cp2hvkn7msxrdc9cnm4pmcmhcdf3q6rwm507bniigrswnx4"))))
    (properties `((upstream-name . "dynsim")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-gridextra r-ggplot2))
    (home-page "https://cran.r-project.org/package=dynsim")
    (synopsis "Dynamic Simulations of Autoregressive Relationships")
    (description
     "Dynamic simulations and graphical depictions of autoregressive relationships.")
    (license license:gpl3)))

(define-public r-dynrb
  (package
    (name "r-dynrb")
    (version "0.18")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynRB" version))
       (sha256
        (base32 "0sz0a1g6z48f0s7ch86y9mvazwk4gdswjj179a13d0yjhy9rgpk0"))))
    (properties `((upstream-name . "dynRB")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-reshape2
                             r-rcolorbrewer
                             r-ggplot2
                             r-foreign
                             r-dplyr
                             r-corrplot))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dynRB")
    (synopsis "Dynamic Range Boxes")
    (description
     "Improves the concept of multivariate range boxes, which is highly susceptible
for outliers and does not consider the distribution of the data.  The package
uses dynamic range boxes to overcome these problems.")
    (license license:gpl2)))

(define-public r-dynr
  (package
    (name "r-dynr")
    (version "0.1.16-105")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynr" version))
       (sha256
        (base32 "0s9n62k9cghvqgcpgingcvni3fzq2d9lrnj48i92kb25165446wm"))))
    (properties `((upstream-name . "dynr")))
    (build-system r-build-system)
    (inputs (list gsl))
    (propagated-inputs (list r-xtable
                             r-tibble
                             r-stringi
                             r-reshape2
                             r-rdpack
                             r-plyr
                             r-numderiv
                             r-mice
                             r-matrix
                             r-mass
                             r-magrittr
                             r-latex2exp
                             r-ggplot2
                             r-fda
                             r-desolve
                             r-car))
    (native-inputs (list r-knitr))
    (home-page "https://dynrr.github.io/")
    (synopsis "Dynamic Models with Regime-Switching")
    (description
     "Intensive longitudinal data have become increasingly prevalent in various
scientific disciplines.  Many such data sets are noisy, multivariate, and
multi-subject in nature.  The change functions may also be continuous, or
continuous but interspersed with periods of discontinuities (i.e., showing
regime switches).  The package dynr (Dynamic Modeling in R) is an R package that
implements a set of computationally efficient algorithms for handling a broad
class of linear and nonlinear discrete- and continuous-time models with
regime-switching properties under the constraint of linear Gaussian measurement
functions.  The discrete-time models can generally take on the form of a
state-space or difference equation model.  The continuous-time models are
generally expressed as a set of ordinary or stochastic differential equations.
All estimation and computations are performed in C, but users are provided with
the option to specify the model of interest via a set of simple and
easy-to-learn model specification functions in R. Model fitting can be performed
using single-subject time series data or multiple-subject longitudinal data.
Ou, Hunter, & Chow (2019) <doi:10.32614%2FRJ-2019-012> provided a detailed
introduction to the interface and more information on the algorithms.")
    (license license:gpl3)))

(define-public r-dynprog
  (package
    (name "r-dynprog")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynprog" version))
       (sha256
        (base32 "11zsx2c4hv7k22pw85aa01zk4r0qpzwnf73ynylkfxfbi87rda9s"))))
    (properties `((upstream-name . "dynprog")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang))
    (home-page "https://github.com/mailund/dynprog")
    (synopsis "Dynamic Programming Domain-Specific Language")
    (description
     "This package provides a domain-specific language for specifying translating
recursions into dynamic-programming algorithms.  See
<https://en.wikipedia.org/wiki/Dynamic_programming> for a description of dynamic
programming.")
    (license license:gpl3)))

(define-public r-dynpred
  (package
    (name "r-dynpred")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynpred" version))
       (sha256
        (base32 "111ykasaiznn3431msj4flfhmjvzq7dd1mnzn1wklc5ndix1pvf9"))))
    (properties `((upstream-name . "dynpred")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival))
    (home-page "http://www.msbi.nl/putter")
    (synopsis
     "Companion Package to \"Dynamic Prediction in Clinical Survival Analysis\"")
    (description
     "The dynpred package contains functions for dynamic prediction in survival
analysis.")
    (license license:gpl2+)))

(define-public r-dynparam
  (package
    (name "r-dynparam")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynparam" version))
       (sha256
        (base32 "12cclb8r13gn407197sw5gx2vfd0qc69mp16jam9chybxbj3pvx0"))))
    (properties `((upstream-name . "dynparam")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-purrr
                             r-magrittr
                             r-dynutils
                             r-dplyr
                             r-carrier
                             r-assertthat))
    (home-page "https://github.com/dynverse/dynparam")
    (synopsis "Creating Meta-Information for Parameters")
    (description
     "This package provides tools for describing parameters of algorithms in an
abstract way.  Description can include an id, a description, a domain (range or
list of values), and a default value.  dynparam can also convert parameter sets
to a @code{ParamHelpers} format, in order to be able to use dynparam in
conjunction with @code{mlrMBO}'.")
    (license license:expat)))

(define-public r-dynpanel
  (package
    (name "r-dynpanel")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynpanel" version))
       (sha256
        (base32 "073kfl5g4d7v8wd2qnpixqrxbac3cqj35z03ax2zlb8h2afa7j62"))))
    (properties `((upstream-name . "dynpanel")))
    (build-system r-build-system)
    (propagated-inputs (list r-gtools))
    (home-page "https://cran.r-project.org/package=dynpanel")
    (synopsis "Dynamic Panel Data Models")
    (description
     "Computes the first stage GMM estimate of a dynamic linear model with p lags of
the dependent variables.")
    (license license:gpl3)))

(define-public r-dynnom
  (package
    (name "r-dynnom")
    (version "5.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DynNom" version))
       (sha256
        (base32 "0nc1dw5ihqm819na1dd85v4wlpidvp5yk50rrsyp0labm8nkh0qv"))))
    (properties `((upstream-name . "DynNom")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-stargazer
                             r-shiny
                             r-rms
                             r-plotly
                             r-magrittr
                             r-ggplot2
                             r-dplyr
                             r-compare
                             r-broom
                             r-bbmisc))
    (home-page "https://cran.r-project.org/package=DynNom")
    (synopsis "Visualising Statistical Models using Dynamic Nomograms")
    (description
     "Demonstrate the results of a statistical model object as a dynamic nomogram in
an RStudio panel or web browser.  The package provides two generics functions:
@code{DynNom}, which display statistical model objects as a dynamic nomogram;
DNbuilder, which builds required scripts to publish a dynamic nomogram on a web
server such as the <https://www.shinyapps.io/>.  Current version of
@code{DynNom} supports stats::lm, stats::glm, survival::coxph, rms::ols,
rms::Glm, rms::lrm, rms::cph, and mgcv::gam model objects.")
    (license license:gpl2)))

(define-public r-dynmix
  (package
    (name "r-dynmix")
    (version "2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynmix" version))
       (sha256
        (base32 "09mm2k6p6vmj5ab9a0gzm7wqf35righ78c8sabnlk9d1wwxs4s70"))))
    (properties `((upstream-name . "dynmix")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-rcpparmadillo r-rcpp r-mass))
    (home-page "https://CRAN.R-project.org/package=dynmix")
    (synopsis "Estimation of Dynamic Finite Mixtures")
    (description
     "Allows to perform the dynamic mixture estimation with state-space components and
normal regression components, and clustering with normal mixture.
Quasi-Bayesian estimation, as well as, that based on the Kerridge inaccuracy
approximation are implemented.  Main references: Nagy and Suzdaleva (2013)
<doi:10.1016/j.apm.2013.05.038>; Nagy et al. (2011) <doi:10.1002/acs.1239>.")
    (license license:gpl3)))

(define-public r-dynlm
  (package
    (name "r-dynlm")
    (version "0.3-6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynlm" version))
       (sha256
        (base32 "1g8qsb5m69yn35sm0shd97vbnbpqfkjkd7lbkwch1gpfxkld53zq"))))
    (properties `((upstream-name . "dynlm")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-lmtest r-car))
    (home-page "https://cran.r-project.org/package=dynlm")
    (synopsis "Dynamic Linear Regression")
    (description "Dynamic linear models and time series regression.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-dynforest
  (package
    (name "r-dynforest")
    (version "1.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DynForest" version))
       (sha256
        (base32 "0x78gbgzl4dad5g6w27cdfpngsykanv3lz3xffpqndd971wkzhiy"))))
    (properties `((upstream-name . "DynForest")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-survival
                             r-stringr
                             r-prodlim
                             r-pec
                             r-pbapply
                             r-lcmm
                             r-ggplot2
                             r-foreach
                             r-dorng
                             r-doparallel
                             r-desctools
                             r-cmprsk))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/anthonydevaux/DynForest")
    (synopsis "Random Forest with Multivariate Longitudinal Predictors")
    (description
     "Based on random forest principle, @code{DynForest} is able to include multiple
longitudinal predictors to provide individual predictions.  Longitudinal
predictors are modeled through the random forest.  The methodology is fully
described for a survival outcome in: Devaux, Helmer, Genuer & Proust-Lima (2023)
<doi: 10.1177/09622802231206477>.")
    (license license:lgpl3+)))

(define-public r-dynetnlaresistance
  (package
    (name "r-dynetnlaresistance")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynetNLAResistance" version))
       (sha256
        (base32 "018y3m648ni31rlisjfnrx1d10mm48wpxanlnnxxpnqxjcywg2x8"))))
    (properties `((upstream-name . "dynetNLAResistance")))
    (build-system r-build-system)
    (propagated-inputs (list r-igraph r-foreach r-doparallel))
    (home-page "https://cran.r-project.org/package=dynetNLAResistance")
    (synopsis "Resisting Neighbor Label Attack in a Dynamic Network")
    (description
     "An anonymization algorithm to resist neighbor label attack in a dynamic network.")
    (license license:expat)))

(define-public r-dyndimred
  (package
    (name "r-dyndimred")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dyndimred" version))
       (sha256
        (base32 "1rj45bgms1x0zm1xjw2ylm45w9xnd68pmgb8dckzkszqg27d0fbh"))))
    (properties `((upstream-name . "dyndimred")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-lmds r-irlba r-dynutils))
    (home-page "https://github.com/dynverse/dyndimred")
    (synopsis "Dimensionality Reduction Methods in a Common Format")
    (description
     "This package provides a common interface for applying dimensionality reduction
methods, such as Principal Component Analysis ('PCA'), Independent Component
Analysis ('ICA'), diffusion maps, Locally-Linear Embedding ('LLE'),
t-distributed Stochastic Neighbor Embedding ('t-SNE'), and Uniform Manifold
Approximation and Projection ('UMAP').  Has built-in support for sparse
matrices.")
    (license license:expat)))

(define-public r-dyncorr
  (package
    (name "r-dyncorr")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynCorr" version))
       (sha256
        (base32 "0l5k764j1zhsqpgp0ndihah63hsk3zv9hviixfmh4h3i0sr0q52p"))))
    (properties `((upstream-name . "dynCorr")))
    (build-system r-build-system)
    (propagated-inputs (list r-lpridge))
    (home-page "https://cran.r-project.org/package=dynCorr")
    (synopsis "Dynamic Correlation Package")
    (description
     "Computes dynamical correlation estimates and percentile bootstrap confidence
intervals for pairs of longitudinal responses, including consideration of lags
and derivatives.")
    (license license:gpl2)))

(define-public r-dynconfir
  (package
    (name "r-dynconfir")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynConfiR" version))
       (sha256
        (base32 "1ql8c712g7jx0j1aw7qrfsp81abiajigzvwwlq6v96ar5ag5jrgy"))))
    (properties `((upstream-name . "dynConfiR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-rcpp
                             r-progress
                             r-minqa
                             r-magrittr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/SeHellmann/dynConfiR")
    (synopsis "Dynamic Models for Confidence and Response Time Distributions")
    (description
     "This package provides density functions for the joint distribution of choice,
response time and confidence for discrete confidence judgments as well as
functions for parameter fitting, prediction and simulation for various dynamical
models of decision confidence.  All models are explained in detail by Hellmann
et al. (2023; Preprint available at <https://osf.io/9jfqr/>, published version:
<doi:10.1037/rev0000411>).  Implemented models are the @code{dynaViTE} model,
@code{dynWEV} model, the 2DSD model (Pleskac & Busemeyer, 2010,
<doi:10.1037/a0019737>), and various race models.  C++ code for @code{dynWEV}
and 2DSD is based on the rtdists package by Henrik Singmann.")
    (license license:gpl3+)))

(define-public r-dyncomp
  (package
    (name "r-dyncomp")
    (version "0.0.2-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dyncomp" version))
       (sha256
        (base32 "13wp2k8nbgrbrqng2dmgy0ixgidk51wq9y7mv5pdbvdajxdsyh11"))))
    (properties `((upstream-name . "dyncomp")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo))
    (home-page "https://cran.r-project.org/package=dyncomp")
    (synopsis "Complexity of Short and Coarse-Grained Time Series")
    (description
     "While there are many well-established measures for identifying critical
fluctuations and phase transitions, these measures only work with many points of
measurement and thus are unreliable when studying short and coarse-grained time
series.  This package provides a measure for complexity in a time series that
does not rely on long time series (Kaiser (2017), <doi:10.17605/OSF.IO/GWTKX>).")
    (license license:expat)))

(define-public r-dynclust
  (package
    (name "r-dynclust")
    (version "3.24")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DynClust" version))
       (sha256
        (base32 "0nbbzx0ixblpcbjxx0gp7082nz6nh5vc2l5nzdfq1mqzlq9jy2xn"))))
    (properties `((upstream-name . "DynClust")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DynClust")
    (synopsis
     "Denoising and Clustering for Dynamical Image Sequence (2D or 3D)+t")
    (description
     "This package provides a two-stage procedure for the denoising and clustering of
stack of noisy images acquired over time.  Clustering only assumes that the data
contain an unknown but small number of dynamic features.  The method first
denoises the signals using local spatial and full temporal information.  The
clustering step uses the previous output to aggregate voxels based on the
knowledge of their spatial neighborhood.  Both steps use a single keytool based
on the statistical comparison of the difference of two signals with the null
signal.  No assumption is therefore required on the shape of the signals.  The
data are assumed to be normally distributed (or at least follow a symmetric
distribution) with a known constant variance.  Working pixelwise, the method can
be time-consuming depending on the size of the data-array but harnesses the
power of multicore cpus.")
    (license license:expat)))

(define-public r-dynbiplotgui
  (package
    (name "r-dynbiplotgui")
    (version "1.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynBiplotGUI" version))
       (sha256
        (base32 "04026jz4vdyj2a2kry5kk5k84cy4vqqrcn328hxwnwh7r8i7klvn"))))
    (properties `((upstream-name . "dynBiplotGUI")))
    (build-system r-build-system)
    (inputs (list gnu-make))
    (propagated-inputs (list r-tcltk2))
    (home-page "https://cran.r-project.org/package=dynBiplotGUI")
    (synopsis "Full Interactive GUI for Dynamic Biplot in R")
    (description
     "This package provides a GUI to solve dynamic biplots and classical biplot.  Try
matrices of 2-way and 3-way.  The GUI can be run in multiple languages.")
    (license license:gpl2+)))

(define-public r-dynatree
  (package
    (name "r-dynatree")
    (version "1.2-17")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynaTree" version))
       (sha256
        (base32 "1w7z1qjyhhcymi9if1x8i8sniya642diwnvkf0qhwzan8scig1yj"))))
    (properties `((upstream-name . "dynaTree")))
    (build-system r-build-system)
    (home-page "https://bobby.gramacy.com/r_packages/dynaTree/")
    (synopsis "Dynamic Trees for Learning and Design")
    (description
     "Inference by sequential Monte Carlo for dynamic tree regression and
classification models with hooks provided for sequential design and
optimization, fully online learning with drift, variable selection, and
sensitivity analysis of inputs.  Illustrative examples from the original dynamic
trees paper (Gramacy, Taddy & Polson (2011); <doi:10.1198/jasa.2011.ap09769>)
are facilitated by demos in the package; see demo(package=\"@code{dynaTree}\").")
    (license license:lgpl2.0+)))

(define-public r-dynatopgis
  (package
    (name "r-dynatopgis")
    (version "0.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynatopGIS" version))
       (sha256
        (base32 "1sv519dc7fs6zrwnyggkzrcy866a6pgag0shk6rr6cd3xa1blwpv"))))
    (properties `((upstream-name . "dynatopGIS")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra r-r6 r-jsonlite))
    (native-inputs (list r-knitr))
    (home-page "https://waternumbers.github.io/dynatopGIS/")
    (synopsis
     "Algorithms for Helping Build Dynamic TOPMODEL Implementations from Spatial Data")
    (description
     "This package provides a set of algorithms based on Quinn et al. (1991)
<doi:10.1002/hyp.3360050106> for processing river network and digital elevation
data to build implementations of Dynamic TOPMODEL, a semi-distributed
hydrological model proposed in Beven and Freer (2001) <doi:10.1002/hyp.252>.
The dynatop package implements simulation code for Dynamic TOPMODEL based on the
output of @code{dynatopGIS}'.")
    (license license:gpl2)))

(define-public r-dynatop
  (package
    (name "r-dynatop")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynatop" version))
       (sha256
        (base32 "06wp8ld22k3r76imsj8wkrpplmbdlgbl71p94ddglwp8yfq1igsp"))))
    (properties `((upstream-name . "dynatop")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-xts r-rcpp r-r6))
    (native-inputs (list r-knitr))
    (home-page "https://waternumbers.github.io/dynatop/")
    (synopsis "An Implementation of Dynamic TOPMODEL Hydrological Model in R")
    (description
     "An R implementation and enhancement of the Dynamic TOPMODEL semi-distributed
hydrological model originally proposed by Beven and Freer (2001)
<doi:10.1002/hyp.252>.  The dynatop package implements code for simulating
models which can be created using the @code{dynatopGIS} package.")
    (license license:gpl2)))

(define-public r-dynate
  (package
    (name "r-dynate")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DYNATE" version))
       (sha256
        (base32 "172lm5k0hz774a0d2s1hs86q7q50s6n4i4ba8jddy3l5a1gqkpd4"))))
    (properties `((upstream-name . "DYNATE")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyverse
                             r-tibble
                             r-reshape2
                             r-matrix
                             r-dplyr
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DYNATE")
    (synopsis "Dynamic Aggregation Testing")
    (description
     "This package provides a multiple testing procedure aims to find the rare-variant
association regions.  When variants are rare, the single variant association
test approach suffers from low power.  To improve testing power, the procedure
dynamically and hierarchically aggregates smaller genome regions to larger ones
and performs multiple testing for disease associations with a controlled
node-level false discovery rate.  This method are members of the family of
ancillary information assisted recursive testing introduced in Pura, Li, Chan
and Xie (2021) <@code{arXiv:1906.07757v2>} and Li, Sung and Xie (2021)
<@code{arXiv:2103.11085v2>}.")
    (license license:gpl3)))

(define-public r-dynaspec
  (package
    (name "r-dynaspec")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynaSpec" version))
       (sha256
        (base32 "1mkc74jd25ydfl3ssl5kvcwjrvi6wdlm76v1m4sf4fm3vag37jyc"))))
    (properties `((upstream-name . "dynaSpec")))
    (build-system r-build-system)
    (inputs (list ffmpeg))
    (propagated-inputs (list r-warbler
                             r-viridis
                             r-tuner
                             r-seewave
                             r-scales
                             r-png
                             r-ggplot2
                             r-gganimate
                             r-ari))
    (home-page "https://github.com/maRce10/dynaSpec")
    (synopsis "Dynamic Spectrogram Visualizations")
    (description
     "This package provides a set of tools to generate dynamic spectrogram
visualizations in video format.")
    (license license:gpl2+)))

(define-public r-dynarer
  (package
    (name "r-dynarer")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DynareR" version))
       (sha256
        (base32 "0ph57kwinv9nqla82glg0bj1iaqrnw2y8a8invq1qy9yabldl798"))))
    (properties `((upstream-name . "DynareR")))
    (build-system r-build-system)
    (inputs (list octave))
    (propagated-inputs (list r-magrittr r-knitr))
    (native-inputs (list r-knitr))
    (home-page "https://CRAN.R-project.org/package=DynareR")
    (synopsis
     "Bringing the Power of 'Dynare' to 'R', 'R Markdown', and 'Quarto'")
    (description
     "It allows running Dynare program from base R, R Markdown and Quarto.  Dynare is
a software platform for handling a wide class of economic models, in particular
dynamic stochastic general equilibrium ('DSGE') and overlapping generations
('OLG') models.  This package does not only integrate R and Dynare but also
serves as a Dynare Knit-Engine for knitr package.  The package requires Dynare
(<https://www.dynare.org/>) and Octave (<https://www.octave.org/download.html>).
 Write all your Dynare commands in R or R Markdown chunk.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-dynarankr
  (package
    (name "r-dynarankr")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DynaRankR" version))
       (sha256
        (base32 "1fzicainh1dm016cglm2x6j1i2g5r71vgrj0dnsflbxc5v426sqm"))))
    (properties `((upstream-name . "DynaRankR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-dplyr))
    (home-page "https://github.com/straussed/DynaRankR")
    (synopsis "Inferring Longitudinal Dominance Hierarchies")
    (description
     "This package provides functions for inferring longitudinal dominance
hierarchies, which describe dominance relationships and their dynamics in a
single latent hierarchy over time.  Strauss & Holekamp (in press).")
    (license license:gpl2)))

(define-public r-dynamite
  (package
    (name "r-dynamite")
    (version "1.5.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynamite" version))
       (sha256
        (base32 "1gbhrswczs1lb7qwv2wgiapl5xax2z5indfmzvq8f4d45cd4wn2v"))))
    (properties `((upstream-name . "dynamite")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-rstan
                             r-rlang
                             r-posterior
                             r-patchwork
                             r-loo
                             r-glue
                             r-ggplot2
                             r-ggforce
                             r-data-table
                             r-cli
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/dynamite/")
    (synopsis
     "Bayesian Modeling and Causal Inference for Multivariate Longitudinal Data")
    (description
     "Easy-to-use and efficient interface for Bayesian inference of complex panel
(time series) data using dynamic multivariate panel models by Helske and Tikka
(2024) <doi:10.1016/j.alcr.2024.100617>.  The package supports joint modeling of
multiple measurements per individual, time-varying and time-invariant effects,
and a wide range of discrete and continuous distributions.  Estimation of these
dynamic multivariate panel models is carried out via Stan'.  For an in-depth
tutorial of the package, see (Tikka and Helske, 2024)
<doi:10.48550/@code{arXiv.2302.01607>}.")
    (license license:gpl3+)))

(define-public r-dynamicsdm
  (package
    (name "r-dynamicsdm")
    (version "1.3.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynamicSDM" version))
       (sha256
        (base32 "0126yj2qafg93jipkbszlwjcy20yxnd4adn8r5b7cwf5ipkp92mc"))))
    (properties `((upstream-name . "dynamicSDM")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-terra
                             r-sf
                             r-rgee
                             r-reticulate
                             r-readr
                             r-magrittr
                             r-lubridate
                             r-googledrive
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/r-a-dobson/dynamicSDM")
    (synopsis
     "Species Distribution and Abundance Modelling at High Spatio-Temporal Resolution")
    (description
     "This package provides a collection of novel tools for generating species
distribution and abundance models (SDM) that are dynamic through both space and
time.  These highly flexible functions incorporate spatial and temporal aspects
across key SDM stages; including when cleaning and filtering species occurrence
data, generating pseudo-absence records, assessing and correcting sampling
biases and autocorrelation, extracting explanatory variables and projecting
distribution patterns.  Throughout, functions utilise Google Earth Engine and
Google Drive to minimise the computing power and storage demands associated with
species distribution modelling at high spatio-temporal resolution.")
    (license license:gpl3+)))

(define-public r-dynamicgp
  (package
    (name "r-dynamicgp")
    (version "1.1-9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DynamicGP" version))
       (sha256
        (base32 "00hf3r39b9xid129kzgdnwdfrwrspxkz7dydgna3c5lrl7670paz"))))
    (properties `((upstream-name . "DynamicGP")))
    (build-system r-build-system)
    (propagated-inputs (list r-lhs))
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=DynamicGP")
    (synopsis "Modelling and Analysis of Dynamic Computer Experiments")
    (description
     "Emulating and solving inverse problems for dynamic computer experiments.  It
contains two major functionalities: (1) localized GP model for large-scale
dynamic computer experiments using the algorithm proposed by Zhang et al. (2018)
<@code{arXiv:1611.09488>}; (2) solving inverse problems in dynamic computer
experiments.  The current version only supports 64-bit version of R.")
    (license license:gpl2+)))

(define-public r-dynamic
  (package
    (name "r-dynamic")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynamic" version))
       (sha256
        (base32 "15jxly44rj2x79jvps2ln0hrm1384p56yll9jk96w1vhaf3gbsxm"))))
    (properties `((upstream-name . "dynamic")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-simstandard
                             r-purrr
                             r-patchwork
                             r-magrittr
                             r-lavaan
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/melissagwolf/dynamic")
    (synopsis "DFI Cutoffs for Latent Variable Models")
    (description
     "Returns dynamic fit index (DFI) cutoffs for latent variable models that are
tailored to the user's model statement, model type, and sample size.  This is
the counterpart of the Shiny Application, <https://dynamicfit.app>.")
    (license license:agpl3)))

(define-public r-dynamaedes
  (package
    (name "r-dynamaedes")
    (version "2.2.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynamAedes" version))
       (sha256
        (base32 "0dzr8wf00hwwnivqn73hcgdncx8jkka54fygiy6iz9b065ilcvqi"))))
    (properties `((upstream-name . "dynamAedes")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra
                             r-geosphere
                             r-foreach
                             r-drc
                             r-doparallel
                             r-abind))
    (native-inputs (list r-knitr))
    (home-page "https://mattmar.github.io/dynamAedes/")
    (synopsis
     "Unified Mechanistic Model for the Population Dynamics of Invasive Aedes Mosquitoes")
    (description
     "Generalised model for population dynamics of invasive Aedes mosquitoes.
Rationale and model structure are described here: Da Re et al. (2021)
<doi:10.1016/j.ecoinf.2020.101180> and Da Re et al. (2022)
<doi:10.1101/2021.12.21.473628>.")
    (license license:gpl2+)))

(define-public r-dynamac
  (package
    (name "r-dynamac")
    (version "0.1.12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dynamac" version))
       (sha256
        (base32 "0gggzhidn5z4g7pzqx1bg56prnh9krph65k3yj677qrff12abbx9"))))
    (properties `((upstream-name . "dynamac")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-lmtest))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/andyphilips/dynamac/")
    (synopsis "Dynamic Simulation and Testing for Single-Equation ARDL Models")
    (description
     "While autoregressive distributed lag (ARDL) models allow for extremely flexible
dynamics, interpreting substantive significance of complex lag structures
remains difficult.  This package is designed to assist users in dynamically
simulating and plotting the results of various ARDL models.  It also contains
post-estimation diagnostics, including a test for cointegration when estimating
the error-correction variant of the autoregressive distributed lag model
(Pesaran, Shin, and Smith 2001 <doi:10.1002/jae.616>).")
    (license license:gpl2+)))

(define-public r-dyn-log
  (package
    (name "r-dyn-log")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dyn.log" version))
       (sha256
        (base32 "0vlzv6zy29qhygm77kww65wpnp77a93ja13vr4p2yyychrjspqx3"))))
    (properties `((upstream-name . "dyn.log")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-stringr
                             r-rlang
                             r-r6
                             r-glue
                             r-crayon))
    (native-inputs (list r-knitr))
    (home-page "https://bmoretz.github.io/dyn.log/")
    (synopsis
     "Dynamic Logging for R Inspired by Configuration Driven Development")
    (description
     "This package provides a comprehensive and dynamic configuration driven logging
package for R. While there are several excellent logging solutions already in
the R ecosystem, I always feel constrained in some way by each of them.  Every
project is designed differently to solve it's domain specific problem, and
ultimately the utility of a logging solution is its ability to adapt to this
design.  This is the raison d'Ãªtre for dyn.log': to provide a modular design,
template mechanics and a configuration-based integration model, so that the
logger can integrate deeply into your design, even though it knows nothing about
it.")
    (license license:expat)))

(define-public r-dymo
  (package
    (name "r-dymo")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dymo" version))
       (sha256
        (base32 "0s1gpi5qiafkf91awyx52qw15qs7m18bql51jibgh1lqnqgv1757"))))
    (properties `((upstream-name . "dymo")))
    (build-system r-build-system)
    (propagated-inputs (list r-tictoc
                             r-scales
                             r-readr
                             r-purrr
                             r-narray
                             r-moments
                             r-modeest
                             r-matlib
                             r-mass
                             r-lubridate
                             r-imputets
                             r-greybox
                             r-ggplot2
                             r-fancova))
    (home-page "https://rpubs.com/giancarlo_vercellino/dymo")
    (synopsis
     "Dynamic Mode Decomposition for Multivariate Time Feature Prediction")
    (description
     "An application of Dynamic Mode Decomposition for prediction of time features.
Automatic search for the best model across the space of all possible feature
combinations and ranks of Singular Value Decomposition.")
    (license license:gpl3)))

(define-public r-dymep
  (package
    (name "r-dymep")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DyMEP" version))
       (sha256
        (base32 "1jy2yrdih4c1c2d04qnx0z6m466djh91i5cpcbr23rbz0rqf2ig9"))))
    (properties `((upstream-name . "DyMEP")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DyMEP")
    (synopsis "Dynamic Multi Environment Phenology-Model")
    (description
     "Mechanistically models/predicts the phenology (macro-phases) of 10 crop plants
(trained on a big dataset over 80 years derived from the German weather service
(DWD) <https://opendata.dwd.de/>).  Can be applied for remote sensing purposes,
dynamically check the best subset of available covariates for the given dataset
and crop.")
    (license license:lgpl3+)))

(define-public r-dym
  (package
    (name "r-dym")
    (version "0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DYM" version))
       (sha256
        (base32 "1rk0xs224xi68f0mrygny2rklggl4grk866q7y9xck38bwy7aw94"))))
    (properties `((upstream-name . "DYM")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DYM")
    (synopsis "Did You Mean?")
    (description
     "Add a \"Did You Mean\" feature to the R interactive.  With this package, error
messages for misspelled input of variable names or package names suggest what
you really want to do in addition to notification of the mistake.")
    (license license:bsd-3)))

(define-public r-dykstra
  (package
    (name "r-dykstra")
    (version "1.0-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Dykstra" version))
       (sha256
        (base32 "1rc1409ky0ysqr3ccq28yhbs94m6d0z2dfa66k4c7irxjvbagwz6"))))
    (properties `((upstream-name . "Dykstra")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=Dykstra")
    (synopsis "Quadratic Programming using Cyclic Projections")
    (description
     "Solves quadratic programming problems using Richard L. Dykstra's cyclic
projection algorithm.  Routine allows for a combination of equality and
inequality constraints.  See Dykstra (1983) <doi:10.1080/01621459.1983.10477029>
for details.")
    (license license:gpl2+)))

(define-public r-dydea
  (package
    (name "r-dydea")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dydea" version))
       (sha256
        (base32 "15alr3f6wkkpjd5wmcjazi58yc8gwcqr662mjwlfg15r94fzqrlg"))))
    (properties `((upstream-name . "dydea")))
    (build-system r-build-system)
    (propagated-inputs (list r-chaos01))
    (home-page "https://cran.r-project.org/package=dydea")
    (synopsis "Detection of Chaotic and Regular Intervals in the Data")
    (description
     "Finds regular and chaotic intervals in the data using the 0-1 test for chaos
proposed by Gottwald and Melbourne (2004) <DOI:10.1137/080718851>.")
    (license license:gpl3)))

(define-public r-dycdtools
  (package
    (name "r-dycdtools")
    (version "0.4.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dycdtools" version))
       (sha256
        (base32 "0c5ds2bnnv08c68hyxr4p4p6h9cc2pbivgyyqglaz23317rcxlcp"))))
    (properties `((upstream-name . "dycdtools")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rcolorbrewer
                             r-r-utils
                             r-ncdf4
                             r-lubridate
                             r-ggplot2
                             r-dplyr))
    (home-page "https://github.com/SongyanYu/dycdtools")
    (synopsis
     "Calibration Assistant and Post-Processing Tool for Aquatic Ecosystem Model DYRESM-CAEDYM")
    (description
     "Dynamic Reservoir Simulation Model (DYRESM) and Computational Aquatic Ecosystem
Dynamics Model (CAEDYM) model development, including assisting with calibrating
selected model parameters and visualising model output through time series plot,
profile plot, contour plot, and scatter plot.  For more details, see Yu et al.
(2023) <https://journal.r-project.org/articles/RJ-2023-008/>.")
    (license license:expat)))

(define-public r-dyads
  (package
    (name "r-dyads")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dyads" version))
       (sha256
        (base32 "0nx4gx51p0qz1565yn7xg0ijrkqvn9ql9hrmp5lwl4lxvsjnwki1"))))
    (properties `((upstream-name . "dyads")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfast r-rcppziggurat r-mvtnorm r-mass
                             r-cholwishart))
    (home-page "https://cran.r-project.org/package=dyads")
    (synopsis "Dyadic Network Analysis")
    (description
     "This package contains functions for the MCMC simulation of dyadic network models
j2 (Zijlstra, 2017, <doi:10.1080/0022250X.2017.1387858>) and p2 (Van Duijn,
Snijders & Zijlstra, 2004, <doi: 10.1046/j.0039-0402.2003.00258.x>), the
multilevel p2 model (Zijlstra, Van Duijn & Snijders (2009) <doi:
10.1348/000711007X255336>), and the bidirectional (multilevel) counterpart of
the the multilevel p2 model as described in Zijlstra, Van Duijn & Snijders
(2009) <doi: 10.1348/000711007X255336>, the (multilevel) b2 model.")
    (license license:gpl2+)))

(define-public r-dwreg
  (package
    (name "r-dwreg")
    (version "2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DWreg" version))
       (sha256
        (base32 "0bgahzgcxz86n0ady97l48zyahv3p2iyc2ivbij1xrfx3wcx3b5n"))))
    (properties `((upstream-name . "DWreg")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-maxlik r-ecdat r-discreteweibull))
    (home-page "https://cran.r-project.org/package=DWreg")
    (synopsis "Parametric Regression for Discrete Response")
    (description
     "Regression for a discrete response, where the conditional distribution is
modelled via a discrete Weibull distribution.")
    (license license:gpl2+)))

(define-public r-dwp
  (package
    (name "r-dwp")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dwp" version))
       (sha256
        (base32 "1a70lxw4ck3pbklyibn8x6qpgj16zvawi76qqc9rnc26q2n5zp6j"))))
    (properties `((upstream-name . "dwp")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam
                             r-statmod
                             r-sf
                             r-pracma
                             r-plotrix
                             r-numderiv
                             r-mvtnorm
                             r-matrixstats
                             r-mass
                             r-magrittr
                             r-invgamma
                             r-gtools
                             r-genest
                             r-expint
                             r-boot))
    (home-page "https://cran.r-project.org/package=dwp")
    (synopsis "Density-Weighted Proportion")
    (description
     "Fit a Poisson regression to carcass distance data and integrate over the
searched area at a wind farm to estimate the fraction of carcasses falling in
the searched area and format the output for use as the dwp parameter in the
@code{GenEst} or eoa package for estimating bird and bat mortality, following
Dalthorp, et al. (2022) <@code{arXiv:2201.10064>}.")
    (license license:cc0)))

(define-public r-dwls
  (package
    (name "r-dwls")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DWLS" version))
       (sha256
        (base32 "02fd5q91shwjzc6bxqv4m8al7q1vl0mah6niymij37p69wlixy42"))))
    (properties `((upstream-name . "DWLS")))
    (build-system r-build-system)
    (propagated-inputs (list r-varhandle
                             r-summarizedexperiment
                             r-seurat
                             r-rocr
                             r-reshape
                             r-quadprog
                             r-mast
                             r-e1071
                             r-dplyr))
    (home-page "https://github.com/sistia01/DWLS")
    (synopsis
     "Gene Expression Deconvolution Using Dampened Weighted Least Squares")
    (description
     "The rapid development of single-cell transcriptomic technologies has helped
uncover the cellular heterogeneity within cell populations.  However, bulk
RNA-seq continues to be the main workhorse for quantifying gene expression
levels due to technical simplicity and low cost.  To most effectively extract
information from bulk data given the new knowledge gained from single-cell
methods, we have developed a novel algorithm to estimate the cell-type
composition of bulk data from a single-cell RNA-seq-derived cell-type signature.
 Comparison with existing methods using various real RNA-seq data sets indicates
that our new approach is more accurate and comprehensive than previous methods,
especially for the estimation of rare cell types.  More importantly,our method
can detect cell-type composition changes in response to external perturbations,
thereby providing a valuable, cost-effective method for dissecting the
cell-type-specific effects of drug treatments or condition changes.  As such,
our method is applicable to a wide range of biological and clinical
investigations.  Dampened weighted least squares ('DWLS') is an estimation
method for gene expression deconvolution, in which the cell-type composition of
a bulk RNA-seq data set is computationally inferred.  This method corrects
common biases towards cell types that are characterized by highly expressed
genes and/or are highly prevalent, to provide accurate detection across diverse
cell types.  See: <https://www.nature.com/articles/s41467-019-10802-z.pdf> for
more information about the development of DWLS and the methods behind our
functions.")
    (license license:gpl2)))

(define-public r-dwlm
  (package
    (name "r-dwlm")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dwlm" version))
       (sha256
        (base32 "0n5dil9qvyy4gish3wnv8bzq0ci1p0dr2vmbbadl29jl7rd1v0rc"))))
    (properties `((upstream-name . "dwlm")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dwlm")
    (synopsis "Doubly Weighted Linear Model")
    (description
     "This linear model solution is useful when both predictor and response have
associated uncertainty.  The doubly weights linear model solution is invariant
on which quantity is used as predictor or response.  Based on the results by
Reed(1989) <doi:10.1119/1.15963> and Ripley & Thompson(1987)
<doi:10.1039/AN9871200377>.")
    (license license:gpl2+)))

(define-public r-dwlasso
  (package
    (name "r-dwlasso")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DWLasso" version))
       (sha256
        (base32 "1i8j8wjfvg69ldr8ahz1zv3m2wgxd701iph94ad22zs9qwqfg16z"))))
    (properties `((upstream-name . "DWLasso")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-hglasso r-glmnet))
    (home-page "https://cran.r-project.org/package=DWLasso")
    (synopsis "Degree Weighted Lasso")
    (description
     "This package infers networks with hubs using degree weighted Lasso method.")
    (license license:gpl2)))

(define-public r-dwdradar
  (package
    (name "r-dwdradar")
    (version "0.2.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dwdradar" version))
       (sha256
        (base32 "0dwnyzzha8bz6pzacak909hp65jmf1l3wby9vg62gp7rwlr1gbaj"))))
    (properties `((upstream-name . "dwdradar")))
    (build-system r-build-system)
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=dwdradar")
    (synopsis "Read Binary Radar Files from 'DWD' (German Weather Service)")
    (description
     "The DWD provides gridded radar data for Germany in binary format.  dwdradar
reads these files and enables a fast conversion into numerical format.")
    (license license:gpl2+)))

(define-public r-dwdlarger
  (package
    (name "r-dwdlarger")
    (version "0.2-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DWDLargeR" version))
       (sha256
        (base32 "03i3gycbmxpikqqqhchprm2qji5dgjbvm3ggvmgyc1vh5ap075by"))))
    (properties `((upstream-name . "DWDLargeR")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix))
    (home-page "https://arxiv.org/pdf/1604.05473")
    (synopsis
     "Fast Algorithms for Large Scale Generalized Distance Weighted Discrimination")
    (description
     "Solving large scale distance weighted discrimination.  The main algorithm is a
symmetric Gauss-Seidel based alternating direction method of multipliers (ADMM)
method.  See Lam, X.Y., Marron, J.S., Sun, D.F., and Toh, K.C. (2018)
<doi:10.48550/@code{arXiv.1604.05473>} for more details.")
    (license license:gpl2)))

(define-public r-dwctaxon
  (package
    (name "r-dwctaxon")
    (version "2.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dwctaxon" version))
       (sha256
        (base32 "0ypdfqnf70ylbrd1r8kpb531cd08izmqhsz84yxzw6xfyiqa6657"))))
    (properties `((upstream-name . "dwctaxon")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-settings
                             r-rlang
                             r-purrr
                             r-glue
                             r-dplyr
                             r-digest
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/dwctaxon/")
    (synopsis "Edit and Validate Darwin Core Taxon Data")
    (description
     "Edit and validate taxonomic data in compliance with Darwin Core standards
(Darwin Core Taxon class <https://dwc.tdwg.org/terms/#taxon>).")
    (license license:expat)))

(define-public r-dvqcc
  (package
    (name "r-dvqcc")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dvqcc" version))
       (sha256
        (base32 "011mwdwh046wninfjdy00wxn312ykzn90nz9fz3l7c5cw9gzzfkg"))))
    (properties `((upstream-name . "dvqcc")))
    (build-system r-build-system)
    (propagated-inputs (list r-tsdyn r-ggplot2))
    (home-page "https://cran.r-project.org/package=dvqcc")
    (synopsis
     "Dynamic VAR - Based Control Charts for Batch Process Monitoring")
    (description
     "This package provides a set of control charts for batch processes based on the
VAR model.  The package contains the implementation of T2.var and W.var control
charts based on VAR model coefficients using the couple vectors theory.  In each
time-instant the VAR coefficients are estimated from a historical in-control
dataset and a decision rule is made for online classifying of a new batch data.
Those charts allow efficient online monitoring since the very first
time-instant.  The offline version is available too.  In order to evaluate the
chart's performance, this package contains functions to generate batch data for
offline and online monitoring.See in Danilo Marcondes Filho and Marcio Valk
(2020) <doi:10.1016/j.ejor.2019.12.038>.")
    (license license:gpl3)))

(define-public r-dvir
  (package
    (name "r-dvir")
    (version "3.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dvir" version))
       (sha256
        (base32 "1anqm4lfr911yzj3v9953b72y7mbvbm4x52vkblwzlnxznkhmcn4"))))
    (properties `((upstream-name . "dvir")))
    (build-system r-build-system)
    (propagated-inputs (list r-verbalisr
                             r-ribd
                             r-pedtools
                             r-pedprobr
                             r-pedfamilias
                             r-pbapply
                             r-forrel))
    (home-page "https://github.com/magnusdv/dvir")
    (synopsis "Disaster Victim Identification")
    (description
     "Joint DNA-based disaster victim identification (DVI), as described in Vigeland
and Egeland (2021) <doi:10.21203/rs.3.rs-296414/v1>.  Identification is
performed by optimising the joint likelihood of all victim samples and reference
individuals.  Individual identification probabilities, conditional on all
available information, are derived from the joint solution in the form of
posterior pairing probabilities.  dvir is part of the pedsuite collection of
packages for pedigree analysis.")
    (license license:gpl3)))

(define-public r-dvhmetrics
  (package
    (name "r-dvhmetrics")
    (version "0.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DVHmetrics" version))
       (sha256
        (base32 "0dxbjqiqhzjrv867qhxmqavzklq0j3qjv4qwdacyrq8faz82vhv7"))))
    (properties `((upstream-name . "DVHmetrics")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-reshape2 r-kernsmooth r-ggplot2 r-dt))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/dwoll/DVHmetrics/")
    (synopsis "Analyze Dose-Volume Histograms and Check Constraints")
    (description
     "Functionality for analyzing dose-volume histograms (DVH) in radiation oncology:
Read DVH text files, calculate DVH metrics as well as generalized equivalent
uniform dose (@code{gEUD}), biologically effective dose (BED), equivalent dose
in 2 Gy fractions (EQD2), normal tissue complication probability (NTCP), and
tumor control probability (TCP).  Show DVH diagrams, check and visualize quality
assurance constraints for the DVH. Includes web-based graphical user interface.")
    (license license:gpl2+)))

(define-public r-durga
  (package
    (name "r-durga")
    (version "2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Durga" version))
       (sha256
        (base32 "0iq29ga1cn5fnnj1b90pprqcldygmy695si0vq4pr8d59q029ah9"))))
    (properties `((upstream-name . "Durga")))
    (build-system r-build-system)
    (propagated-inputs (list r-vipor r-rcolorbrewer r-boot))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/KhanKawsar/EstimationPlot")
    (synopsis "Effect Size Estimation and Visualisation")
    (description
     "An easy-to-use yet powerful system for plotting grouped data effect sizes.
Various types of effect size can be estimated, then plotted together with a
representation of the original data.  Select from many possible data
representations (box plots, violin plots, raw data points etc.), and combine as
desired.  Durga plots are implemented in base R, so are compatible with base R
methods for combining plots, such as layout()'.  See Khan & @code{McLean} (2023)
<doi:10.1101/2023.02.06.526960>.")
    (license license:expat)))

(define-public r-dupree
  (package
    (name "r-dupree")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dupree" version))
       (sha256
        (base32 "0q8c0z1yhym20rhfjrc8n03gk458z0n8axx013rcwk1vc2zwk670"))))
    (properties `((upstream-name . "dupree")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringdist
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-lintr
                             r-dplyr))
    (home-page "https://github.com/russHyde/dupree")
    (synopsis "Identify Duplicated R Code in a Project")
    (description
     "Identifies code blocks that have a high level of similarity within a set of R
files.")
    (license license:expat)))

(define-public r-dupnodes
  (package
    (name "r-dupnodes")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dupNodes" version))
       (sha256
        (base32 "1697pcr27lix8vf1krq6vdby8dk53h0s14gcng1y5rdngrxav9nk"))))
    (properties `((upstream-name . "dupNodes")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-igraph))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dupNodes")
    (synopsis
     "Computes DNSLbetweenness, a Betweenness Measure that Includes Self-Loops")
    (description
     "Computes a new measure, DNSL betweenness, via the creation of a new graph from
an existing one, duplicating nodes with self-loops.  This betweenness centrality
does not drop this essential information.  Implements Merelo & Molinari (2024)
<doi:10.1007/s42001-023-00245-4>.")
    (license license:gpl3)))

(define-public r-dupir
  (package
    (name "r-dupir")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dupiR" version))
       (sha256
        (base32 "14krgg9fh63nyi3rchmrlggw7rykylc6b52cih87rl09x9zlgq17"))))
    (properties `((upstream-name . "dupiR")))
    (build-system r-build-system)
    (propagated-inputs (list r-plotrix))
    (home-page "https://cran.r-project.org/package=dupiR")
    (synopsis
     "Bayesian Inference from Count Data using Discrete Uniform Priors")
    (description
     "We consider a set of sample counts obtained by sampling arbitrary fractions of a
finite volume containing an homogeneously dispersed population of identical
objects.  This package implements a Bayesian derivation of the posterior
probability distribution of the population size using a binomial likelihood and
non-conjugate, discrete uniform priors under sampling with or without
replacement.  This can be used for a variety of statistical problems involving
absolute quantification under uncertainty.  See Comoglio et al. (2013)
<doi:10.1371/journal.pone.0074388>.")
    (license license:gpl2)))

(define-public r-dunlin
  (package
    (name "r-dunlin")
    (version "0.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dunlin" version))
       (sha256
        (base32 "10xfps9b2dxw4w6c5z5djsp7ssz1rnpccvnai471r1zppyv14hy7"))))
    (properties `((upstream-name . "dunlin")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-tibble
                             r-stringr
                             r-rlang
                             r-magrittr
                             r-glue
                             r-forcats
                             r-dplyr
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://insightsengineering.github.io/dunlin/")
    (synopsis "Preprocessing Tools for Clinical Trial Data")
    (description
     "This package provides a collection of functions to preprocess data and organize
them in a format amenable to use by chevron.")
    (license license:asl2.0)))

(define-public r-dundermifflin
  (package
    (name "r-dundermifflin")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dundermifflin" version))
       (sha256
        (base32 "0rp8p4ln92kfxkczl7vi9r2jhxb1ky203s02940cjjkczsphpcc1"))))
    (properties `((upstream-name . "dundermifflin")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi r-crayon))
    (home-page "https://cran.r-project.org/package=dundermifflin")
    (synopsis "The Office Quotes on-Demand")
    (description
     "This package provides functions to randomly select, return, and print quotes or
entire scenes from the American version of the show the Office.  Receive laughs
from one of of the greatest sitcoms of all time on demand.  Add these functions
to your .Rprofile to get a good laugh everytime you start a new R session.")
    (license license:expat)))

(define-public r-dummy
  (package
    (name "r-dummy")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dummy" version))
       (sha256
        (base32 "081a5h33gw6ym4isy91h6mcf247c2vsdygv9ll07a3mgjcjnk79p"))))
    (properties `((upstream-name . "dummy")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dummy")
    (synopsis
     "Automatic Creation of Dummies with Support for Predictive Modeling")
    (description
     "Efficiently create dummies of all factors and character vectors in a data frame.
 Support is included for learning the categories on one data set (e.g., a
training set) and deploying them on another (e.g., a test set).")
    (license license:gpl2+)))

(define-public r-dumbbell
  (package
    (name "r-dumbbell")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dumbbell" version))
       (sha256
        (base32 "0v0b4wbfskvcnzx10z9v4rf3mq8ccswz63pd6i1z7mggnwv38ps5"))))
    (properties `((upstream-name . "dumbbell")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyverse
                             r-tidyr
                             r-rstatix
                             r-rlang
                             r-ggplot2
                             r-dplyr
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/foocheung2/dumbbell")
    (synopsis "Displaying Changes Between Two Points Using Dumbbell Plots")
    (description "This package creates a Dumbbell Plot.")
    (license license:expat)))

(define-public r-duke
  (package
    (name "r-duke")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "duke" version))
       (sha256
        (base32 "04z7vcgdljp47grn1ppdj4acfs3gq7xmghyzj96wq1aisnh0777b"))))
    (properties `((upstream-name . "duke")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/aidangildea/duke")
    (synopsis "Creating a Color-Blind Friendly Duke Color Package")
    (description
     "Generates visualizations with Dukeâs official suite of colors in a color blind
friendly way.")
    (license license:expat)))

(define-public r-duckplyr
  (package
    (name "r-duckplyr")
    (version "0.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "duckplyr" version))
       (sha256
        (base32 "1lrg5prs6gy1iv6i5n970miafvz1jqnv6bzvw2lciszrj5d2a8ry"))))
    (properties `((upstream-name . "duckplyr")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-tidyselect
                             r-tibble
                             r-rlang
                             r-lifecycle
                             r-jsonlite
                             r-glue
                             r-duckdb
                             r-dplyr
                             r-dbi
                             r-collections
                             r-cli))
    (home-page "https://duckdblabs.github.io/duckplyr/")
    (synopsis "'DuckDB'-Backed Version of 'dplyr'")
    (description
     "This package provides a drop-in replacement for dplyr', powered by @code{DuckDB}
for performance.  Also defines a set of generics that provide a low-level
implementer's interface for the high-level user interface of dplyr'.")
    (license license:expat)))

(define-public r-duckduckr
  (package
    (name "r-duckduckr")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "duckduckr" version))
       (sha256
        (base32 "1wki8xvqp5hr27iafd9jbryl9faywfkdkpn0pa0afywbic39k2cm"))))
    (properties `((upstream-name . "duckduckr")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-crul))
    (home-page "https://github.com/dirkschumacher/duckduckr")
    (synopsis "Simple Client for the DuckDuckGo Instant Answer API")
    (description
     "Programmatic access to the @code{DuckDuckGo} Instant Answer API
<https://api.duckduckgo.com/api>.")
    (license license:expat)))

(define-public r-duckdbfs
  (package
    (name "r-duckdbfs")
    (version "0.0.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "duckdbfs" version))
       (sha256
        (base32 "0rp8w8slmy3sbm143z9qy18bfwpnzad8jfw6ylccf3dmryh9siab"))))
    (properties `((upstream-name . "duckdbfs")))
    (build-system r-build-system)
    (propagated-inputs (list r-glue
                             r-fs
                             r-duckdb
                             r-dplyr
                             r-dbplyr
                             r-dbi))
    (home-page "https://github.com/cboettig/duckdbfs")
    (synopsis
     "High Performance Remote File System, Database and 'Geospatial' Access Using 'duckdb'")
    (description
     "This package provides friendly wrappers for creating duckdb'-backed connections
to tabular datasets ('csv', parquet, etc) on local or remote file systems.  This
mimics the behaviour of \"open_dataset\" in the arrow package, but in addition to
S3 file system also generalizes to any list of http URLs.")
    (license license:expat)))

(define-public r-duckdb
  (package
    (name "r-duckdb")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "duckdb" version))
       (sha256
        (base32 "06scj60z277mhilhsq2b9mlcbryrwhqvph1rkd2rgpq231qarj3s"))))
    (properties `((upstream-name . "duckdb")))
    (build-system r-build-system)
    (propagated-inputs (list r-dbi))
    (home-page "https://r.duckdb.org/")
    (synopsis "DBI Package for the DuckDB Database Management System")
    (description
     "The @code{DuckDB} project is an embedded analytical data management system with
support for the Structured Query Language (SQL).  This package includes all of
@code{DuckDB} and an R Database Interface (DBI) connector.")
    (license license:expat)))

(define-public r-dub
  (package
    (name "r-dub")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dub" version))
       (sha256
        (base32 "066lzyk44380mf17vx4db4a3a4rs7zl85mj5hjg172khjbqnbixw"))))
    (properties `((upstream-name . "dub")))
    (build-system r-build-system)
    (home-page "https://github.com/egnha/dub")
    (synopsis "Unpacking Assignment for Lists via Pattern Matching")
    (description
     "This package provides an operator for assigning nested components of a list to
names via a concise pattern matching syntax.  This is especially convenient for
assigning individual names to the multiple values that a function may return in
the form of a list, and for extracting deeply nested list components.")
    (license license:expat)))

(define-public r-duawranglr
  (package
    (name "r-duawranglr")
    (version "0.6.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "duawranglr" version))
       (sha256
        (base32 "0hxmvyl81xlp3vv1w7462cjfa9hdz5lki0p5pn0ik7dv5aap3wbq"))))
    (properties `((upstream-name . "duawranglr")))
    (build-system r-build-system)
    (propagated-inputs (list r-readxl r-readr r-haven r-dplyr r-digest))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/btskinner/duawranglr")
    (synopsis "Securely Wrangle Dataset According to Data Usage Agreement")
    (description
     "Create shareable data sets from raw data files that contain protected elements.
Relying on master crosswalk files that list restricted variables, package
functions warn users about possible violations of data usage agreement and
prevent writing protected elements.")
    (license license:expat)))

(define-public r-dualtrees
  (package
    (name "r-dualtrees")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dualtrees" version))
       (sha256
        (base32 "02zwfvz4vb8ppyjggkn5483p7b12l3ah1swpgc7g3p94ii5hr0vy"))))
    (properties `((upstream-name . "dualtrees")))
    (build-system r-build-system)
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=dualtrees")
    (synopsis
     "Decimated and Undecimated 2D Complex Dual-Tree Wavelet Transform")
    (description
     "An implementation of the decimated two-dimensional complex dual-tree wavelet
transform as described in Kingsbury (1999) <doi:10.1098/rsta.1999.0447> and
Selesnick et al. (2005) <doi:10.1109/MSP.2005.1550194>.  Also includes the
undecimated version and spectral bias correction described in Nelson et al.
(2018) <doi:10.1007/s11222-017-9784-0>.  The code is partly based on the dtcwt
Python library.")
    (license license:expat)))

(define-public r-dualscale
  (package
    (name "r-dualscale")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dualScale" version))
       (sha256
        (base32 "0dw8vknkvb9qzmxw2xmwnpa1dlrqhx70j32q6dm5j1sxjyw2zx37"))))
    (properties `((upstream-name . "dualScale")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer
                             r-matrixcalc
                             r-matrix
                             r-glue
                             r-ggrepel
                             r-ggplot2
                             r-ff
                             r-eba))
    (home-page "https://cran.r-project.org/package=dualScale")
    (synopsis "Dual Scaling Analysis of Data")
    (description
     "Dual Scaling, developed by Professor Shizuhiko Nishisato (1994, ISBN:
0-9691785-3-6), is a fundamental technique in multivariate analysis used for
data scaling and correspondence analysis.  Its utility lies in its ability to
represent multidimensional data in a lower-dimensional space, making it easier
to visualize and understand underlying patterns in complex data.  This technique
has been implemented to handle various types of data, including Contingency and
Frequency data (CF), Multiple-Choice data (MC), Sorting data (SO),
Paired-Comparison data (PC), and Rank-Order data (RO), providing users with a
powerful tool to explore relationships between variables and observations in
various fields, from sociology to ecology, enabling deeper and more efficient
analysis of multivariate datasets.")
    (license license:agpl3+)))

(define-public r-dual
  (package
    (name "r-dual")
    (version "0.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dual" version))
       (sha256
        (base32 "08r2qz5rvsc3pjrc8rsks6r39w52n621mfg77yfnk4lc1vqn4y8d"))))
    (properties `((upstream-name . "dual")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dual")
    (synopsis "Automatic Differentiation with Dual Numbers")
    (description
     "Automatic differentiation is achieved by using dual numbers without providing
hand-coded gradient functions.  The output value of a mathematical function is
returned with the values of its exact first derivative (or gradient).  For more
details see Baydin, Pearlmutter, Radul, and Siskind (2018)
<https://jmlr.org/papers/volume18/17-468/17-468.pdf>.")
    (license license:gpl3)))

(define-public r-dtwumi
  (package
    (name "r-dtwumi")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTWUMI" version))
       (sha256
        (base32 "0pybgbfs2yp2ljbs0kra5z70x3llkiwdngp6cadgs3j9rar4vq4q"))))
    (properties `((upstream-name . "DTWUMI")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlist
                             r-lsa
                             r-entropy
                             r-e1071
                             r-dtwbi
                             r-dtw))
    (home-page "http://mawenzi.univ-littoral.fr/DTWUMI/")
    (synopsis
     "Imputation of Multivariate Time Series Based on Dynamic Time Warping")
    (description
     "This package provides functions to impute large gaps within multivariate time
series based on Dynamic Time Warping methods.  Gaps of size 1 or inferior to a
defined threshold are filled using simple average and weighted moving average
respectively.  Larger gaps are filled using the methodology provided by Phan et
al. (2017) <DOI:10.1109/MLSP.2017.8168165>: a query is built immediately
before/after a gap and a moving window is used to find the most similar sequence
to this query using Dynamic Time Warping.  To lower the calculation time,
similar sequences are pre-selected using global features.  Contrary to the
univariate method (package DTWBI'), these global features are not estimated over
the sequence containing the gap(s), but a feature matrix is built to summarize
general features of the whole multivariate signal.  Once the most similar
sequence to the query has been identified, the adjacent sequence to this window
is used to fill the gap considered.  This function can deal with multiple gaps
over all the sequences componing the input multivariate signal.  However, for
better consistency, large gaps at the same location over all sequences should be
avoided.")
    (license license:gpl2+)))

(define-public r-dtwrappers2
  (package
    (name "r-dtwrappers2")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTwrappers2" version))
       (sha256
        (base32 "06dz7i5hddqwj307fmkp93v7c4r0nvbi3bi9j4hqx77z7bdy2m8j"))))
    (properties `((upstream-name . "DTwrappers2")))
    (build-system r-build-system)
    (propagated-inputs (list r-dtwrappers r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DTwrappers2")
    (synopsis "Extensions of 'DTwrappers'")
    (description
     "Offers functionality which provides methods for data analyses and cleaning that
can be flexibly applied across multiple variables and in groups.  These include
cleaning accidental text, contingent calculations, counting missing data, and
building summarizations of the data.")
    (license license:gpl3)))

(define-public r-dtwrappers
  (package
    (name "r-dtwrappers")
    (version "0.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTwrappers" version))
       (sha256
        (base32 "028n1211h9gmv050xfiw347x59gykb6ndvd371fdf53bbkqirqa4"))))
    (properties `((upstream-name . "DTwrappers")))
    (build-system r-build-system)
    (propagated-inputs (list r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DTwrappers")
    (synopsis
     "Simplified Data Analysis with Wrapper Functions for the 'Data.Table' Package")
    (description
     "This package provides functionality for users who are learning R or the
techniques of data analysis.  Written as a collection of wrapper functions, the
DTwrapper package facilitates many core operations of data processing.  This is
achieved with relatively few requirements about the order of the processing
steps or knowledge of specialized syntax.  DTwrappers creates coding results
along with translations to data.table's code.  This enables users to benefit
from the speed and efficiency of data.table's calculations.  Furthermore, the
package also provides the translated code for educational purposes so that users
can review working examples of coding syntax and calculations.")
    (license license:gpl3)))

(define-public r-dtwbi
  (package
    (name "r-dtwbi")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTWBI" version))
       (sha256
        (base32 "06lp4yc5nhacrgic78l014g2w1ibwgs8dp8zrahk5aripaczl25y"))))
    (properties `((upstream-name . "DTWBI")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlist r-lsa r-entropy r-e1071 r-dtw))
    (home-page "http://mawenzi.univ-littoral.fr/DTWBI/")
    (synopsis "Imputation of Time Series Based on Dynamic Time Warping")
    (description
     "This package provides functions to impute large gaps within time series based on
Dynamic Time Warping methods.  It contains all required functions to create
large missing consecutive values within time series and to fill them, according
to the paper Phan et al. (2017), <DOI:10.1016/j.patrec.2017.08.019>.
Performance criteria are added to compare similarity between two signals (query
and reference).")
    (license license:gpl2+)))

(define-public r-dtts
  (package
    (name "r-dtts")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dtts" version))
       (sha256
        (base32 "0n13q14a4vhfx6jvjg4zbch0874agfm8z5mlwzvpvh4vc5rcc4bk"))))
    (properties `((upstream-name . "dtts")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppdate
                             r-rcppcctz
                             r-rcpp
                             r-nanotime
                             r-data-table
                             r-bit64))
    (home-page "https://cran.r-project.org/package=dtts")
    (synopsis "'data.table' Time-Series")
    (description
     "High-frequency time-series support via nanotime and data.table'.")
    (license license:gpl2+)))

(define-public r-dttr2
  (package
    (name "r-dttr2")
    (version "0.5.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dttr2" version))
       (sha256
        (base32 "1fh154phspzwkx8mqk5v1xfq93z6x15kqv7s5xm7ky2rj27wdmin"))))
    (properties `((upstream-name . "dttr2")))
    (build-system r-build-system)
    (propagated-inputs (list r-lifecycle r-hms r-chk))
    (home-page "https://github.com/poissonconsulting/dttr2")
    (synopsis "Manipulate Date, POSIXct and hms Vectors")
    (description
     "Manipulates date ('Date'), date time ('POSIXct') and time ('hms') vectors.
Date/times are considered discrete and are floored whenever encountered.  Times
are wrapped and time zones are maintained unless explicitly altered by the user.")
    (license license:expat)))

(define-public r-dtsg
  (package
    (name "r-dtsg")
    (version "1.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTSg" version))
       (sha256
        (base32 "0gln3zliljhs7rmqbyi7nbrzknc4g7psk9rwnd5xh020fa2k2cm1"))))
    (properties `((upstream-name . "DTSg")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6 r-data-table r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://gisler.github.io/DTSg/")
    (synopsis
     "Class for Working with Time Series Data Based on 'data.table' and 'R6' with Largely Optional Reference Semantics")
    (description
     "Basic time series functionalities such as listing of missing values, application
of arbitrary aggregation as well as rolling (asymmetric) window functions and
automatic detection of periodicity.  As it is mainly based on data.table', it is
fast and (in combination with the R6 package) offers reference semantics.  In
addition to its native R6 interface, it provides an S3 interface for those who
prefer the latter.  Finally yet importantly, its functional approach allows for
incorporating functionalities from many other packages.")
    (license license:expat)))

(define-public r-dtsea
  (package
    (name "r-dtsea")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTSEA" version))
       (sha256
        (base32 "1f1di9ypq6f0929pq15xncf7zw16wlqap4rchbia27n39cv15dni"))))
    (properties `((upstream-name . "DTSEA")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-magrittr
                             r-igraph
                             r-fgsea
                             r-dplyr
                             r-biocparallel))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DTSEA")
    (synopsis "Drug Target Set Enrichment Analysis")
    (description
     "It is a novel tool used to identify the candidate drugs against a particular
disease based on the drug target set enrichment analysis.  It assumes the most
effective drugs are those with a closer affinity in the protein-protein
interaction network to the specified disease. (See GÃ³mez-Carballa et al. (2022)
<doi: 10.1016/j.envres.2022.112890> and Feng et al. (2022) <doi:
10.7150/ijms.67815> for disease expression profiles; see Wishart et al. (2018)
<doi: 10.1093/nar/gkx1037> and Gaulton et al. (2017) <doi: 10.1093/nar/gkw1074>
for drug target information; see Kanehisa et al. (2021) <doi:
10.1093/nar/gkaa970> for the details of KEGG database.).")
    (license license:gpl2+)))

(define-public r-dtrsurv
  (package
    (name "r-dtrsurv")
    (version "1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dtrSurv" version))
       (sha256
        (base32 "1xc39rigaylrq6d6zm6szgkiwdh4xjkvcima9lkhs1qnbrj3gb5l"))))
    (properties `((upstream-name . "dtrSurv")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival))
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=dtrSurv")
    (synopsis "Dynamic Treatment Regimes for Survival Analysis")
    (description
     "This package provides methods for estimating multi-stage optimal dynamic
treatment regimes for survival outcomes with dependent censoring.  Cho, H.,
Holloway, S. T., and Kosorok, M. R. (2020) <@code{arXiv:2012.03294>}.")
    (license license:gpl2)))

(define-public r-dtrreg
  (package
    (name "r-dtrreg")
    (version "2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTRreg" version))
       (sha256
        (base32 "1irgkrar8m0xy97y19j48s8ab9y4cjzbbnhk3mhqbbs2qgam92cw"))))
    (properties `((upstream-name . "DTRreg")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6 r-nnet))
    (home-page "https://cran.r-project.org/package=DTRreg")
    (synopsis
     "DTR Estimation and Inference via G-Estimation, Dynamic WOLS, Q-Learning, and Dynamic Weighted Survival Modeling (DWSurv)")
    (description
     "Dynamic treatment regime estimation and inference via G-estimation, dynamic
weighted ordinary least squares (@code{dWOLS}) and Q-learning.  Inference via
bootstrap and recursive sandwich estimation.  Estimation and inference for
survival outcomes via Dynamic Weighted Survival Modeling (DWSurv).  Extension to
continuous treatment variables.  Wallace et al. (2017)
<DOI:10.18637/jss.v080.i02>; Simoneau et al. (2020)
<DOI:10.1080/00949655.2020.1793341>.")
    (license license:gpl2)))

(define-public r-dtrlearn2
  (package
    (name "r-dtrlearn2")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTRlearn2" version))
       (sha256
        (base32 "0l756zb1wkpa1z5zjkc8jndmh2630gckxxfqslabzjmgsjf7fjgm"))))
    (properties `((upstream-name . "DTRlearn2")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-mass r-kernlab r-glmnet r-foreach))
    (home-page "https://cran.r-project.org/package=DTRlearn2")
    (synopsis
     "Statistical Learning Methods for Optimizing Dynamic Treatment Regimes")
    (description
     "We provide a comprehensive software to estimate general K-stage DTRs from SMARTs
with Q-learning and a variety of outcome-weighted learning methods.
Penalizations are allowed for variable selection and model regularization.  With
the outcome-weighted learning scheme, different loss functions - SVM hinge loss,
SVM ramp loss, binomial deviance loss, and L2 loss - are adopted to solve the
weighted classification problem at each stage; augmentation in the outcomes is
allowed to improve efficiency.  The estimated DTR can be easily applied to a new
sample for individualized treatment recommendations or DTR evaluation.")
    (license license:gpl2)))

(define-public r-dtrkernsmooth
  (package
    (name "r-dtrkernsmooth")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTRKernSmooth" version))
       (sha256
        (base32 "0ikq9rj7harlc00gj6wqc62pyj25ap9ajfh622b5cj5zkdrc8qy1"))))
    (properties `((upstream-name . "DTRKernSmooth")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppeigen r-rcpp))
    (home-page "https://cran.r-project.org/package=DTRKernSmooth")
    (synopsis
     "Estimate and Make Inference About Optimal Treatment Regimes via Smoothed Methods")
    (description
     "This package provides methods to estimate the optimal treatment regime among all
linear regimes via smoothed estimation methods, and construct element-wise
confidence intervals for the optimal linear treatment regime vector, as well as
the confidence interval for the optimal value via wild bootstrap procedures, if
the population follows treatments recommended by the optimal linear regime.  See
more details in: Wu, Y. and Wang, L. (2021), \"Resampling-based Confidence
Intervals for Model-free Robust Inference on Optimal Treatment Regimes\",
Biometrics, 77: 465â 476, <doi:10.1111/biom.13337>.")
    (license license:gpl2+)))

(define-public r-dtreg
  (package
    (name "r-dtreg")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dtreg" version))
       (sha256
        (base32 "02rplyjzdn4liipgi73qhanqn2lqdk1hymrrsfvvyarzyba3yiwr"))))
    (properties `((upstream-name . "dtreg")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-r6 r-jsonlite r-httr2))
    (native-inputs (list r-knitr))
    (home-page "https://gitlab.com/TIBHannover/orkg/dtreg-r")
    (synopsis
     "Interact with Data Type Registries and Create Machine-Readable Data")
    (description
     "You can load a schema from a DTR (data type registry) as an R object.  Use this
schema to write your data in JSON-LD (@code{JavaScript} Object Notation for
Linked Data) format to make it machine readable.")
    (license license:expat)))

(define-public r-dtrackr
  (package
    (name "r-dtrackr")
    (version "0.4.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dtrackr" version))
       (sha256
        (base32 "0biwciv8f8rd6psydiriyylklw7q954dsr3rrax5a2fc3gn9adbz"))))
    (properties `((upstream-name . "dtrackr")))
    (build-system r-build-system)
    (propagated-inputs (list r-v8
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rsvg
                             r-rlang
                             r-purrr
                             r-png
                             r-pdftools
                             r-magrittr
                             r-htmltools
                             r-glue
                             r-fs
                             r-dplyr
                             r-base64enc))
    (native-inputs (list r-knitr))
    (home-page "https://terminological.github.io/dtrackr/index.html")
    (synopsis "Track your Data Pipelines")
    (description
     "Track and document dplyr data pipelines.  As you filter, mutate, and join your
way through a data set, dtrackr seamlessly keeps track of your data flow and
makes publication ready documentation of a data pipeline simple.")
    (license license:expat)))

(define-public r-dtpcrm
  (package
    (name "r-dtpcrm")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dtpcrm" version))
       (sha256
        (base32 "0k25fm0z3snpx1v2kwd50svgnkjhn5c0hy1gnlw2lif6rjz1fzd9"))))
    (properties `((upstream-name . "dtpcrm")))
    (build-system r-build-system)
    (propagated-inputs (list r-diagram r-dfcrm))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dtpcrm")
    (synopsis "Dose Transition Pathways for Continual Reassessment Method")
    (description
     "This package provides the dose transition pathways (DTP) to project in advance
the doses recommended by a model-based design for subsequent patients (stay,
escalate, deescalate or stop early) using all the accumulated toxicity
information; See Yap et al (2017) <doi: 10.1158/1078-0432.CCR-17-0582>.  DTP can
be used as a design and an operational tool and can be displayed as a table or
flow diagram.  The dtpcrm package also provides the modified continual
reassessment method (CRM) and time-to-event CRM (TITE-CRM) with added practical
considerations to allow stopping early when there is sufficient evidence that
the lowest dose is too toxic and/or there is a sufficient number of patients
dosed at the maximum tolerated dose.")
    (license license:gpl2+)))

(define-public r-dtp
  (package
    (name "r-dtp")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dtp" version))
       (sha256
        (base32 "0qy8nrbq22bfbajkxq6blkq7583pc5mb392gmqb3c9daxmqn42vb"))))
    (properties `((upstream-name . "dtp")))
    (build-system r-build-system)
    (propagated-inputs (list r-plyr r-gtools r-formula))
    (home-page "https://cran.r-project.org/package=dtp")
    (synopsis "Dynamic Panel Threshold Model")
    (description
     "Compute the dynamic threshold panel model suggested by (Stephanie Kremer,
Alexander Bick and Dieter Nautz (2013) <doi:10.1007/s00181-012-0553-9>) in which
they extended the (Hansen (1999) <doi: 10.1016/S0304-4076(99)00025-1>) original
static panel threshold estimation and the Caner and (Hansen (2004)
<doi:10.1017/S0266466604205011>) cross-sectional instrumental variable threshold
model, where generalized methods of moments type estimators are used.")
    (license license:gpl3)))

(define-public r-dtmcpack
  (package
    (name "r-dtmcpack")
    (version "0.1-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTMCPack" version))
       (sha256
        (base32 "1a07hpl1fagigxkd3yjjkwjpmjwbfyg9a7m8fcj1602xl525h2ki"))))
    (properties `((upstream-name . "DTMCPack")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DTMCPack")
    (synopsis
     "Suite of Functions Related to Discrete-Time Discrete-State Markov Chains")
    (description
     "This package provides a series of functions which aid in both simulating and
determining the properties of finite, discrete-time, discrete state markov
chains.  Two functions (DTMC, @code{MultDTMC}) produce n iterations of a Markov
Chain(s) based on transition probabilities and an initial distribution.  The
function FPTime determines the first passage time into each state.  The function
statdistr determines the stationary distribution of a Markov Chain.")
    (license license:gpl2+)))

(define-public r-dtmapi
  (package
    (name "r-dtmapi")
    (version "0.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dtmapi" version))
       (sha256
        (base32 "1a0a5dff82igzxsz0ma3j2w7waqq2nrv3cy0df2nh7sgqvcldk4m"))))
    (properties `((upstream-name . "dtmapi")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-jsonlite r-httr2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Displacement-Tracking-Matrix/dtmapi-R")
    (synopsis "Fetching Data from the 'Displacement Tracking Matrix'")
    (description
     "Allows humanitarian community, academia, media, government, and non-governmental
organizations to utilize the data collected by the Displacement Tracking Matrix
(<https://dtm.iom.int>), a unit in the International Organization for Migration.
 This also provides non-sensitive Internally Displaced Person figures,
aggregated at the country, Admin 1 (states, provinces, or equivalent), and Admin
2 (smaller administrative areas) levels.")
    (license license:expat)))

(define-public r-dti
  (package
    (name "r-dti")
    (version "1.5.4.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dti" version))
       (sha256
        (base32 "058qny6hv3lcirjmc7kbldyy1i333p9vmvpz4jl9dyrcz5h6qmjh"))))
    (properties `((upstream-name . "dti")))
    (build-system r-build-system)
    (inputs (list gsl))
    (propagated-inputs (list r-rgl
                             r-quadprog
                             r-oro-nifti
                             r-oro-dicom
                             r-gsl
                             r-awsmethods
                             r-aws
                             r-adimpro))
    (native-inputs (list gfortran))
    (home-page "https://www.wias-berlin.de/research/ats/imaging/")
    (synopsis "Analysis of Diffusion Weighted Imaging (DWI) Data")
    (description
     "Diffusion Weighted Imaging (DWI) is a Magnetic Resonance Imaging modality, that
measures diffusion of water in tissues like the human brain.  The package
contains R-functions to process diffusion-weighted data.  The functionality
includes diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI),
modeling for high angular resolution diffusion weighted imaging (HARDI) using
Q-ball-reconstruction and tensor mixture models, several methods for structural
adaptive smoothing including POAS and @code{msPOAS}, and a streamline fiber
tracking for tensor and tensor mixture models.  The package provides
functionality to manipulate and visualize results in 2D and 3D.")
    (license license:gpl2+)))

(define-public r-dtgiw
  (package
    (name "r-dtgiw")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dtgiw" version))
       (sha256
        (base32 "1902rhfrnmp3550c6sqfrzs7xrrjpym0zpqhfnlffdnn42cp910r"))))
    (properties `((upstream-name . "dtgiw")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dtgiw")
    (synopsis "Discrete Transmuted Generalized Inverse Weibull Distribution")
    (description
     "The Discrete Transmuted Generalized Inverse Weibull (DTGIW) distribution is a
new distribution for count data analysis.  The DTGIW is discrete distribution
based on Atchanut and Sirinapa (2021). <DOI: 10.14456/sjst-psu.2021.149>.")
    (license license:gpl3)))

(define-public r-dtda-ni
  (package
    (name "r-dtda-ni")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTDA.ni" version))
       (sha256
        (base32 "0lv8k37n271zcmp5mxxc6z03bx283lnc4iz3zz1k2mnfzq2wrahz"))))
    (properties `((upstream-name . "DTDA.ni")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/sidoruvigo/DTDA.ni")
    (synopsis "Doubly Truncated Data Analysis, Non Iterative")
    (description
     "Non-iterative estimator for the cumulative distribution of a doubly truncated
variable.  de UÃ±a-Ãlvarez J. (2018) <doi:10.1007/978-3-319-73848-2_37>.")
    (license license:gpl2)))

(define-public r-dtda-cif
  (package
    (name "r-dtda-cif")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTDA.cif" version))
       (sha256
        (base32 "12vkhqxdhir06s35kr76dwns9m02wyicz3mv4r56fqglsfyw77xr"))))
    (properties `((upstream-name . "DTDA.cif")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-foreach r-doparallel))
    (home-page "https://cran.r-project.org/package=DTDA.cif")
    (synopsis "Doubly Truncated Data Analysis, Cumulative Incidence Functions")
    (description
     "Nonparametric estimator of the cumulative incidences of competing risks under
double truncation.  The estimator generalizes the Efron-Petrosian NPMLE
(Non-Parametric Maximun Likelihood Estimator) to the competing risks setting.
Efron, B. and Petrosian, V. (1999) <doi:10.2307/2669997>.")
    (license license:gpl2)))

(define-public r-dtda
  (package
    (name "r-dtda")
    (version "3.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTDA" version))
       (sha256
        (base32 "1x65ahrci7n8v5d6nfz2p3p1x0zjam3a2mvw9m1rpdmfgbalpim7"))))
    (properties `((upstream-name . "DTDA")))
    (build-system r-build-system)
    (propagated-inputs (list r-foreach r-doparallel))
    (home-page "https://cran.r-project.org/package=DTDA")
    (synopsis "Doubly Truncated Data Analysis")
    (description
     "Implementation of different algorithms for analyzing randomly truncated data,
one-sided and two-sided (i.e.  doubly) truncated data.  It serves to compute
empirical cumulative distributions and also kernel density and hazard functions
using different bandwidth selectors.  Several real data sets are included.")
    (license license:gpl2)))

(define-public r-dtd
  (package
    (name "r-dtd")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DtD" version))
       (sha256
        (base32 "1czspjdxjhbfk2df7wk0x3d1ilwrjqw4s4gdc4hq0gjcjqyx0c39"))))
    (properties `((upstream-name . "DtD")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DtD")
    (synopsis "Distance to Default")
    (description
     "This package provides fast methods to work with Merton's distance to default
model introduced in Merton (1974) <doi:10.1111/j.1540-6261.1974.tb03058.x>.  The
methods includes simulation and estimation of the parameters.")
    (license license:gpl2)))

(define-public r-dtcompair
  (package
    (name "r-dtcompair")
    (version "1.2.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTComPair" version))
       (sha256
        (base32 "1ajmzap56vpfxn0x57alb6h2g94z132i96jsmczjl6zajm5yr6y4"))))
    (properties `((upstream-name . "DTComPair")))
    (build-system r-build-system)
    (propagated-inputs (list r-propcis r-gee r-ellipse r-assertthat))
    (home-page "https://github.com/chstock/DTComPair")
    (synopsis "Comparison of Binary Diagnostic Tests in a Paired Study Design")
    (description
     "Comparison of the accuracy of two binary diagnostic tests in a \"paired\" study
design, i.e.  when each test is applied to each subject in the study.")
    (license license:gpl3+)))

(define-public r-dtcomb
  (package
    (name "r-dtcomb")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dtComb" version))
       (sha256
        (base32 "0zfcbwl40hxva5282qplr27idclickid0p4a8vnz5559abygl5aa"))))
    (properties `((upstream-name . "dtComb")))
    (build-system r-build-system)
    (propagated-inputs (list r-proc
                             r-optimalcutpoints
                             r-glmnet
                             r-ggpubr
                             r-ggplot2
                             r-gam
                             r-epir
                             r-caret))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/gokmenzararsiz/dtComb")
    (synopsis "Statistical Combination of Diagnostic Tests")
    (description
     "This package provides a system for combining two diagnostic tests using various
approaches that include statistical and machine-learning-based methodologies.
These approaches are divided into four groups: linear combination methods,
non-linear combination methods, mathematical operators, and machine learning
algorithms.  See the <https://biotools.erciyes.edu.tr/@code{dtComb/>} website
for more information, documentation, and examples.")
    (license license:expat)))

(define-public r-dtbm
  (package
    (name "r-dtbm")
    (version "3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dTBM" version))
       (sha256
        (base32 "0asqz2r55awp5xh7gqawkh8lgal64216qi9ncg2jvfg5ny5ryv4i"))))
    (properties `((upstream-name . "dTBM")))
    (build-system r-build-system)
    (propagated-inputs (list r-weightedcluster r-envstats))
    (home-page "https://cran.r-project.org/package=dTBM")
    (synopsis
     "Multi-Way Spherical Clustering via Degree-Corrected Tensor Block Models")
    (description
     "Implement weighted higher-order initialization and angle-based iteration for
multi-way spherical clustering under degree-corrected tensor block model.  See
reference Jiaxin Hu and Miaoyan Wang (2023) <doi:10.1109/TIT.2023.3239521>.")
    (license license:gpl2+)))

(define-public r-dtaxg
  (package
    (name "r-dtaxg")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTAXG" version))
       (sha256
        (base32 "1jxa0ix0z35i0xdnjl698j8iqjmp6nz8ckah9bap5ay9rkq0xd7f"))))
    (properties `((upstream-name . "DTAXG")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DTAXG")
    (synopsis "Diagnostic Test Assessment in the Absence of Gold Standard")
    (description
     "To calculate the sensitivity and specificity in the absence of gold standard
using the Bayesian method.  The Bayesian method can be referenced at Haiyan Gu
and Qiguang Chen (1999) <doi:10.3969/j.issn.1002-3674.1999.04.004>.")
    (license license:gpl3)))

(define-public r-dtat
  (package
    (name "r-dtat")
    (version "0.3-7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTAT" version))
       (sha256
        (base32 "0rh09bdygqwzdlx0girs2ir5dy3jd3r2m4xia46njxvh3jld5vsg"))))
    (properties `((upstream-name . "DTAT")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-shiny
                             r-r2d3
                             r-pomp
                             r-km-ci
                             r-jsonlite
                             r-hmisc
                             r-dplyr
                             r-data-table))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://precisionmethods.guru/")
    (synopsis "Dose Titration Algorithm Tuning")
    (description
     "Dose Titration Algorithm Tuning (DTAT) is a methodologic framework allowing dose
individualization to be conceived as a continuous learning process that begins
in early-phase clinical trials and continues throughout drug development, on
into clinical practice.  This package includes code that researchers may use to
reproduce or extend key results of the DTAT research programme, plus tools for
trialists to design and simulate a 3+3/PC dose-finding study.  Please see Norris
(2017a) <doi:10.12688/f1000research.10624.3> and Norris (2017c)
<doi:10.1101/240846>.")
    (license license:expat)))

(define-public r-dtaplots
  (package
    (name "r-dtaplots")
    (version "1.0.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DTAplots" version))
       (sha256
        (base32 "1jwfh8j8ahaj2z19g2f70r652j77q4f0b7j91mggsb0dgk449342"))))
    (properties `((upstream-name . "DTAplots")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DTAplots")
    (synopsis
     "Creates Plots Accompanying Bayesian Diagnostic Test Accuracy Meta-Analyses")
    (description
     "Function to create forest plots.  Functions to use posterior samples from
Bayesian bivariate meta-analysis model, Bayesian hierarchical summary receiver
operating characteristic (HSROC) meta-analysis model or Bayesian latent class
(LC) meta-analysis model to create Summary Receiver Operating Characteristic
(SROC) plots using methods described by Harbord et al
(2007)<doi:10.1093/biostatistics/kxl004>.")
    (license license:gpl2+)))

(define-public r-dtangle
  (package
    (name "r-dtangle")
    (version "2.0.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dtangle" version))
       (sha256
        (base32 "0yg1fbrqixqp93vdw3grvz1la5l2kidgs730qp6yihkp3260cxf3"))))
    (properties `((upstream-name . "dtangle")))
    (build-system r-build-system)
    (propagated-inputs (list r-deoptimr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dtangle")
    (synopsis "Cell Type Deconvolution from Gene Expressions")
    (description
     "Deconvolving cell types from high-throughput gene profiling data.  For more
information on dtangle see Hunt et al. (2019)
<doi:10.1093/bioinformatics/bty926>.")
    (license license:gpl3)))

(define-public r-dtableone
  (package
    (name "r-dtableone")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Dtableone" version))
       (sha256
        (base32 "0pv04l4wxf44zva5w96i02g4z8zx3zgjxxjacfg0vh2f7gx4pjnq"))))
    (properties `((upstream-name . "Dtableone")))
    (build-system r-build-system)
    (propagated-inputs (list r-proc r-irr r-epir r-dplyr))
    (home-page "https://cran.r-project.org/package=Dtableone")
    (synopsis "Tabular Comparison of Paired Diagnostic Tests")
    (description
     "Offers statistical methods to compare diagnostic performance between two binary
diagnostic tests on the same subject in clinical studies.  Includes functions
for generating formatted tables to display diagnostic outcomes, facilitating a
clear and comprehensive comparison directly through the R console.  Inspired by
and extending the functionalities of the DT@code{ComPair}', tableone', and
gtsummary packages.")
    (license license:gpl2)))

(define-public r-dswe
  (package
    (name "r-dswe")
    (version "1.8.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DSWE" version))
       (sha256
        (base32 "0xbhbiiq0mhqspxlgzlnrq2zm3gnb8n4rj285rdgq4cbpmfrly6l"))))
    (properties `((upstream-name . "DSWE")))
    (build-system r-build-system)
    (propagated-inputs (list r-xgboost
                             r-rcpparmadillo
                             r-rcpp
                             r-mixtools
                             r-matrixstats
                             r-kernsmooth
                             r-gss
                             r-fnn
                             r-e1071
                             r-dplyr))
    (home-page "https://github.com/TAMU-AML/DSWE-Package")
    (synopsis "Data Science for Wind Energy")
    (description
     "Data science methods used in wind energy applications.  Current functionalities
include creating a multi-dimensional power curve model, performing power curve
function comparison, covariate matching, and energy decomposition.  Relevant
works for the developed functions are: @code{funGP}() - Prakash et al. (2022)
<doi:10.1080/00401706.2021.1905073>, AMK() - Lee et al. (2015)
<doi:10.1080/01621459.2014.977385>, @code{tempGP}() - Prakash et al. (2022)
<doi:10.1080/00401706.2022.2069158>, @code{ComparePCurve}() - Ding et al. (2021)
<doi:10.1016/j.renene.2021.02.136>, @code{deltaEnergy}() - Latiffianti et al.
(2022) <doi:10.1002/we.2722>, @code{syncSize}() - Latiffianti et al. (2022)
<doi:10.1002/we.2722>, @code{imptPower}() - Latiffianti et al. (2022)
<doi:10.1002/we.2722>, All other functions - Ding (2019, ISBN:9780429956508).")
    (license license:expat)))

(define-public r-dsva
  (package
    (name "r-dsva")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dSVA" version))
       (sha256
        (base32 "0vy0flyg82x0n9vw6jf9f76qy84sp0wnis91faj37ac5hdv3pvsb"))))
    (properties `((upstream-name . "dSVA")))
    (build-system r-build-system)
    (propagated-inputs (list r-sva))
    (home-page "https://cran.r-project.org/package=dSVA")
    (synopsis "Direct Surrogate Variable Analysis")
    (description
     "This package provides functions for direct surrogate variable analysis, which
can identify hidden factors in high-dimensional biomedical data.")
    (license license:gpl2+)))

(define-public r-dstem
  (package
    (name "r-dstem")
    (version "2.0-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dSTEM" version))
       (sha256
        (base32 "0llp5az6sdbq9kk9dbk0app7lx3jbns2amb8pd9nbvrgz133jg5m"))))
    (properties `((upstream-name . "dSTEM")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://doi.org/10.1214/20-EJS1751")
    (synopsis
     "Multiple Testing of Local Extrema for Detection of Change Points")
    (description
     "Simultaneously detect the number and locations of change points in piecewise
linear models under stationary Gaussian noise allowing autocorrelated random
noise.  The core idea is to transform the problem of detecting change points
into the detection of local extrema (local maxima and local minima)through
kernel smoothing and differentiation of the data sequence, see Cheng et al.
(2020) <doi:10.1214/20-EJS1751>.  A low-computational and fast algorithm call
@code{dSTEM} is introduced to detect change points based on the STEM algorithm
in D. Cheng and A. Schwartzman (2017) <doi:10.1214/16-AOS1458>.")
    (license license:gpl3)))

(define-public r-dstat2x2xk
  (package
    (name "r-dstat2x2xk")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dstat2x2xk" version))
       (sha256
        (base32 "16qbczzjzhmsby8d2sf1xnijiczlk29xazbgl98jbfpmpfzn4q6j"))))
    (properties `((upstream-name . "dstat2x2xk")))
    (build-system r-build-system)
    (propagated-inputs (list r-biasedurn))
    (home-page "https://cran.r-project.org/package=dstat2x2xk")
    (synopsis "Demonstrated Insensitivity to Bias in 2x2xK Contingency Tables")
    (description
     "For an observational study with binary treatment, binary outcome and K strata,
implements a d-statistic that uses those strata most insensitive to unmeasured
bias in treatment assignment.<doi:10.1093/biomet/asaa032> The package has one
function, dstat2x2xk.")
    (license license:gpl2)))

(define-public r-dstat
  (package
    (name "r-dstat")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dstat" version))
       (sha256
        (base32 "023jp0xdbg200ww1gnr3fzgjqd82acag0jps7q6j6m27q11psvgz"))))
    (properties `((upstream-name . "dstat")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dstat")
    (synopsis
     "Conditional Sensitivity Analysis for Matched Observational Studies")
    (description
     "This package provides a d-statistic tests the null hypothesis of no treatment
effect in a matched, nonrandomized study of the effects caused by treatments.  A
d-statistic focuses on subsets of matched pairs that demonstrate insensitivity
to unmeasured bias in such an observational study, correcting for double-use of
the data by conditional inference.  This conditional inference can, in favorable
circumstances, substantially increase the power of a sensitivity analysis
(Rosenbaum (2010) <doi:10.1007/978-1-4419-1213-8_14>).  There are two examples,
one concerning unemployment from Lalive et al. (2006)
<doi:10.1111/j.1467-937X.2006.00406.x>, the other concerning smoking and
periodontal disease from Rosenbaum (2017) <doi:10.1214/17-STS621>.")
    (license license:gpl2)))

(define-public r-dstarm
  (package
    (name "r-dstarm")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DstarM" version))
       (sha256
        (base32 "0wm5kr2pkgbvh9svjq8zq46zn50hwf58rs3y1ybnwcfjc2q75h1s"))))
    (properties `((upstream-name . "DstarM")))
    (build-system r-build-system)
    (propagated-inputs (list r-rwiener
                             r-rtdists
                             r-rcpparmadillo
                             r-rcpp
                             r-ggplot2
                             r-deoptim))
    (home-page "https://github.com/vandenman/DstarM")
    (synopsis "Analyze Two Choice Reaction Time Data with the D*M Method")
    (description
     "This package provides a collection of functions to estimate parameters of a
diffusion model via a D*M analysis.  Build in models are: the Ratcliff diffusion
model, the RWiener diffusion model, and Linear Ballistic Accumulator models.
Custom models functions can be specified as long as they have a density
function.")
    (license license:gpl2+)))

(define-public r-dstabledist
  (package
    (name "r-dstabledist")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dstabledist" version))
       (sha256
        (base32 "07nvsv0xb6wv0yl7ia7sgm6ysi4w2714pjyqhbzl76mp4c7cx7cd"))))
    (properties `((upstream-name . "dstabledist")))
    (build-system r-build-system)
    (propagated-inputs (list r-stabledist r-rdpack))
    (home-page "https://cran.r-project.org/package=dstabledist")
    (synopsis "The Discrete Stable Distribution Functions")
    (description
     "Probability generating function, formulae for the probabilities (discrete
density) and random generation for discrete stable random variables.")
    (license license:gpl3)))

(define-public r-dst
  (package
    (name "r-dst")
    (version "1.8.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dst" version))
       (sha256
        (base32 "1h91pz04cr9frnrnz7zdrn5lwhfsgfx1q9xk0wwifpzhkfy2h9ix"))))
    (properties `((upstream-name . "dst")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-rlang r-matrix r-ggplot2 r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dst")
    (synopsis "Using the Theory of Belief Functions")
    (description
     "Using the Theory of Belief Functions for evidence calculus.  Basic probability
assignments, or mass functions, can be defined on the subsets of a set of
possible values and combined.  A mass function can be extended to a larger
frame.  Marginalization, i.e.  reduction to a smaller frame can also be done.
These features can be combined to analyze small belief networks and take into
account situations where information cannot be satisfactorily described by
probability distributions.")
    (license license:gpl2+)))

(define-public r-dssp
  (package
    (name "r-dssp")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DSSP" version))
       (sha256
        (base32 "1z4sfqlgqwhxhm8aryv5c3vlzamn9nx2c49dyi1axq4qpy7dg3pr"))))
    (properties `((upstream-name . "DSSP")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp
                             r-rust
                             r-rcpparmadillo
                             r-rcpp
                             r-posterior
                             r-mcmcse))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/gentrywhite/DSSP")
    (synopsis "Implementation of the Direct Sampling Spatial Prior")
    (description
     "Draw samples from the direct sampling spatial prior model as described in G.
White, D. Sun, P. Speckman (2019) <@code{arXiv:1906.05575>}.  The basic model
assumes a Gaussian likelihood and derives a spatial prior based on thin-plate
splines.")
    (license license:gpl3+)))

(define-public r-dssd
  (package
    (name "r-dssd")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dssd" version))
       (sha256
        (base32 "1nbr8mdva6g7p9mrbbg6g116vrvny07yvkyklgjbw79vrj7lfgy3"))))
    (properties `((upstream-name . "dssd")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dssd")
    (synopsis "Distance Sampling Survey Design")
    (description
     "This package creates survey designs for distance sampling surveys.  These
designs can be assessed for various effort and coverage statistics.  Once the
user is satisfied with the design characteristics they can generate a set of
transects to use in their distance sampling survey.  Many of the designs
implemented in this R package were first made available in our Distance for
Windows software and are detailed in Chapter 7 of Advanced Distance Sampling,
Buckland et.  al. (2008, ISBN-13: 978-0199225873).  Find out more about
estimating animal/plant abundance with distance sampling at
<http://distancesampling.org/>.")
    (license license:gpl2+)))

(define-public r-dssat
  (package
    (name "r-dssat")
    (version "0.0.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DSSAT" version))
       (sha256
        (base32 "0ws1s8gccn3qhb7jalj3lv4qpgy2hdan63wpp6fsvlqmd202wfa3"))))
    (properties `((upstream-name . "DSSAT")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-readr
                             r-purrr
                             r-magrittr
                             r-lubridate
                             r-glue
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=DSSAT")
    (synopsis "Comprehensive R Interface for the DSSAT Cropping Systems Model")
    (description
     "The purpose of this package is to provide a comprehensive R interface to the
Decision Support System for Agrotechnology Transfer Cropping Systems Model
(DSSAT-CSM; see <https://dssat.net> for more information).  The package provides
cross-platform functions to read and write input files, run DSSAT-CSM, and read
output files.")
    (license license:gpl3+)))

(define-public r-dsrtest
  (package
    (name "r-dsrtest")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dsrTest" version))
       (sha256
        (base32 "1nfwcab6p7swki8d2j2dywj93xidkjqcq84majvq90yabx353jd3"))))
    (properties `((upstream-name . "dsrTest")))
    (build-system r-build-system)
    (propagated-inputs (list r-loglognorm r-exactci r-asht))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mnelsonr/dsrTest")
    (synopsis
     "Tests and Confidence Intervals on Directly Standardized Rates for Several Methods")
    (description
     "Perform a test of a simple null hypothesis about a directly standardized rate
and obtain the matching confidence interval using a choice of methods.")
    (license license:gpl2+)))

(define-public r-dspoty
  (package
    (name "r-dspoty")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DSpoty" version))
       (sha256
        (base32 "18z8gk3zj7k2szxg9579qy5klrqjw6zsk5x9jmwrv4qhb98fyji6"))))
    (properties `((upstream-name . "DSpoty")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-purrr r-httr r-dplyr))
    (home-page "https://github.com/AlbertoAlmuinha/DSpoty")
    (synopsis "Get 'Spotify' API Multiple Information")
    (description
     "You can retrieve Spotify API Information such as artists, albums, tracks,
features tracks, recommendations or related artists.  This package allows you to
search all the information by name and also includes a distance based algorithm
to find similar songs.  More information:
<https://developer.spotify.com/documentation/web-api/> .")
    (license license:gpl3)))

(define-public r-dsos
  (package
    (name "r-dsos")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dsos" version))
       (sha256
        (base32 "1qv44wj1dvng1m4lkscn9yylhxsr8ck46wv54vjy9px4g7rmjaq5"))))
    (properties `((upstream-name . "dsos")))
    (build-system r-build-system)
    (propagated-inputs (list r-simctest r-scales r-ggplot2 r-future-apply
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/vathymut/dsos")
    (synopsis "Dataset Shift with Outlier Scores")
    (description
     "Test for no adverse shift in two-sample comparison when we have a training set,
the reference distribution, and a test set.  The approach is flexible and relies
on a robust and powerful test statistic, the weighted AUC. Technical details are
in Kamulete, V. M. (2021) <@code{arXiv:1908.04000>}.  Modern notions of
outlyingness such as trust scores and prediction uncertainty can be used as the
underlying scores for example.")
    (license license:gpl3+)))

(define-public r-dsopal
  (package
    (name "r-dsopal")
    (version "1.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DSOpal" version))
       (sha256
        (base32 "1jhjk2anh5kc421r0l8v0s5cbnqhdwwiirk1zcmmgk62k3an0lsf"))))
    (properties `((upstream-name . "DSOpal")))
    (build-system r-build-system)
    (propagated-inputs (list r-opalr r-dsi))
    (home-page "https://github.com/datashield/DSOpal/")
    (synopsis "'DataSHIELD' Implementation for 'Opal'")
    (description
     "@code{DataSHIELD} is an infrastructure and series of R packages that enables the
remote and non-disclosive analysis of sensitive research data.  This package is
the @code{DataSHIELD} interface implementation for Opal', which is the data
integration application for biobanks by O@code{BiBa}'.  Participant data, once
collected from any data source, must be integrated and stored in a central data
repository under a uniform model.  Opal is such a central repository.  It can
import, process, validate, query, analyze, report, and export data.  Opal is the
reference implementation of the @code{DataSHIELD} infrastructure.")
    (license license:lgpl2.1+)))

(define-public r-dsmsearch
  (package
    (name "r-dsmsearch")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dsmSearch" version))
       (sha256
        (base32 "1kif46mjhrxxmdv4jahagjd3bz47na3k4r8m10cm85cac88iichm"))))
    (properties `((upstream-name . "dsmSearch")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra
                             r-sp
                             r-sf
                             r-lidr
                             r-imager
                             r-httr2
                             r-dplyr))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://cran.r-project.org/package=dsmSearch")
    (synopsis "DSM and LiDAR downloader")
    (description
     "This package provides a collection of functions to search and donwload DSM
(Digital Surface Model) and @code{LiDAR} (Light Detection and Ranging) data via
APIs, including @code{OpenTopography}
<https://portal.opentopography.org/apidocs/> and TNMAccess
<https://apps.nationalmap.gov/tnmaccess/#/>.")
    (license license:gpl3)))

(define-public r-dsmolgenisarmadillo
  (package
    (name "r-dsmolgenisarmadillo")
    (version "2.0.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DSMolgenisArmadillo" version))
       (sha256
        (base32 "0myhpkblj8dl1csqd91wk7xr4zvnk400ygqbwbajayjn6l7dvqmd"))))
    (properties `((upstream-name . "DSMolgenisArmadillo")))
    (build-system r-build-system)
    (propagated-inputs (list r-urltools
                             r-stringr
                             r-molgenisauth
                             r-jsonlite
                             r-httr
                             r-dsi
                             r-dplyr
                             r-base64enc))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/molgenis/molgenis-r-datashield/")
    (synopsis "'DataSHIELD' Client for 'MOLGENIS Armadillo'")
    (description
     "@code{DataSHIELD} is an infrastructure and series of R packages that enables the
remote and non-disclosive analysis of sensitive research data.  This package is
the @code{DataSHIELD} interface implementation to analyze data shared on a
MOLGENIS Armadillo server.  MOLGENIS Armadillo is a light-weight
@code{DataSHIELD} server using a file store and an RServe server.")
    (license license:lgpl2.1+)))

(define-public r-dsmmr
  (package
    (name "r-dsmmr")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dsmmR" version))
       (sha256
        (base32 "0pdhpshdhpd1cvgnx3cnbkczwychxv49w90sc4lvgviknl7wd4c1"))))
    (properties `((upstream-name . "dsmmR")))
    (build-system r-build-system)
    (propagated-inputs (list r-discreteweibull))
    (home-page "https://github.com/Mavrogiannis-Ioannis/dsmmR")
    (synopsis "Estimation and Simulation of Drifting Semi-Markov Models")
    (description
     "This package performs parametric and non-parametric estimation and simulation of
drifting semi-Markov processes.  The definition of parametric and non-parametric
model specifications is also possible.  Furthermore, three different types of
drifting semi-Markov models are considered.  These models differ in the number
of transition matrices and sojourn time distributions used for the computation
of a number of semi-Markov kernels, which in turn characterize the drifting
semi-Markov kernel.  For the parametric model estimation and specification,
several discrete distributions are considered for the sojourn times: Uniform,
Poisson, Geometric, Discrete Weibull and Negative Binomial.  The non-parametric
model specification makes no assumptions about the shape of the sojourn time
distributions.  Semi-Markov models are described in: Barbu, V.S., Limnios, N.
(2008) <doi:10.1007/978-0-387-73173-5>.  Drifting Markov models are described
in: Vergne, N. (2008) <doi:10.2202/1544-6115.1326>.  Reliability indicators of
Drifting Markov models are described in: Barbu, V. S., Vergne, N. (2019)
<doi:10.1007/s11009-018-9682-8>.  We acknowledge the DATALAB Project
<https://lmrs-num.math.cnrs.fr/projet-datalab.html> (financed by the European
Union with the European Regional Development fund (ERDF) and by the Normandy
Region) and the HSMM-INCA Project (financed by the French Agence Nationale de la
Recherche (ANR) under grant ANR-21-CE40-0005).")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-dsmisc
  (package
    (name "r-dsmisc")
    (version "0.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dsmisc" version))
       (sha256
        (base32 "19760hcb5154rayhj72r48r7glh2qyaf178zkxplywmsw338kws4"))))
    (properties `((upstream-name . "dsmisc")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-rcpp))
    (home-page "https://cran.r-project.org/package=dsmisc")
    (synopsis "Data Science Box of Pandora Miscellaneous")
    (description
     "Tool collection for common and not so common data science use cases.  This
includes custom made algorithms for data management as well as value
calculations that are hard to find elsewhere because of their specificity but
would be a waste to get lost nonetheless.  Currently available functionality:
find sub-graphs in an edge list data.frame, find mode or modes in a vector of
values, extract (a) specific regular expression group(s), generate ISO time
stamps that play well with file names, or generate URL parameter lists by
expanding value combinations.")
    (license license:gpl2+)))

(define-public r-dsm
  (package
    (name "r-dsm")
    (version "2.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dsm" version))
       (sha256
        (base32 "159hlllbp4qy5dxmxgsjcl2ksflq7z7v1ra5d7piyanm9c632q8a"))))
    (properties `((upstream-name . "dsm")))
    (build-system r-build-system)
    (propagated-inputs (list r-statmod
                             r-plyr
                             r-numderiv
                             r-nlme
                             r-mrds
                             r-mgcv
                             r-ggplot2))
    (home-page "https://github.com/DistanceDevelopment/dsm")
    (synopsis "Density Surface Modelling of Distance Sampling Data")
    (description
     "Density surface modelling of line transect data.  A Generalized Additive
Model-based approach is used to calculate spatially-explicit estimates of animal
abundance from distance sampling (also presence/absence and strip transect)
data.  Several utility functions are provided for model checking, plotting and
variance estimation.")
    (license license:gpl2+)))

(define-public r-dslite
  (package
    (name "r-dslite")
    (version "1.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DSLite" version))
       (sha256
        (base32 "1xc9igwsxwiirg40br1qckai0lzhijfnpdrxg94r38hngb7r5cy2"))))
    (properties `((upstream-name . "DSLite")))
    (build-system r-build-system)
    (propagated-inputs (list r-rly r-r6 r-dsi))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/datashield/DSLite/")
    (synopsis "'DataSHIELD' Implementation on Local Datasets")
    (description
     "@code{DataSHIELD} is an infrastructure and series of R packages that enables the
remote and non-disclosive analysis of sensitive research data.  This
@code{DataSHIELD} Interface implementation is for analyzing datasets living in
the current R session.  The purpose of this is primarily for lightweight
@code{DataSHIELD} analysis package development.")
    (license license:lgpl2.1+)))

(define-public r-dslice
  (package
    (name "r-dslice")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dslice" version))
       (sha256
        (base32 "0h34bnji7ll2zh79d1yilj908mjgf27yify2kl2gapj9k499zc2v"))))
    (properties `((upstream-name . "dslice")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales r-rcpp r-ggplot2))
    (home-page "https://cran.r-project.org/package=dslice")
    (synopsis "Dynamic Slicing")
    (description
     "Dynamic slicing is a method designed for dependency detection between a
categorical variable and a continuous variable.  It could be applied for
non-parametric hypothesis testing and gene set enrichment analysis.")
    (license license:gpl2+)))

(define-public r-dsld
  (package
    (name "r-dsld")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dsld" version))
       (sha256
        (base32 "1qx5lj7fiaksfp4vc0n0dxjcjpijx5lp4c0ifmzrfsd67d5zhlbb"))))
    (properties `((upstream-name . "dsld")))
    (build-system r-build-system)
    (propagated-inputs (list r-sandwich
                             r-rmarkdown
                             r-regtools
                             r-ranger
                             r-qeml
                             r-plotly
                             r-kendall
                             r-gtools
                             r-ggplot2
                             r-freqparcoord
                             r-fairness
                             r-fairml))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/matloff/dsld")
    (synopsis "Data Science Looks at Discrimination")
    (description
     "Statistical and graphical tools for detecting and measuring discrimination and
bias, be it racial, gender, age or other.  Detection and remediation of bias in
machine learning algorithms.  Python interfaces available.")
    (license license:gpl2+)))

(define-public r-dslabs
  (package
    (name "r-dslabs")
    (version "0.8.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dslabs" version))
       (sha256
        (base32 "19nx8jjjadwhkk4wp3lv7xddq8pbj6l405xaxk4fhvgcvlxa65zk"))))
    (properties `((upstream-name . "dslabs")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2))
    (home-page "https://cran.r-project.org/package=dslabs")
    (synopsis "Data Science Labs")
    (description
     "Datasets and functions that can be used for data analysis practice, homework and
projects in data science courses and workshops.  26 datasets are available for
case studies in data visualization, statistical inference, modeling, linear
regression, data wrangling and machine learning.")
    (license license:artistic2.0)))

(define-public r-dsl
  (package
    (name "r-dsl")
    (version "0.1-7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DSL" version))
       (sha256
        (base32 "05wj3zypr2kqfbka930qnwnk2r43pqi13pbs5n6lm8vdq4zjblw4"))))
    (properties `((upstream-name . "DSL")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DSL")
    (synopsis "Distributed Storage and List")
    (description
     "An abstract DList class helps storing large list-type objects in a distributed
manner.  Corresponding high-level functions and methods for handling distributed
storage (DStorage) and lists allows for processing such DLists on distributed
systems efficiently.  In doing so it uses a well defined storage backend
implemented based on the DStorage class.")
    (license license:gpl3)))

(define-public r-dsjobtracker
  (package
    (name "r-dsjobtracker")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DSjobtracker" version))
       (sha256
        (base32 "09n7gxks3j2gx0yyzdnpxa6ncg2hv48v503z1d3qk3fwvcd6r0s1"))))
    (properties `((upstream-name . "DSjobtracker")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/thiyangt/DSjobtracker")
    (synopsis
     "What Skills and Qualifications are Required for Data Science Related Jobs?")
    (description
     "Dataset containing information about job listings for data science job roles.")
    (license (license:fsdg-compatible "CC BY 4.0"))))

(define-public r-dsims
  (package
    (name "r-dsims")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dsims" version))
       (sha256
        (base32 "0mqnpcs9bijkc0l6x6qssr527rh4j4ignlgvgrqxqgii3ikdx92j"))))
    (properties `((upstream-name . "dsims")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf
                             r-rstudioapi
                             r-rlang
                             r-purrr
                             r-mrds
                             r-mgcv
                             r-gridextra
                             r-ggplot2
                             r-dssd
                             r-dplyr
                             r-distance))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/DistanceDevelopment/dsims")
    (synopsis "Distance Sampling Simulations")
    (description
     "This package performs distance sampling simulations.  dsims repeatedly generates
instances of a user defined population within a given survey region.  It then
generates realisations of a survey design and simulates the detection process.
The data are then analysed so that the results can be compared for accuracy and
precision across all replications.  This process allows users to optimise survey
designs for their specific set of survey conditions.  The effects of uncertainty
in population distribution or parameters can be investigated under a number of
simulations so that users can be confident that they have achieved a robust
survey design before deploying vessels into the field.  The distance sampling
designs used in this package from dssd are detailed in Chapter 7 of Advanced
Distance Sampling, Buckland et.  al. (2008, ISBN-13: 978-0199225873).  General
distance sampling methods are detailed in Introduction to Distance Sampling:
Estimating Abundance of Biological Populations, Buckland et.  al. (2004,
ISBN-13: 978-0198509271).  Find out more about estimating animal/plant abundance
with distance sampling at <http://distancesampling.org/>.")
    (license license:gpl2+)))

(define-public r-dsi
  (package
    (name "r-dsi")
    (version "1.7.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DSI" version))
       (sha256
        (base32 "1pwsmql0d8grwm5whhf6gav14i9wj057msdshliwi52c2rvh2m9l"))))
    (properties `((upstream-name . "DSI")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6 r-progress r-cli))
    (home-page "https://github.com/datashield/DSI/")
    (synopsis "'DataSHIELD' Interface")
    (description
     "@code{DataSHIELD} is an infrastructure and series of R packages that enables the
remote and non-disclosive analysis of sensitive research data.  This package
defines the API that is to be implemented by @code{DataSHIELD} compliant data
repositories.")
    (license license:lgpl2.1+)))

(define-public r-dsem
  (package
    (name "r-dsem")
    (version "1.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dsem" version))
       (sha256
        (base32 "1zqywsa2ip48vpzbk1xml1glrihgfwf37z25pzs07xzj0ij1lwjy"))))
    (properties `((upstream-name . "dsem")))
    (build-system r-build-system)
    (propagated-inputs (list r-tmb r-sem r-rcppeigen r-matrix r-igraph))
    (native-inputs (list r-knitr))
    (home-page "https://james-thorson-noaa.github.io/dsem/")
    (synopsis "Fit Dynamic Structural Equation Models")
    (description
     "Applies dynamic structural equation models to time-series data with generic and
simplified specification for simultaneous and lagged effects.  Methods are
described in Thorson et al. (2024) \"Dynamic structural equation models
synthesize ecosystem dynamics constrained by ecological mechanisms.\".")
    (license license:gpl3)))

(define-public r-dsdp
  (package
    (name "r-dsdp")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dsdp" version))
       (sha256
        (base32 "0n0cyqzwv97wqq8m8a3qr6bg2p07ky9dm6hmlxwd2ggxrn3kmxv8"))))
    (properties `((upstream-name . "dsdp")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-ggplot2))
    (native-inputs (list r-rmarkdown r-knitr gfortran))
    (home-page "https://tsuchiya-lab.github.io/dsdp/")
    (synopsis "Density Estimation with Semidefinite Programming")
    (description
     "The models of probability density functions are Gaussian or exponential
distributions with polynomial correction terms.  Using a maximum likelihood
method, dsdp computes parameters of Gaussian or exponential distributions
together with degrees of polynomials by a grid search, and coefficient of
polynomials by a variant of semidefinite programming.  It adopts Akaike
Information Criterion for model selection.  See a vignette for a tutorial and
more on our Github repository <https://github.com/tsuchiya-lab/dsdp/>.")
    (license license:expat)))

(define-public r-dscore
  (package
    (name "r-dscore")
    (version "1.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dscore" version))
       (sha256
        (base32 "1skcmd2fh8s5d5qdj661niwa3cfd01i22kxxcf84awad0p1p8g57"))))
    (properties `((upstream-name . "dscore")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-stringi r-rcpparmadillo r-rcpp r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/d-score/dscore")
    (synopsis "D-Score for Child Development")
    (description
     "The D-score summarizes the child's performance on a set of milestones into a
single number.  The package implements four Rasch model keys to convert
milestone scores into a D-score.  It provides tools to calculate the D-score and
its precision from the child's milestone scores, to convert the D-score into the
Development-for-Age Z-score (DAZ) using age-conditional references, and to map
milestone names into a generic 9-position item naming convention.")
    (license license:agpl3)))

(define-public r-dsbayes
  (package
    (name "r-dsbayes")
    (version "2023.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DSBayes" version))
       (sha256
        (base32 "0sk5xfs13jxy4n3qgifh75bry1b53mm9gk1x14mpy2vw359cbqx4"))))
    (properties `((upstream-name . "DSBayes")))
    (build-system r-build-system)
    (propagated-inputs (list r-bb))
    (home-page "https://cran.r-project.org/package=DSBayes")
    (synopsis "Bayesian Subgroup Analysis in Clinical Trials")
    (description
     "Calculate posterior modes and credible intervals of parameters of the
Dixon-Simon model for subgroup analysis (with binary covariates) in clinical
trials.  For details of the methodology, please refer to D.O. Dixon and R. Simon
(1991), Biometrics, 47: 871-881.")
    (license license:gpl2+)))

(define-public r-dsample
  (package
    (name "r-dsample")
    (version "0.91.3.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dsample" version))
       (sha256
        (base32 "1f34gp5qic70fnv2ds3v9jk08ginbk9ivxddcvdaadr249lvln12"))))
    (properties `((upstream-name . "dsample")))
    (build-system r-build-system)
    (propagated-inputs (list r-mnormt r-mass))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dsample")
    (synopsis "Discretization-Based Direct Random Sample Generation")
    (description
     "Discretization-based random sampling algorithm that is useful for a complex
model in high dimension is implemented.  The normalizing constant of a target
distribution is not needed.  Posterior summaries are compared with those by
@code{OpenBUGS}'.  The method is described: Wang and Lee (2014)
<doi:10.1016/j.csda.2013.06.011> and exercised in Lee (2009)
<http://hdl.handle.net/1993/21352>.")
    (license license:gpl3)))

(define-public r-dsam
  (package
    (name "r-dsam")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DSAM" version))
       (sha256
        (base32 "1bm7wicpq372xnwlib18434cid90vy575zc4f4xgsy2vsm8f87ym"))))
    (properties `((upstream-name . "DSAM")))
    (build-system r-build-system)
    (propagated-inputs (list r-xgboost r-proc r-matrix r-kohonen r-caret))
    (home-page "https://github.com/lark-max/DSAM")
    (synopsis "Data Splitting Algorithms for Model Developments")
    (description
     "Providing six different algorithms that can be used to split the available data
into training, test and validation subsets with similar distribution for
hydrological model developments.  The @code{dataSplit}() function will help you
divide the data according to specific requirements, and you can refer to the
par.default() function to set the parameters for data splitting.  The
@code{getAUC}() function will help you measure the similarity of distribution
features between the data subsets.  For more information about the data
splitting algorithms, please refer to: Chen et al. (2022)
<doi:10.1016/j.jhydrol.2022.128340>, Zheng et al. (2022)
<doi:10.1029/2021WR031818>.")
    (license license:expat)))

(define-public r-dsairm
  (package
    (name "r-dsairm")
    (version "0.9.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DSAIRM" version))
       (sha256
        (base32 "0zp5dcfdzrywp252d1dcyvaxn8lygqs7hzxk0v9yzgahrbxnlvw9"))))
    (properties `((upstream-name . "DSAIRM")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml
                             r-shiny
                             r-rlang
                             r-plotly
                             r-nloptr
                             r-lhs
                             r-gridextra
                             r-ggplot2
                             r-dplyr
                             r-desolve
                             r-boot
                             r-adaptivetau))
    (native-inputs (list r-knitr))
    (home-page "https://ahgroup.github.io/DSAIRM/")
    (synopsis "Dynamical Systems Approach to Immune Response Modeling")
    (description
     "Simulation models (apps) of various within-host immune response scenarios.  The
purpose of the package is to help individuals learn about within-host infection
and immune response modeling from a dynamical systems perspective.  All apps
include explanations of the underlying models and instructions on what to do
with the models.")
    (license license:gpl3)))

(define-public r-dsaide
  (package
    (name "r-dsaide")
    (version "0.9.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DSAIDE" version))
       (sha256
        (base32 "01yljprcwkq0n7w9yr1xlkajyzyd0n8kmxkj80wcldp5mvqjmyxd"))))
    (properties `((upstream-name . "DSAIDE")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml
                             r-shiny
                             r-rlang
                             r-plotly
                             r-nloptr
                             r-lhs
                             r-gridextra
                             r-ggplot2
                             r-dplyr
                             r-desolve
                             r-adaptivetau))
    (native-inputs (list r-knitr))
    (home-page "https://ahgroup.github.io/DSAIDE/")
    (synopsis
     "Dynamical Systems Approach to Infectious Disease Epidemiology (Ecology/Evolution)")
    (description
     "Exploration of simulation models (apps) of various infectious disease
transmission dynamics scenarios.  The purpose of the package is to help
individuals learn about infectious disease epidemiology (ecology/evolution) from
a dynamical systems perspective.  All apps include explanations of the
underlying models and instructions on what to do with the models.")
    (license license:gpl3)))

(define-public r-dsa
  (package
    (name "r-dsa")
    (version "1.0.12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dsa" version))
       (sha256
        (base32 "16lqqm0lcgpkzkj7d0akamzap85aj4dyj5rs5fkb5b9bjqa5r4c5"))))
    (properties `((upstream-name . "dsa")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-xts
                             r-tsoutliers
                             r-timedate
                             r-seastests
                             r-rjava
                             r-reshape2
                             r-r2html
                             r-htmlwidgets
                             r-gridextra
                             r-ggplot2
                             r-forecast
                             r-dygraphs))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dsa")
    (synopsis "Seasonal Adjustment of Daily Time Series")
    (description
     "Seasonal- and calendar adjustment of time series with daily frequency using the
DSA approach developed by Ollech, Daniel (2018): Seasonal adjustment of daily
time series.  Bundesbank Discussion Paper 41/2018.")
    (license license:gpl3)))

(define-public r-ds4psy
  (package
    (name "r-ds4psy")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ds4psy" version))
       (sha256
        (base32 "1l5qqcpzad2nnhzzcb43slgmdg08v830l5np8mc7qh4wlig1x95l"))))
    (properties `((upstream-name . "ds4psy")))
    (build-system r-build-system)
    (propagated-inputs (list r-unikn r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://bookdown.org/hneth/ds4psy/")
    (synopsis "Data Science for Psychologists")
    (description
     "All datasets and functions required for the examples and exercises of the book
\"Data Science for Psychologists\" (by Hansjoerg Neth, Konstanz University, 2022),
available at <https://bookdown.org/hneth/ds4psy/>.  The book and course
introduce principles and methods of data science to students of psychology and
other biological or social sciences.  The ds4psy package primarily provides
datasets, but also functions for data generation and manipulation (e.g., of text
and time data) and graphics that are used in the book and its exercises.  All
functions included in ds4psy are designed to be explicit and instructive, rather
than efficient or elegant.")
    (license license:cc-by-sa4.0)))

(define-public r-ds
  (package
    (name "r-ds")
    (version "4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ds" version))
       (sha256
        (base32 "1iic5fb27cnhsa83zg28hydrhzc01i9z0711xvk95c3gv7mbfp2p"))))
    (properties `((upstream-name . "ds")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ds")
    (synopsis "Descriptive Statistics")
    (description
     "This package performs various analyzes of descriptive statistics, including
correlations, graphics and tables.")
    (license license:gpl2)))

(define-public r-drviaspcn
  (package
    (name "r-drviaspcn")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DRviaSPCN" version))
       (sha256
        (base32 "1m111n2ycr5z3dy3mhkyxfw0fq74lny0kajk91d0klcpixfv7y2g"))))
    (properties `((upstream-name . "DRviaSPCN")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp
                             r-pheatmap
                             r-igraph
                             r-gsva
                             r-clusterprofiler
                             r-chemminer))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DRviaSPCN")
    (synopsis "Drug Repurposing in Cancer via a Subpathway Crosstalk Network")
    (description
     "This package provides a systematic biology tool was developed to repurpose drugs
via a subpathway crosstalk network.  The operation modes include 1) calculating
centrality scores of SPs in the context of gene expression data to reflect the
influence of SP crosstalk, 2) evaluating drug-disease reverse association based
on disease- and drug-induced SPs weighted by the SP crosstalk, 3) identifying
cancer candidate drugs through perturbation analysis.  There are also several
functions used to visualize the results.")
    (license license:gpl2+)))

(define-public r-drumr
  (package
    (name "r-drumr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drumr" version))
       (sha256
        (base32 "09xi3sf424bpq10fq25j209dylfbi1lfd911r44ffadkxzvp5p1s"))))
    (properties `((upstream-name . "drumr")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-audio))
    (home-page "https://cran.r-project.org/package=drumr")
    (synopsis "Turn R into a Drum Machine")
    (description
     "Includes various functions for playing drum sounds.  beat() plays a drum sound
from one of the six included drum kits.  tempo() sets spacing between calls to
beat() in bpm.  Together the two functions can be used to create many different
drum patterns.")
    (license license:gpl3)))

(define-public r-drugutilisation
  (package
    (name "r-drugutilisation")
    (version "0.7.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DrugUtilisation" version))
       (sha256
        (base32 "17896mf0mryqrmlllkh7dhf65id31n26z4h757kdsb2wj32my7k9"))))
    (properties `((upstream-name . "DrugUtilisation")))
    (build-system r-build-system)
    (propagated-inputs (list r-visomopresults
                             r-tidyr
                             r-stringr
                             r-rlang
                             r-purrr
                             r-patientprofiles
                             r-omopgenerics
                             r-lifecycle
                             r-glue
                             r-dplyr
                             r-dbplyr
                             r-codelistgenerator
                             r-clock
                             r-cli
                             r-checkmate
                             r-cdmconnector))
    (native-inputs (list r-knitr))
    (home-page "https://darwin-eu-dev.github.io/DrugUtilisation/")
    (synopsis
     "Summarise Patient-Level Drug Utilisation in Data Mapped to the OMOP Common Data Model")
    (description
     "Summarise patient-level drug utilisation cohorts using data mapped to the
Observational Medical Outcomes Partnership (OMOP) common data model.  New users
and prevalent users cohorts can be generated and their characteristics,
indication and drug use summarised.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-drugsim2dr
  (package
    (name "r-drugsim2dr")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DrugSim2DR" version))
       (sha256
        (base32 "1sphg3imdyr71amwqzmzzp6h1ai2m6rm87l08mv70i6jlznwf9kr"))))
    (properties `((upstream-name . "DrugSim2DR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-sp
                             r-rvest
                             r-reshape2
                             r-pheatmap
                             r-igraph
                             r-fastmatch
                             r-chemminer))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DrugSim2DR")
    (synopsis "Predict Drug Functional Similarity to Drug Repurposing")
    (description
     "This package provides a systematic biology tool was developed to repurpose drugs
via a drug-drug functional similarity network. @code{DrugSim2DR} first predict
drug-drug functional similarity in the context of specific disease, and then
using the similarity constructed a weighted drug similarity network.  Finally,
it used a network propagation algorithm on the network to identify drugs with
significant target abnormalities as candidate drugs.")
    (license license:gpl2+)))

(define-public r-drugprepr
  (package
    (name "r-drugprepr")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drugprepr" version))
       (sha256
        (base32 "07401dqw4krqh3rv7y13526n0xjdlaw14gcxwranksjchmqjd3ij"))))
    (properties `((upstream-name . "drugprepr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-sqldf
                             r-rlang
                             r-purrr
                             r-dplyr
                             r-doseminer
                             r-desctools))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=drugprepr")
    (synopsis
     "Prepare Electronic Prescription Record Data to Estimate Drug Exposure")
    (description
     "Prepare prescription data (such as from the Clinical Practice Research Datalink)
into an analysis-ready format, with start and stop dates for each patient's
prescriptions.  Based on Pye et al (2018) <doi:10.1002/pds.4440>.")
    (license license:expat)))

(define-public r-drugexposurediagnostics
  (package
    (name "r-drugexposurediagnostics")
    (version "1.0.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DrugExposureDiagnostics" version))
       (sha256
        (base32 "1isn6q7k8ll2w9nbizj46c287hacwpc31a0kh20qrif9xa4akwp0"))))
    (properties `((upstream-name . "DrugExposureDiagnostics")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-shiny
                             r-rlang
                             r-omopgenerics
                             r-magrittr
                             r-glue
                             r-drugutilisation
                             r-dplyr
                             r-checkmate
                             r-cdmconnector))
    (native-inputs (list r-knitr))
    (home-page "https://darwin-eu.github.io/DrugExposureDiagnostics/")
    (synopsis "Diagnostics for OMOP Common Data Model Drug Records")
    (description
     "Ingredient specific diagnostics for drug exposure records in the Observational
Medical Outcomes Partnership (OMOP) common data model.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-drugdevelopr
  (package
    (name "r-drugdevelopr")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drugdevelopR" version))
       (sha256
        (base32 "0mbr0s826wmknw4n50qbg5i9b5x969s9h7w21nni17i074iqjhpb"))))
    (properties `((upstream-name . "drugdevelopR")))
    (build-system r-build-system)
    (propagated-inputs (list r-progressr
                             r-mvtnorm
                             r-msm
                             r-mass
                             r-iterators
                             r-foreach
                             r-doparallel
                             r-cubature))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Sterniii3/drugdevelopR")
    (synopsis "Utility-Based Optimal Phase II/III Drug Development Planning")
    (description
     "Plan optimal sample size allocation and go/no-go decision rules for phase II/III
drug development programs with time-to-event, binary or normally distributed
endpoints when assuming fixed treatment effects or a prior distribution for the
treatment effect, using methods from Kirchner et al. (2016)
<doi:10.1002/sim.6624> and Preussler (2020).  Optimal is in the sense of maximal
expected utility, where the utility is a function taking into account the
expected cost and benefit of the program.  It is possible to extend to more
complex settings with bias correction (Preussler S et al. (2020)
<doi:10.1186/s12874-020-01093-w>), multiple phase III trials (Preussler et al.
(2019) <doi:10.1002/bimj.201700241>), multi-arm trials (Preussler et al. (2019)
<doi:10.1080/19466315.2019.1702092>), and multiple endpoints (Kieser et al.
(2018) <doi:10.1002/pst.1861>).")
    (license license:expat)))

(define-public r-drugdemand
  (package
    (name "r-drugdemand")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drugDemand" version))
       (sha256
        (base32 "1gmpvcrcs1j2m98dxppa0jss781dpscw89ffh8d6yamm385p0951"))))
    (properties `((upstream-name . "drugDemand")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-stringr
                             r-rlang
                             r-rcpp
                             r-purrr
                             r-plotly
                             r-nlme
                             r-mvtnorm
                             r-mass
                             r-l1pack
                             r-foreach
                             r-eventpred
                             r-erify
                             r-dplyr
                             r-dorng
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=drugDemand")
    (synopsis "Drug Demand Forecasting")
    (description
     "This package performs drug demand forecasting by modeling drug dispensing data
while taking into account predicted enrollment and treatment discontinuation
dates.  The gap time between randomization and the first drug dispensing visit
is modeled using interval-censored exponential, Weibull, log-logistic, or
log-normal distributions (Anderson-Bergman (2017) <doi:10.18637/jss.v081.i12>).
The number of skipped visits is modeled using Poisson, zero-inflated Poisson, or
negative binomial distributions (Zeileis, Kleiber & Jackman (2008)
<doi:10.18637/jss.v027.i08>).  The gap time between two consecutive drug
dispensing visits given the number of skipped visits is modeled using linear
regression based on least squares or least absolute deviations (Birkes & Dodge
(1993, ISBN:0-471-56881-3)).  The number of dispensed doses is modeled using
linear or linear mixed-effects models (@code{McCulloch} & Searle (2001,
ISBN:0-471-19364-X)).")
    (license license:gpl2+)))

(define-public r-drquality
  (package
    (name "r-drquality")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DRquality" version))
       (sha256
        (base32 "1rr9341y6nf8qdaabfwzbjgwmsb7z1i514cz4x2z5hj9qxyjiy4c"))))
    (properties `((upstream-name . "DRquality")))
    (build-system r-build-system)
    (propagated-inputs (list r-databionicswarm))
    (home-page "https://cran.r-project.org/package=DRquality")
    (synopsis "Quality Measurements for Dimensionality Reduction")
    (description
     "Several quality measurements for investigating the performance of dimensionality
reduction methods are provided here.  In addition a new quality measurement
called Gabriel classification error is made accessible, which was published in
Thrun, M. C., MÃ¤rte, J., & Stier, Q: \"Analyzing Quality Measurements for
Dimensionality Reduction\" (2023), Machine Learning and Knowledge Extraction
(MAKE), <DOI:10.3390/make5030056>.")
    (license license:gpl3)))

(define-public r-drpop
  (package
    (name "r-drpop")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drpop" version))
       (sha256
        (base32 "1gh0w1a59070g9mmck4fp9591vfw23c5nlj3jrkxwarp4vfy1dqp"))))
    (properties `((upstream-name . "drpop")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-superlearner
                             r-stringr
                             r-reshape2
                             r-ranger
                             r-nnls
                             r-nnet
                             r-janitor
                             r-ggplot2
                             r-gam
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=drpop")
    (synopsis "Efficient and Doubly Robust Population Size Estimation")
    (description
     "Estimation of the total population size from capture-recapture data efficiently
and with low bias implementing the methods from Das M, Kennedy EH, and Jewell NP
(2021) <@code{arXiv:2104.14091>}.  The estimator is doubly robust against errors
in the estimation of the intermediate nuisance parameters.  Users can choose
from the flexible estimation models provided in the package, or use any other
preferred model.")
    (license license:gpl3)))

(define-public r-drought
  (package
    (name "r-drought")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drought" version))
       (sha256
        (base32 "1xarpzfcj4zldyfzl30vxkgqwcbi17nly6vbxsm7z8vigjslx6ma"))))
    (properties `((upstream-name . "drought")))
    (build-system r-build-system)
    (propagated-inputs (list r-corrplot r-copula))
    (home-page "https://cran.r-project.org/package=drought")
    (synopsis "Statistical Modeling and Assessment of Drought")
    (description
     "Provide tools for drought monitoring based on univariate and multivariate
drought indicators.Statistical drought prediction based on Ensemble Streamflow
Prediction (ESP), drought risk assessments, and drought propagation are also
provided.  Please see Hao Zengchao et al. (2017)
<doi:10.1016/j.envsoft.2017.02.008>.")
    (license license:gpl3)))

(define-public r-drord
  (package
    (name "r-drord")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drord" version))
       (sha256
        (base32 "0xi85s6y78d54qv3cw7q72dz5kcs8cc8nyjyaxr5h6pfpzi2l8i9"))))
    (properties `((upstream-name . "drord")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam r-ordinal r-mass r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/benkeser/drord")
    (synopsis "Doubly-Robust Estimators for Ordinal Outcomes")
    (description
     "Efficient covariate-adjusted estimators of quantities that are useful for
establishing the effects of treatments on ordinal outcomes.")
    (license license:expat)))

(define-public r-droptest
  (package
    (name "r-droptest")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "droptest" version))
       (sha256
        (base32 "1wlfhj6c4pb5mcybyd2bcn55y3azk7dv7d7il97qwbhl8kf59csl"))))
    (properties `((upstream-name . "droptest")))
    (build-system r-build-system)
    (propagated-inputs (list r-data-table))
    (home-page "https://github.com/chadr/droptest")
    (synopsis "Simulates LOX Drop Testing")
    (description
     "Generates simulated data representing the LOX drop testing process (also known
as impact testing).  A simulated process allows for accelerated study of test
behavior.  Functions are provided to simulate trials, test series, and groups of
test series.  Functions for creating plots specific to this process are also
included.  Test attributes and criteria can be set arbitrarily.  This work is
not endorsed by or affiliated with NASA. See \"ASTM G86-17, Standard Test Method
for Determining Ignition Sensitivity of Materials to Mechanical Impact in
Ambient Liquid Oxygen and Pressurized Liquid and Gaseous Oxygen Environments\"
<doi:10.1520/G0086-17>.")
    (license license:expat)))

(define-public r-dropr
  (package
    (name "r-dropr")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dropR" version))
       (sha256
        (base32 "159kw9wxglc7rbb5bvvg1ixi0j1y22179wn7g40k9ahpfvfmbqy4"))))
    (properties `((upstream-name . "dropR")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-shiny r-lifecycle r-ggplot2
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://iscience-kn.github.io/dropR/")
    (synopsis "Dropout Analysis by Condition")
    (description
     "Analysis and visualization of dropout between conditions in surveys and (online)
experiments.  Features include computation of dropout statistics, comparing
dropout between conditions (e.g. Chi square), analyzing survival (e.g.
Kaplan-Meier estimation), comparing conditions with the most different rates of
dropout (Kolmogorov-Smirnov) and visualizing the result of each in designated
plotting functions.  Sources: Andrea Frick, Marie-Terese Baechtiger &
Ulf-Dietrich Reips (2001)
<https://www.researchgate.net/publication/223956222_Financial_incentives_personal_information_and_drop-out_in_online_studies>;
Ulf-Dietrich Reips (2002) \"Standards for Internet-Based Experimenting\"
<doi:10.1027//1618-3169.49.4.243>.")
    (license license:gpl3+)))

(define-public r-dropout
  (package
    (name "r-dropout")
    (version "2.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dropout" version))
       (sha256
        (base32 "09rcmxcdl8g7fcgv86c4mv5gd0399vd17a8g58x039s7yz52ys3j"))))
    (properties `((upstream-name . "dropout")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/hendr1km/dropout")
    (synopsis "Handling Incomplete Responses in Survey Data Analysis")
    (description
     "Offers robust tools to identify and manage incomplete responses in survey
datasets, thereby enhancing the quality and reliability of research findings.")
    (license license:expat)))

(define-public r-dromics
  (package
    (name "r-dromics")
    (version "2.6-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DRomics" version))
       (sha256
        (base32 "0bhs89hwzylg6w86s89i96l36k8z3k496w2nq38bri1b7vy22hbi"))))
    (properties `((upstream-name . "DRomics")))
    (build-system r-build-system)
    (propagated-inputs (list r-summarizedexperiment
                             r-rlang
                             r-limma
                             r-ggplot2
                             r-ggfortify
                             r-deseq2))
    (native-inputs (list r-knitr))
    (home-page "https://lbbe.univ-lyon1.fr/fr/dromics")
    (synopsis "Dose Response for Omics")
    (description
     "Several functions are provided for dose-response (or concentration-response)
characterization from omics data.  DRomics is especially dedicated to omics data
obtained using a typical dose-response design, favoring a great number of tested
doses (or concentrations) rather than a great number of replicates (no need of
replicates).  DRomics provides functions 1) to check, normalize and or transform
data, 2) to select monotonic or biphasic significantly responding items (e.g.
probes, metabolites), 3) to choose the best-fit model among a predefined family
of monotonic and biphasic models to describe each selected item, 4) to derive a
benchmark dose or concentration and a typology of response from each fitted
curve.  In the available version data are supposed to be single-channel
microarray data in log2, RNAseq data in raw counts, or already pretreated
continuous omics data (such as metabolomic data) in log scale.  In order to link
responses across biological levels based on a common method, DRomics also
handles apical data as long as they are continuous and follow a normal
distribution for each dose or concentration, with a common standard error.  For
further details see Delignette-Muller et al (2023) <DOI:10.24072/pcjournal.325>
and Larras et al (2018) <DOI:10.1021/acs.est.8b04752>.")
    (license license:gpl2+)))

(define-public r-droll
  (package
    (name "r-droll")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "droll" version))
       (sha256
        (base32 "0gd1vnvkjdsw7gz4czi4g9zq5080awfr4dy2srgksh4ah4ki4vm3"))))
    (properties `((upstream-name . "droll")))
    (build-system r-build-system)
    (propagated-inputs (list r-ryacas))
    (home-page "https://cran.r-project.org/package=droll")
    (synopsis "Analyze Roll Distributions")
    (description
     "This package provides a toolkit for parsing dice notation, analyzing rolls,
calculating success probabilities, and plotting outcome distributions.")
    (license license:expat)))

(define-public r-driver
  (package
    (name "r-driver")
    (version "0.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "driveR" version))
       (sha256
        (base32 "00cwzy097wbl1k3sw3nfn0kzb6af7hyzwaznvlckf77g7kw86bmi"))))
    (properties `((upstream-name . "driveR")))
    (build-system r-build-system)
    (propagated-inputs (list r-txdb-hsapiens-ucsc-hg38-knowngene
                             r-txdb-hsapiens-ucsc-hg19-knowngene
                             r-s4vectors
                             r-rlang
                             r-randomforest
                             r-org-hs-eg-db
                             r-genomicranges
                             r-genomicfeatures
                             r-genomeinfodb
                             r-caret))
    (native-inputs (list r-knitr))
    (home-page "https://egeulgen.github.io/driveR/")
    (synopsis "Prioritizing Cancer Driver Genes Using Genomics Data")
    (description
     "Cancer genomes contain large numbers of somatic alterations but few genes drive
tumor development.  Identifying cancer driver genes is critical for precision
oncology.  Most of current approaches either identify driver genes based on
mutational recurrence or using estimated scores predicting the functional
consequences of mutations. @code{driveR} is a tool for personalized or batch
analysis of genomic data for driver gene prioritization by combining genomic
information and prior biological knowledge.  As features, @code{driveR} uses
coding impact metaprediction scores, non-coding impact scores, somatic copy
number alteration scores, hotspot gene/double-hit gene condition, phenolyzer
gene scores and memberships to cancer-related KEGG pathways.  It uses these
features to estimate cancer-type-specific probability for each gene of being a
cancer driver using the related task of a multi-task learning classification
model.  The method is described in detail in Ulgen E, Sezerman OU. 2021.
@code{driveR}: @code{driveR}: a novel method for prioritizing cancer driver
genes using somatic genomics data.  BMC Bioinformatics
<doi:10.1186/s12859-021-04203-7>.")
    (license license:expat)))

(define-public r-drip
  (package
    (name "r-drip")
    (version "2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DRIP" version))
       (sha256
        (base32 "18cais2n8kx1hpb66kqpjlvjx750rhgfvx4h4jjixmb8aqnf7p48"))))
    (properties `((upstream-name . "DRIP")))
    (build-system r-build-system)
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=DRIP")
    (synopsis "Discontinuous Regression and Image Processing")
    (description
     "This package provides a collection of functions that perform jump regression and
image analysis such as denoising, deblurring and jump detection.  The
implemented methods are based on the following research: Qiu, P. (1998)
<doi:10.1214/aos/1024691468>, Qiu, P. and Yandell, B. (1997) <doi:
10.1080/10618600.1997.10474746>, Qiu, P. (2009) <doi:
10.1007/s10463-007-0166-9>, Kang, Y. and Qiu, P. (2014) <doi:
10.1080/00401706.2013.844732>, Qiu, P. and Kang, Y. (2015) <doi:
10.5705/ss.2014.054>, Kang, Y., Mukherjee, P.S. and Qiu, P. (2018) <doi:
10.1080/00401706.2017.1415975>, Kang, Y. (2020) <doi:
10.1080/10618600.2019.1665536>.")
    (license license:gpl2+)))

(define-public r-drimmr
  (package
    (name "r-drimmr")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drimmR" version))
       (sha256
        (base32 "0fi0ifb9y2jfb347684fd9pjfgn4b693yb5sqbcfpf2z7jvknsi1"))))
    (properties `((upstream-name . "drimmR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyverse
                             r-seqinr
                             r-reshape2
                             r-rdpack
                             r-ggplot2
                             r-future
                             r-foreach
                             r-dplyr
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=drimmR")
    (synopsis
     "Estimation, Simulation and Reliability of Drifting Markov Models")
    (description
     "This package performs the drifting Markov models (DMM) which are non-homogeneous
Markov models designed for modeling the heterogeneities of sequences in a more
flexible way than homogeneous Markov chains or even hidden Markov models.  In
this context, we developed an R package dedicated to the estimation, simulation
and the exact computation of associated reliability of drifting Markov models.
The implemented methods are described in Vergne, N. (2008),
<doi:10.2202/1544-6115.1326> and Barbu, V.S., Vergne, N. (2019)
<doi:10.1007/s11009-018-9682-8> .")
    (license license:gpl3)))

(define-public r-drillr
  (package
    (name "r-drillr")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DrillR" version))
       (sha256
        (base32 "0n7pim5kk0wfdjcc67v4vvdb7wyhn5bcgi2a12nbyfyydss7pk1g"))))
    (properties `((upstream-name . "DrillR")))
    (build-system r-build-system)
    (propagated-inputs (list r-httr))
    (home-page "https://cran.r-project.org/package=DrillR")
    (synopsis "R Driver for Apache Drill")
    (description
     "This package provides a R driver for Apache Drill<https://drill.apache.org>,
which could connect to the Apache Drill
cluster<https://drill.apache.org/docs/installing-drill-on-the-cluster> or
drillbit<https://drill.apache.org/docs/embedded-mode-prerequisites> and get
result(in data frame) from the SQL query and check the current configuration
status.  This link <https://drill.apache.org/docs> contains more information
about Apache Drill.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-drifter
  (package
    (name "r-drifter")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drifter" version))
       (sha256
        (base32 "1xsp8cm02wd8zink0jqrdaii7s2dh0rw96rs6k8zr2g0341wmfba"))))
    (properties `((upstream-name . "drifter")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-ingredients r-dplyr r-dalex))
    (home-page "https://ModelOriented.github.io/drifter/")
    (synopsis
     "Concept Drift and Concept Shift Detection for Predictive Models")
    (description
     "Concept drift refers to the change in the data distribution or in the
relationships between variables over time.  drifter calculates distances between
variable distributions or variable relations and identifies both types of drift.
 Key functions are: calculate_covariate_drift() checks distance between
corresponding variables in two datasets, calculate_residuals_drift() checks
distance between residual distributions for two models, calculate_model_drift()
checks distance between partial dependency profiles for two models,
check_drift() executes all checks against drift.  drifter is a part of the
@code{DrWhy.AI} universe (Biecek 2018) <@code{arXiv:1806.08915>}.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-driftbursthypothesis
  (package
    (name "r-driftbursthypothesis")
    (version "0.4.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DriftBurstHypothesis" version))
       (sha256
        (base32 "1pmsbv1rl79s520nxj536m8gf7xyfjskj8r88rxmxscbgp8c1xz2"))))
    (properties `((upstream-name . "DriftBurstHypothesis")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-xts r-rcpparmadillo r-rcpp))
    (home-page "https://github.com/emilsjoerup/DriftBurstHypothesis")
    (synopsis "Calculates the Test-Statistic for the Drift Burst Hypothesis")
    (description
     "Calculates the T-Statistic for the drift burst hypothesis from the working paper
Christensen, Oomen and Reno (2018) <DOI:10.2139/ssrn.2842535>.  The authors
MATLAB code is available upon request, see:
<https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2842535>.")
    (license license:gpl3)))

(define-public r-drhur
  (package
    (name "r-drhur")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drhur" version))
       (sha256
        (base32 "06zy2acgmhfc1criid35ci1802zl77qcif2vrhn0w8syixsbjiq8"))))
    (properties `((upstream-name . "drhur")))
    (build-system r-build-system)
    (propagated-inputs (list r-learnr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=drhur")
    (synopsis "Learning R with Dr. Hu")
    (description "Tutarials of R learning easily and happily.")
    (license license:expat)))

(define-public r-drhotnet
  (package
    (name "r-drhotnet")
    (version "2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DRHotNet" version))
       (sha256
        (base32 "0r7lbzmk05k65kgasz3ka1ic4hqdv65yryf2vz5c4x1yrqvsh9sg"))))
    (properties `((upstream-name . "DRHotNet")))
    (build-system r-build-system)
    (propagated-inputs (list r-spdep
                             r-spatstat-linnet
                             r-spatstat-geom
                             r-spatstat
                             r-sp
                             r-raster
                             r-pbsmapping))
    (home-page "https://cran.r-project.org/package=DRHotNet")
    (synopsis "Differential Risk Hotspots in a Linear Network")
    (description
     "This package performs the identification of differential risk hotspots
(Briz-Redon et al.  2019) <doi:10.1016/j.aap.2019.105278> along a linear
network.  Given a marked point pattern lying on the linear network, the method
implemented uses a network-constrained version of kernel density estimation
(@code{McSwiggan} et al.  2017) <doi:10.1111/sjos.12255> to approximate the
probability of occurrence across space for the type of event specified by the
user through the marks of the pattern (Kelsall and Diggle 1995)
<doi:10.2307/3318678>.  The goal is to detect microzones of the linear network
where the type of event indicated by the user is overrepresented.")
    (license license:gpl2)))

(define-public r-drglm
  (package
    (name "r-drglm")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drglm" version))
       (sha256
        (base32 "1v3n546ivvh5hfwlz7m1wn6jdgcd9yjnricah1y7v6r15zy3jyds"))))
    (properties `((upstream-name . "drglm")))
    (build-system r-build-system)
    (propagated-inputs (list r-speedglm r-nnet))
    (native-inputs (list r-knitr))
    (home-page "https://nayemmh.github.io/drglm/")
    (synopsis
     "Fitting Linear and Generalized Linear Models in \"Divide and Recombine\" Approach to Large Data Sets")
    (description
     "To overcome the memory limitations for fitting linear (LM) and Generalized
Linear Models (GLMs) to large data sets, this package implements the Divide and
Recombine (D&R) strategy.  It basically divides the entire large data set into
suitable subsets manageable in size and then fits model to each subset.
Finally, results from each subset are aggregated to obtain the final estimate.
This package also supports fitting GLMs to data sets that cannot fit into memory
and provides methods for fitting GLMs under linear regression, binomial
regression, Poisson regression, and multinomial logistic regression settings.
Respective models are fitted using different D&R strategies as described by: Xi,
Lin, and Chen (2009) <doi:10.1109/TKDE.2008.186>, Xi, Lin and Chen (2006)
<doi:10.1109/TKDE.2006.196>, Zuo and Li (2018) <doi:10.4236/ojs.2018.81003>,
Karim, M.R., Islam, M.A. (2019) <doi:10.1007/978-981-13-9776-9>.")
    (license license:gpl3+)))

(define-public r-drgee
  (package
    (name "r-drgee")
    (version "1.1.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drgee" version))
       (sha256
        (base32 "0hy7887mvlxh73zk2yzp46bqakq924n940j21lw25jgygmzz1176"))))
    (properties `((upstream-name . "drgee")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rcpparmadillo r-rcpp r-nleqslv
                             r-data-table))
    (home-page "https://cran.r-project.org/package=drgee")
    (synopsis "Doubly Robust Generalized Estimating Equations")
    (description
     "Fit restricted mean models for the conditional association between an exposure
and an outcome, given covariates.  Three methods are implemented: O-estimation,
where a nuisance model for the association between the covariates and the
outcome is used; E-estimation where a nuisance model for the association between
the covariates and the exposure is used, and doubly robust (DR) estimation where
both nuisance models are used.  In DR-estimation, the estimates will be
consistent when at least one of the nuisance models is correctly specified, not
necessarily both.  For more information, see Zetterqvist and SjÃ¶lander (2015)
<doi:10.1515/em-2014-0021>.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-drf
  (package
    (name "r-drf")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drf" version))
       (sha256
        (base32 "13b31rynknzirnvgygs1ar5968xdh8dhg60ibn0g359gnzadn7ad"))))
    (properties `((upstream-name . "drf")))
    (build-system r-build-system)
    (propagated-inputs (list r-transport r-rcppeigen r-rcpp r-matrix
                             r-fastdummies))
    (home-page "https://github.com/lorismichel/drf")
    (synopsis "Distributional Random Forests")
    (description
     "An implementation of distributional random forests as introduced in Cevid &
Michel & Meinshausen & Buhlmann (2020) <@code{arXiv:2005.14458>}.")
    (license license:gpl3)))

(define-public r-dregar
  (package
    (name "r-dregar")
    (version "0.1.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DREGAR" version))
       (sha256
        (base32 "15cplshs85r0z659mc7xmj5db7vc95wxs01c34isc22p8z0a287i"))))
    (properties `((upstream-name . "DREGAR")))
    (build-system r-build-system)
    (propagated-inputs (list r-msgps))
    (home-page "http://hamedhaseli.webs.com.")
    (synopsis
     "Regularized Estimation of Dynamic Linear Regression in the Presence of Autocorrelated Residuals (DREGAR)")
    (description
     "This package provides a penalized/non-penalized implementation for dynamic
regression in the presence of autocorrelated residuals (DREGAR) using iterative
penalized/ordinary least squares.  It applies Mallows CP, AIC, BIC and GCV to
select the tuning parameters.")
    (license license:gpl2+)))

(define-public r-dreamerr
  (package
    (name "r-dreamerr")
    (version "1.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dreamerr" version))
       (sha256
        (base32 "11va0bwi8r3qv7cw5zjci0i7876lh02bzf5rdfn6sfv223yllpiy"))))
    (properties `((upstream-name . "dreamerr")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringmagic r-formula))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dreamerr")
    (synopsis "Error Handling Made Easy")
    (description
     "Set of tools to facilitate package development and make R a more user-friendly
place.  Mostly for developers (or anyone who writes/shares functions).  Provides
a simple, powerful and flexible way to check the arguments passed to functions.
The developer can easily describe the type of argument needed.  If the user
provides a wrong argument, then an informative error message is prompted with
the requested type and the problem clearly stated--saving the user a lot of time
in debugging.")
    (license license:gpl3)))

(define-public r-dreamer
  (package
    (name "r-dreamer")
    (version "3.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dreamer" version))
       (sha256
        (base32 "10yvdg5nkw4nawy9hdqyrsgh01xga8l3hn3qi1sbjzniv7903v7d"))))
    (properties `((upstream-name . "dreamer")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-rootsolve
                             r-rlang
                             r-rjags
                             r-purrr
                             r-ggplot2
                             r-ellipsis
                             r-dplyr
                             r-coda))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/rich-payne/dreamer")
    (synopsis "Dose Response Models for Bayesian Model Averaging")
    (description
     "Fits (longitudinal) dose-response models utilizing a Bayesian model averaging
approach as outlined in Gould (2019) <doi:10.1002/bimj.201700211> for both
continuous and binary responses.  Functions for plotting and calculating various
posterior quantities (e.g. posterior mean, quantiles, probability of minimum
efficacious dose, etc.) are also implemented.  Copyright Eli Lilly and Company
(2019).")
    (license license:expat)))

(define-public r-drdrtest
  (package
    (name "r-drdrtest")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DRDRtest" version))
       (sha256
        (base32 "1vrvwr441w526a80s0r2fwqlllvn05ir8v2152jz2wxrwhnpq1s0"))))
    (properties `((upstream-name . "DRDRtest")))
    (build-system r-build-system)
    (propagated-inputs (list r-superlearner r-kernsmooth))
    (home-page "https://cran.r-project.org/package=DRDRtest")
    (synopsis
     "Nonparametric Doubly Robust Test for Continuous Treatment Effect")
    (description
     "Implement the statistical test proposed in Weng et al. (2021) to test whether
the average treatment effect curve is constant and whether a discrete covariate
is a significant effect modifier.")
    (license license:gpl3+)))

(define-public r-drdimont
  (package
    (name "r-drdimont")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DrDimont" version))
       (sha256
        (base32 "1ax70932zn0q21drbp8wr5xy5xjnaqvkqd2cp4cb7bl9f6bcsz9p"))))
    (properties `((upstream-name . "DrDimont")))
    (build-system r-build-system)
    (propagated-inputs (list r-wgcna
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-rfast
                             r-reticulate
                             r-readr
                             r-magrittr
                             r-igraph
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DrDimont")
    (synopsis
     "Drug Response Prediction from Differential Multi-Omics Networks")
    (description
     "While it has been well established that drugs affect and help patients
differently, personalized drug response predictions remain challenging.
Solutions based on single omics measurements have been proposed, and networks
provide means to incorporate molecular interactions into reasoning.  However,
how to integrate the wealth of information contained in multiple omics layers
still poses a complex problem.  We present a novel network analysis pipeline,
@code{DrDimont}, Drug response prediction from Differential analysis of
multi-omics networks.  It allows for comparative conclusions between two
conditions and translates them into differential drug response predictions.
@code{DrDimont} focuses on molecular interactions.  It establishes
condition-specific networks from correlation within an omics layer that are then
reduced and combined into heterogeneous, multi-omics molecular networks.  A
novel semi-local, path-based integration step ensures integrative conclusions.
Differential predictions are derived from comparing the condition-specific
integrated networks. @code{DrDimont's} predictions are explainable, i.e.,
molecular differences that are the source of high differential drug scores can
be retrieved.  Our proposed pipeline leverages multi-omics data for differential
predictions, e.g. on drug response, and includes prior information on
interactions.  The case study presented in the vignette uses data published by
Krug (2020) <doi:10.1016/j.cell.2020.10.036>.  The package license applies only
to the software and explicitly not to the included data.")
    (license license:expat)))

(define-public r-drdid
  (package
    (name "r-drdid")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DRDID" version))
       (sha256
        (base32 "0sjjg4i9lq48na3xwsk0jv8s2jh5b70052ymlkxgha4hpvg9kh4y"))))
    (properties `((upstream-name . "DRDID")))
    (build-system r-build-system)
    (propagated-inputs (list r-trust r-rcpp r-fastglm r-bmisc))
    (home-page "https://psantanna.com/DRDID/")
    (synopsis "Doubly Robust Difference-in-Differences Estimators")
    (description
     "This package implements the locally efficient doubly robust
difference-in-differences (@code{DiD}) estimators for the average treatment
effect proposed by Sant'Anna and Zhao (2020)
<doi:10.1016/j.jeconom.2020.06.003>.  The estimator combines inverse probability
weighting and outcome regression estimators (also implemented in the package) to
form estimators with more attractive statistical properties.  Two different
estimation methods can be used to estimate the nuisance functions.")
    (license license:gpl3)))

(define-public r-drda
  (package
    (name "r-drda")
    (version "2.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drda" version))
       (sha256
        (base32 "0npw800swbdv3s0qj345101y5c8f7am40w8cf7krmyh3jj50cyx0"))))
    (properties `((upstream-name . "drda")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/albertopessia/drda")
    (synopsis "Dose-Response Data Analysis")
    (description
     "Fit logistic functions to observed dose-response continuous data and evaluate
goodness-of-fit measures.  See Malyutina A., Tang J., and Pessia A. (2023)
<doi:10.18637/jss.v106.i04>.")
    (license license:expat)))

(define-public r-drcte
  (package
    (name "r-drcte")
    (version "1.0.30")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drcte" version))
       (sha256
        (base32 "0gpzpmk5v1lr03gl710kp4d4ldfskjr5s66wcl00abg3kz8jpixn"))))
    (properties `((upstream-name . "drcte")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-survival
                             r-sandwich
                             r-plyr
                             r-nor1mix
                             r-multcomp
                             r-mclust
                             r-mass
                             r-lmtest
                             r-drc
                             r-dplyr))
    (home-page "https://www.statforbiology.com")
    (synopsis "Statistical Approaches for Time-to-Event Data in Agriculture")
    (description
     "This package provides a specific and comprehensive framework for the analyses of
time-to-event data in agriculture.  Fit non-parametric and parametric
time-to-event models.  Compare time-to-event curves for different experimental
groups.  Plots and other displays.  It is particularly tailored to the analyses
of data from germination and emergence assays.  The methods are described in
Onofri et al. (2020) \"A unified framework for the analysis of germination,
emergence, and other time-to-event data in weed science\"\", Weed Science, 70,
259-271 <doi:10.1017/wsc.2022.8>.")
    (license license:gpl2+)))

(define-public r-drcseedgerm
  (package
    (name "r-drcseedgerm")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drcSeedGerm" version))
       (sha256
        (base32 "19fyfw5r994l5sbfrh8ar4kqc27j0pgdks1cp7liql6dw5iliyp4"))))
    (properties `((upstream-name . "drcSeedGerm")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-plyr
                             r-mvtnorm
                             r-drcte
                             r-drc
                             r-dplyr))
    (home-page "https://www.statforbiology.com")
    (synopsis
     "Utilities for Data Analyses in Seed Germination/Emergence Assays")
    (description
     "Utility functions to be used to analyse datasets obtained from seed
germination/emergence assays.  Fits several types of seed germination/emergence
models, including those reported in Onofri et al. (2018)
\"Hydrothermal-time-to-event models for seed germination\", European Journal of
Agronomy, 101, 129-139 <doi:10.1016/j.eja.2018.08.011>.  Contains several
datasets for practicing.")
    (license license:gpl2+)))

(define-public r-drclust
  (package
    (name "r-drclust")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drclust" version))
       (sha256
        (base32 "04qi123vdj33dfhgxmwc0c2viwa74lr4x1kj85rgbvvsqhwnp1kz"))))
    (properties `((upstream-name . "drclust")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo
                             r-rcpp
                             r-pheatmap
                             r-fpc
                             r-factoextra
                             r-cluster))
    (home-page "https://cran.r-project.org/package=drclust")
    (synopsis "Simultaneous Clustering and (or) Dimensionality Reduction")
    (description
     "This package provides methods for simultaneous clustering and dimensionality
reduction such as: Double k-means, Reduced k-means, Factorial k-means,
Clustering with Disjoint PCA but also methods for exclusively dimensionality
reduction: Disjoint PCA, Disjoint FA. The statistical methods implemented refer
to the following articles: de Soete G., Carroll J. (1994) \"K-means clustering in
a low-dimensional Euclidean space\" <doi:10.1007/978-3-642-51175-2_24> ; Vichi M.
(2001) \"Double k-means Clustering for Simultaneous Classification of Objects and
Variables\" <doi:10.1007/978-3-642-59471-7_6> ; Vichi M., Kiers H.A.L. (2001)
\"Factorial k-means analysis for two-way data\"
<doi:10.1016/S0167-9473(00)00064-5> ; Vichi M., Saporta G. (2009) \"Clustering
and disjoint principal component analysis\" <doi:10.1016/j.csda.2008.05.028> ;
Vichi M. (2017) \"Disjoint factor analysis with cross-loadings\"
<doi:10.1007/s11634-016-0263-9>.")
    (license license:gpl3+)))

(define-public r-drcarlate
  (package
    (name "r-drcarlate")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drcarlate" version))
       (sha256
        (base32 "05yfyjkxrayz9cmlk7qnbcqgjfxnbkmc2wkbarr9l8m47zzhda8n"))))
    (properties `((upstream-name . "drcarlate")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-splus2r
                             r-purrr
                             r-pracma
                             r-mass
                             r-glmnet))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=drcarlate")
    (synopsis
     "Improving Estimation Efficiency in CAR with Imperfect Compliance")
    (description
     "We provide a list of functions for replicating the results of the Monte Carlo
simulations and empirical application of Jiang et al. (2022).  In particular, we
provide corresponding functions for generating the three types of random data
described in this paper, as well as all the estimation strategies.  Detailed
information about the data generation process and estimation strategy can be
found in Jiang et al. (2022) <doi:10.48550/@code{arXiv.2201.13004>}.")
    (license license:expat)))

(define-public r-drbats
  (package
    (name "r-drbats")
    (version "0.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DrBats" version))
       (sha256
        (base32 "1623h8s6y4klq8xmj480ga2wl6n4c2f26v1dwysyvcrk6lnaghdm"))))
    (properties `((upstream-name . "DrBats")))
    (build-system r-build-system)
    (propagated-inputs (list r-sde
                             r-rstan
                             r-matrix
                             r-mass
                             r-coda
                             r-ade4))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DrBats")
    (synopsis "Data Representation: Bayesian Approach That's Sparse")
    (description
     "Feed longitudinal data into a Bayesian Latent Factor Model to obtain a low-rank
representation.  Parameters are estimated using a Hamiltonian Monte Carlo
algorithm with STAN. See G. Weinrott, B. Fontez, N. Hilgert and S. Holmes,
\"Bayesian Latent Factor Model for Functional Data Analysis\", Actes des
@code{JdS} 2016.")
    (license license:gpl3)))

(define-public r-drayl
  (package
    (name "r-drayl")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DRAYL" version))
       (sha256
        (base32 "0cf5pyx6nwh8srdylpnmymv3dr67fm6qqpwd1hvj1wmyfc8fznpp"))))
    (properties `((upstream-name . "DRAYL")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmutil r-rconics r-pracma r-cubature))
    (home-page "https://cran.r-project.org/package=DRAYL")
    (synopsis "Computation of Rayleigh Densities of Arbitrary Dimension")
    (description
     "We offer an implementation of the series representation put forth in \"A series
representation for multidimensional Rayleigh distributions\" by Wiegand and
Nadarajah <DOI: 10.1002/dac.3510>.  Furthermore we have implemented an
integration approach proposed by Beaulieu et al.  for 3 and 4-dimensional
Rayleigh densities (Beaulieu, Zhang, \"New simplest exact forms for the 3D and 4D
multivariate Rayleigh PDFs with applications to antenna array geometrics\", <DOI:
10.1109/TCOMM.2017.2709307>).")
    (license license:gpl2)))

(define-public r-drawsample
  (package
    (name "r-drawsample")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drawsample" version))
       (sha256
        (base32 "018v4amapfwxx6k4s9drcv2vwil7cplnkwlrhy9djc0a02jxx2l5"))))
    (properties `((upstream-name . "drawsample")))
    (build-system r-build-system)
    (propagated-inputs (list r-xlsx
                             r-tibble
                             r-shinydashboard
                             r-shinycssloaders
                             r-shiny
                             r-readxl
                             r-psych
                             r-moments
                             r-lattice
                             r-dplyr))
    (home-page "https://github.com/atalay-k/drawsample")
    (synopsis "Draw Samples with the Desired Properties from a Data Set")
    (description
     "This package provides a tool to sample data with the desired properties.Samples
can be drawn by purposive sampling with determining distributional conditions,
such as deviation from normality (skewness and kurtosis), and sample size in
quantitative research studies.  For purposive sampling, a researcher has
something in mind and participants that fit the purpose of the study are
included (Etikan,Musa, & Alkassim, 2015)
<doi:10.11648/j.ajtas.20160501.11>.Purposive sampling can be useful for
answering many research questions (Klar & Leeper, 2019)
<doi:10.1002/9781119083771.ch21>.")
    (license license:expat)))

(define-public r-drawr
  (package
    (name "r-drawr")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DRaWR" version))
       (sha256
        (base32 "1pschc911zrcgy6vmh9aylz79qfifxvxrm5gxwah7xv50plpar78"))))
    (properties `((upstream-name . "DRaWR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rocr r-matrix))
    (home-page "https://cran.r-project.org/package=DRaWR")
    (synopsis "Discriminative Random Walk with Restart")
    (description
     "We present D@code{RaWR}, a network-based method for ranking genes or properties
related to a given gene set.  Such related genes or properties are identified
from among the nodes of a large, heterogeneous network of biological
information.  Our method involves a random walk with restarts, performed on an
initial network with multiple node and edge types, preserving more of the
original, specific property information than current methods that operate on
homogeneous networks.  In this first stage of our algorithm, we find the
properties that are the most relevant to the given gene set and extract a
subnetwork of the original network, comprising only the relevant properties.  We
then rerank genes by their similarity to the given gene set, based on a second
random walk with restarts, performed on the above subnetwork.")
    (license license:gpl2)))

(define-public r-drawer
  (package
    (name "r-drawer")
    (version "0.2.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drawer" version))
       (sha256
        (base32 "165w0lk6kp0hw85y1q3wj50jn5jbi4rn00vgz8q0wy68qw2ymhh5"))))
    (properties `((upstream-name . "drawer")))
    (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-stringr
                             r-shiny
                             r-magrittr
                             r-htmltools
                             r-glue
                             r-bsplus))
    (native-inputs (list esbuild))
    (home-page "https://github.com/lz100/drawer")
    (synopsis "An Interactive HTML Image Editing Tool")
    (description
     "An interactive image editing tool that can be added as part of the HTML in
Shiny, R markdown or any type of HTML document.  Often times, plots, photos are
embedded in the web application/file.  drawer can take screenshots of these
image-like elements, or any part of the HTML document and send to an image
editing space called canvas to allow users immediately edit the screenshot(s)
within the same document.  Users can quickly combine, compare different
screenshots, upload their own images and maybe make a scientific figure.")
    (license license:gpl3+)))

(define-public r-draw
  (package
    (name "r-draw")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "draw" version))
       (sha256
        (base32 "0kbz8rcgygl4fhmljzaan5jl7wjvfljcaykm7q9lw9s6m78p06gz"))))
    (properties `((upstream-name . "draw")))
    (build-system r-build-system)
    (home-page "https://github.com/rrwen/draw")
    (synopsis "Wrapper Functions for Producing Graphics")
    (description
     "This package provides a set of user-friendly wrapper functions for creating
consistent graphics and diagrams with lines, common shapes, text, and page
settings.  Compatible with and based on the R grid package.")
    (license license:expat)))

(define-public r-drape
  (package
    (name "r-drape")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drape" version))
       (sha256
        (base32 "0y4y6vvskizghqf78d1vr0skac0ks3yb83m9fgn8i3wmgqrhws19"))))
    (properties `((upstream-name . "drape")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=drape")
    (synopsis "Doubly Robust Average Partial Effects")
    (description
     "Doubly robust average partial effect estimation.  This implementation contains
methods for adding additional smoothness to plug-in regression procedures and
for estimating score functions using smoothing splines.  Details of the method
can be found in Harvey Klyne and Rajen D. Shah (2023) <@code{arXiv:2308.09207>}.")
    (license license:expat)))

(define-public r-dramaanalysis
  (package
    (name "r-dramaanalysis")
    (version "3.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DramaAnalysis" version))
       (sha256
        (base32 "0nsnwais0r592c50nphfzkr1bbygl67mriwsx7dxbvmpdsswlvl1"))))
    (properties `((upstream-name . "DramaAnalysis")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-tokenizers
                             r-stringr
                             r-reshape2
                             r-readr
                             r-httr
                             r-git2r
                             r-data-table))
    (home-page "https://github.com/quadrama/DramaAnalysis")
    (synopsis "Analysis of Dramatic Texts")
    (description
     "Analysis of preprocessed dramatic texts, with respect to literary research.  The
package provides functions to analyze and visualize information about
characters, stage directions, the dramatic structure and the text itself.  The
dramatic texts are expected to be in CSV format, which can be installed from
within the package, sample texts are provided.  The package and the reasoning
behind it are described in Reiter et al. (2017) <doi:10.18420/in2017_119>.")
    (license license:gpl3+)))

(define-public r-drake
  (package
    (name "r-drake")
    (version "7.13.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "drake" version))
       (sha256
        (base32 "1nd8vqlc2hzxlh8vlqjvgls3gc2ya8vmx7nyci5g1nib1l07gxrq"))))
    (properties `((upstream-name . "drake")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-txtq
                             r-tidyselect
                             r-storr
                             r-rlang
                             r-igraph
                             r-digest
                             r-base64url))
    (home-page "https://github.com/ropensci/drake")
    (synopsis "Pipeline Toolkit for Reproducible Computation at Scale")
    (description
     "This package provides a general-purpose computational engine for data analysis,
drake rebuilds intermediate data objects when their dependencies change, and it
skips work when the results are already up to date.  Not every execution starts
from scratch, there is native support for parallel and distributed computing,
and completed projects have tangible evidence that they are reproducible.
Extensive documentation, from beginner-friendly tutorials to practical examples
and more, is available at the reference website
<https://docs.ropensci.org/drake/> and the online manual
<https://books.ropensci.org/drake/>.")
    (license license:gpl3)))

(define-public r-dragular
  (package
    (name "r-dragular")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dragulaR" version))
       (sha256
        (base32 "1cw5v7m1b4pxsizsjb3zdzhydxj577p6q5fcjklsvpzmiixzlyav"))))
    (properties `((upstream-name . "dragulaR")))
    (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-shinyjs r-shiny r-htmlwidgets))
    (native-inputs (list esbuild))
    (home-page "https://dragular.zstat.pl/")
    (synopsis
     "Drag and Drop Elements in 'Shiny' using 'Dragula Javascript Library'")
    (description
     "Move elements between containers in Shiny without explicitly using
@code{JavaScript}'.  It can be used to build custom inputs or to change the
positions of user interface elements like plots or tables.")
    (license license:gpl2)))

(define-public r-dragracer
  (package
    (name "r-dragracer")
    (version "0.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dragracer" version))
       (sha256
        (base32 "0ka3p72c3brrla7dawm4anyr073kgiy39ip5bdig9888gwiwjccq"))))
    (properties `((upstream-name . "dragracer")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dragracer")
    (synopsis "Data Sets for RuPaul's Drag Race")
    (description
     "These are data sets for the hit TV show, @code{RuPaul's} Drag Race.  Data right
now include episode-level data, contestant-level data, and
episode-contestant-level data.  This is a work in progress, and a love letter of
a kind to @code{RuPaul's} Drag Race and the performers that have appeared on the
show.  This may not be the most productive use of my time, but I have tenure and
what are you going to do about it? I think there is at least some value in this
package if it allows the show's fandom to learn more about the R programming
language around its contents.")
    (license license:gpl2)))

(define-public r-dragonking
  (package
    (name "r-dragonking")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dragonking" version))
       (sha256
        (base32 "01b01wd1s2b8sa9f0kfbf2pbzhaqra7xxskigqh3vlj389xqm1id"))))
    (properties `((upstream-name . "dragonking")))
    (build-system r-build-system)
    (home-page "https://github.com/rrrlw/dragonking")
    (synopsis "Statistical Tools to Identify Dragon Kings")
    (description
     "Statistical tests and test statistics to identify events in a dataset that are
dragon kings (DKs).  The statistical methods in this package were reviewed in
Wheatley & Sornette (2015) <doi:10.2139/ssrn.2645709>.")
    (license license:gpl3)))

(define-public r-dracor
  (package
    (name "r-dracor")
    (version "0.2.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dracor" version))
       (sha256
        (base32 "1zs7xfjdx3anrvslfkx483k0swac7rq8y7n7gaws6ap94qy4xrk8"))))
    (properties `((upstream-name . "dracor")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://github.com/natverse/dracor")
    (synopsis "Decode Draco Format 3D Mesh Data")
    (description
     "Decodes meshes and point cloud data encoded by the Draco mesh compression
library from Google.  Note that this is only designed for basic decoding and not
intended as a full scale wrapping of the Draco library.")
    (license license:asl2.0)))

(define-public r-dr4pl
  (package
    (name "r-dr4pl")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dr4pl" version))
       (sha256
        (base32 "1nmy8mxxrmwzw826wvnn4rrm64xal9jr160yqiqj41zmb241q4b6"))))
    (properties `((upstream-name . "dr4pl")))
    (build-system r-build-system)
    (propagated-inputs (list r-tensor
                             r-rlang
                             r-rdpack
                             r-matrix
                             r-glue
                             r-ggplot2
                             r-generics))
    (native-inputs (list r-knitr))
    (home-page "https://bitbucket.org/dittmerlab/dr4pl")
    (synopsis
     "Dose Response Data Analysis using the 4 Parameter Logistic (4pl) Model")
    (description
     "Models the relationship between dose levels and responses in a pharmacological
experiment using the 4 Parameter Logistic model.  Traditional packages on
dose-response modelling such as drc and nplr often draw errors due to
convergence failure especially when data have outliers or non-logistic shapes.
This package provides robust estimation methods that are less affected by
outliers and other initialization methods that work well for data lacking
logistic shapes.  We provide the bounds on the parameters of the 4PL model that
prevent parameter estimates from diverging or converging to zero and base their
justification in a statistical principle.  These methods are used as remedies to
convergence failure problems.  Gadagkar, S. R. and Call, G. B. (2015)
<doi:10.1016/j.vascn.2014.08.006> Ritz, C. and Baty, F. and Streibig, J. C. and
Gerhard, D. (2015) <doi:10.1371/journal.pone.0146021>.")
    (license license:gpl2+)))

(define-public r-dr-sc
  (package
    (name "r-dr-sc")
    (version "3.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DR.SC" version))
       (sha256
        (base32 "076halm823dlrj95hqq3ibdb645vd2w68mixi36wdnh7ngr7ih1f"))))
    (properties `((upstream-name . "DR.SC")))
    (build-system r-build-system)
    (propagated-inputs (list r-spatstat-geom
                             r-seurat
                             r-s4vectors
                             r-rcpparmadillo
                             r-rcpp
                             r-rcolorbrewer
                             r-purrr
                             r-mclust
                             r-matrix
                             r-mass
                             r-irlba
                             r-giraf
                             r-ggplot2
                             r-cowplot
                             r-compquadform))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/feiyoung/DR.SC")
    (synopsis "Joint Dimension Reduction and Spatial Clustering")
    (description
     "Joint dimension reduction and spatial clustering is conducted for Single-cell
RNA sequencing and spatial transcriptomics data, and more details can be
referred to Wei Liu, Xu Liao, Yi Yang, Huazhen Lin, Joe Yeong, Xiang Zhou,
Xingjie Shi and Jin Liu. (2022) <doi:10.1093/nar/gkac219>.  It is not only
computationally efficient and scalable to the sample size increment, but also is
capable of choosing the smoothness parameter and the number of clusters as well.")
    (license license:gpl3)))

(define-public r-dr
  (package
    (name "r-dr")
    (version "3.0.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dr" version))
       (sha256
        (base32 "0dmz4h7biwrn480i66f6jm3c6p4pjvfv24pw1aixvab2vcdkqlnf"))))
    (properties `((upstream-name . "dr")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=dr")
    (synopsis "Methods for Dimension Reduction for Regression")
    (description
     "Functions, methods, and datasets for fitting dimension reduction regression,
using slicing (methods SAVE and SIR), Principal Hessian Directions (phd, using
residuals and the response), and an iterative IRE. Partial methods, that
condition on categorical predictors are also available.  A variety of tests, and
stepwise deletion of predictors, is also included.  Also included is code for
computing permutation tests of dimension.  Adding additional methods of
estimating dimension is straightforward.  For documentation, see the vignette in
the package.  With version 3.0.4, the arguments for dr.step have been modified.")
    (license license:gpl2+)))

(define-public r-dqtg-seq
  (package
    (name "r-dqtg-seq")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dQTG.seq" version))
       (sha256
        (base32 "0by13x0583mxsb1sxl0p4qhzrwzcri7jrc80pgyr7nmpk0cvmsnj"))))
    (properties `((upstream-name . "dQTG.seq")))
    (build-system r-build-system)
    (propagated-inputs (list r-writexl
                             r-vroom
                             r-stringr
                             r-qtl
                             r-openxlsx
                             r-foreach
                             r-doparallel
                             r-data-table
                             r-bb))
    (home-page "https://cran.r-project.org/package=dQTG.seq")
    (synopsis
     "BSA Software for Detecting All Types of QTLs in BC, DH, RIL and F2")
    (description
     "The new (@code{dQTG.seq1} and @code{dQTG.seq2}) and existing (@code{SmoothLOD},
G', @code{deltaSNP} and ED) bulked segregant analysis methods are used to
identify various types of quantitative trait loci for complex traits via extreme
phenotype individuals in bi-parental segregation populations (F2, backcross,
doubled haploid and recombinant inbred line).  The numbers of marker alleles in
extreme low and high pools are used in existing methods to identify
trait-related genes, while the numbers of marker alleles and genotypes in
extreme low and high pools are used in the new methods to construct a new
statistic Gw for identifying trait-related genes. @code{dQTG-seq2} is feasible
to identify extremely over-dominant and small-effect genes in F2.  Li P, Li G,
Zhang YW, Zuo JF, Liu JY, Zhang YM (2022, <doi: 10.1016/j.xplc.2022.100319>).")
    (license license:gpl2+)))

(define-public r-dqastats
  (package
    (name "r-dqastats")
    (version "0.3.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DQAstats" version))
       (sha256
        (base32 "0slp3kq2g4djdfxqx40afxcycyncmdxw757pyrm8anfnpxx4rdvz"))))
    (properties `((upstream-name . "DQAstats")))
    (build-system r-build-system)
    (propagated-inputs (list r-tinytex
                             r-quarto
                             r-parsedate
                             r-magrittr
                             r-knitr
                             r-kableextra
                             r-jsonlite
                             r-future-apply
                             r-future
                             r-dizutils
                             r-diztools
                             r-data-table))
    (native-inputs (list r-quarto))
    (home-page "https://github.com/miracum/dqa-dqastats")
    (synopsis "Core Functions for Data Quality Assessment")
    (description
     "Perform data quality assessment ('DQA') of electronic health records ('EHR').
Publication: Kapsner et al. (2021) <doi:10.1055/s-0041-1733847>.")
    (license license:gpl3)))

(define-public r-dqagui
  (package
    (name "r-dqagui")
    (version "0.2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DQAgui" version))
       (sha256
        (base32 "05qik0zm7ghrn75msrkfi20lxdk9bqjvwwf765ajpfaph5wmmxk5"))))
    (properties `((upstream-name . "DQAgui")))
    (build-system r-build-system)
    (propagated-inputs (list r-waiter
                             r-shinywidgets
                             r-shinyjs
                             r-shinyfiles
                             r-shinydashboard
                             r-shinyalert
                             r-shiny
                             r-parsedate
                             r-magrittr
                             r-lubridate
                             r-knitr
                             r-jsonlite
                             r-dt
                             r-dqastats
                             r-dizutils
                             r-diztools
                             r-daterangepicker
                             r-data-table))
    (home-page "https://github.com/miracum/dqa-dqagui")
    (synopsis "Graphical User Interface for Data Quality Assessment")
    (description
     "This package provides a graphical user interface (GUI) to the functions
implemented in the R package DQAstats'.  Publication: Mang et al. (2021)
<doi:10.1186/s12911-022-01961-z>.")
    (license license:gpl3)))

(define-public r-dptree
  (package
    (name "r-dptree")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DPtree" version))
       (sha256
        (base32 "0d7zf695lwkx4gv50f08cbi3p3mjjay0qgrbmvybf9m15i4zmyd7"))))
    (properties `((upstream-name . "DPtree")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-plyr r-mcmcpack r-mass))
    (home-page "https://cran.r-project.org/package=DPtree")
    (synopsis "Dirichlet-Based Polya Tree")
    (description
     "This package contains functions to perform copula estimation by the
non-parametric Bayesian method, Dirichlet-based Polya Tree.  See Ning (2018)
<doi:10.1080/00949655.2017.1421194>.")
    (license license:expat)))

(define-public r-dptm
  (package
    (name "r-dptm")
    (version "1.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DPTM" version))
       (sha256
        (base32 "1qjk6q4kx7mlzmp15gz468ky6jia3pf16jxyzjhf857z4yi5szl6"))))
    (properties `((upstream-name . "DPTM")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppeigen
                             r-rcpp
                             r-purrr
                             r-parabar
                             r-mass
                             r-coda
                             r-bayesiantools))
    (home-page "https://github.com/HujieBai/DPTM")
    (synopsis "Dynamic Panel Multiple Threshold Model with Fixed Effects")
    (description
     "Compute the fixed effects dynamic panel threshold model suggested by
RamÃ­rez-RondÃ¡n (2020) <doi:10.1080/07474938.2019.1624401>, and dynamic panel
linear model suggested by Hsiao et al. (2002)
<doi:10.1016/S0304-4076(01)00143-9>, where maximum likelihood type estimators
are used.  Multiple threshold estimation based on Markov Chain Monte Carlo
(MCMC) is allowed, and model selection of linear model, threshold model and
multiple threshold model is also allowed.")
    (license license:gpl3+)))

(define-public r-dpseg
  (package
    (name "r-dpseg")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dpseg" version))
       (sha256
        (base32 "19k7w6ln72qriwxdjx9a9cxpxbkqqja69r17zpwxz6qkw60ly4z9"))))
    (properties `((upstream-name . "dpseg")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://gitlab.com/raim/dpseg/")
    (synopsis "Piecewise Linear Segmentation by Dynamic Programming")
    (description
     "Piecewise linear segmentation of ordered data by a dynamic programming
algorithm.  The algorithm was developed for time series data, e.g. growth
curves, and for genome-wide read-count data from next generation sequencing, but
is broadly applicable.  Generic implementations of dynamic programming routines
allow to scan for optimal segmentation parameters and test custom segmentation
criteria (\"scoring functions\").")
    (license license:gpl2+)))

(define-public r-dprop
  (package
    (name "r-dprop")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dprop" version))
       (sha256
        (base32 "0fvghjblm6giq72qqn20qwlw4ki9lrxagsy0jjbiinf51rdrhc8y"))))
    (properties `((upstream-name . "dprop")))
    (build-system r-build-system)
    (propagated-inputs (list r-vares r-extradistr))
    (home-page "https://cran.r-project.org/package=dprop")
    (synopsis "Computation of Some Important Distributional Properties")
    (description
     "Generally, most of the packages specify the probability density function,
cumulative distribution function, quantile function, and random numbers
generation of the probability distributions.  The present package allows to
compute some important distributional properties, including the first four
ordinary and central moments, Pearson's coefficient of skewness and kurtosis,
the mean and variance, coefficient of variation, median, and quartile deviation
at some parametric values of several well-known and extensively used probability
distributions.")
    (license license:gpl2)))

(define-public r-dpqmpfr
  (package
    (name "r-dpqmpfr")
    (version "0.3-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DPQmpfr" version))
       (sha256
        (base32 "0m0dyiy0mj1rg59lk90kk7lnhvgxs2k9ycbpc8sxwx3raf20gdy6"))))
    (properties `((upstream-name . "DPQmpfr")))
    (build-system r-build-system)
    (propagated-inputs (list r-sfsmisc r-rmpfr r-gmp r-dpq))
    (home-page "https://specfun.r-forge.r-project.org/")
    (synopsis
     "DPQ (Density, Probability, Quantile) Distribution Computations using MPFR")
    (description
     "An extension to the DPQ package with computations for DPQ (Density (pdf),
Probability (cdf) and Quantile) functions, where the functions here partly use
the Rmpfr package and hence the underlying MPFR and GMP C libraries.")
    (license license:gpl2+)))

(define-public r-dpq
  (package
    (name "r-dpq")
    (version "0.5-9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DPQ" version))
       (sha256
        (base32 "04bmsqp4mkrf4y1s161ql77f2zpqi66cyqyz9xpzgdf0dizsvn50"))))
    (properties `((upstream-name . "DPQ")))
    (build-system r-build-system)
    (propagated-inputs (list r-sfsmisc))
    (native-inputs (list gfortran))
    (home-page "https://specfun.r-forge.r-project.org/")
    (synopsis "Density, Probability, Quantile ('DPQ') Computations")
    (description
     "Computations for approximations and alternatives for the DPQ (Density (pdf),
Probability (cdf) and Quantile) functions for probability distributions in R.
Primary focus is on (central and non-central) beta, gamma and related
distributions such as the chi-squared, F, and t. -- For several distribution
functions, provide functions implementing formulas from Johnson, Kotz, and Kemp
(1992) <doi:10.1002/bimj.4710360207> and Johnson, Kotz, and Balakrishnan (1995)
for discrete or continuous distributions respectively.  This is for the use of
researchers in these numerical approximation implementations, notably for my own
use in order to improve standard R pbeta(), qgamma(), ..., etc:
{'\"dpq\"'-functions}.")
    (license license:gpl2+)))

(define-public r-dppmix
  (package
    (name "r-dppmix")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dppmix" version))
       (sha256
        (base32 "1gq51kix0jln25gr6bffzdy24fhn6cd3gmyl3jlmvqvni4vwswy7"))))
    (properties `((upstream-name . "dppmix")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm))
    (home-page "https://bitbucket.org/djhshih/dppmix")
    (synopsis "Determinantal Point Process Mixture Models")
    (description
     "Multivariate Gaussian mixture model with a determinant point process prior to
promote the discovery of parsimonious components from observed data.  See Xu,
Mueller, Telesca (2016) <doi:10.1111/biom.12482>.")
    (license license:gpl3+)))

(define-public r-dppack
  (package
    (name "r-dppack")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DPpack" version))
       (sha256
        (base32 "1qhrxy676i13mqxzmgmd82n2hrjdck9scr95kgnpxydwyml2pybp"))))
    (properties `((upstream-name . "DPpack")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmutil
                             r-rdpack
                             r-r6
                             r-nloptr
                             r-mass
                             r-ggplot2
                             r-e1071
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=DPpack")
    (synopsis
     "Differentially Private Statistical Analysis and Machine Learning")
    (description
     "An implementation of common statistical analysis and models with differential
privacy (Dwork et al., 2006a) <doi:10.1007/11681878_14> guarantees.  The package
contains, for example, functions providing differentially private computations
of mean, variance, median, histograms, and contingency tables.  It also
implements some statistical models and machine learning algorithms such as
linear regression (Kifer et al., 2012)
<https://proceedings.mlr.press/v23/kifer12.html> and SVM (Chaudhuri et al.,
2011) <https://jmlr.org/papers/v12/chaudhuri11a.html>.  In addition, it
implements some popular randomization mechanisms, including the Laplace
mechanism (Dwork et al., 2006a) <doi:10.1007/11681878_14>, Gaussian mechanism
(Dwork et al., 2006b) <doi:10.1007/11761679_29>, analytic Gaussian mechanism
(Balle & Wang, 2018) <https://proceedings.mlr.press/v80/balle18a.html>, and
exponential mechanism (@code{McSherry} & Talwar, 2007)
<doi:10.1109/FOCS.2007.66>.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-dpp
  (package
    (name "r-dpp")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DPP" version))
       (sha256
        (base32 "1qalcm4gwh03qpy07d0p323ccq8xmk04v6z30g7wg6ic613bqg7m"))))
    (properties `((upstream-name . "DPP")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-coda))
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=DPP")
    (synopsis
     "Inference of Parameters of Normal Distributions from a Mixture of Normals")
    (description
     "This MCMC method takes a data numeric vector (Y) and assigns the elements of Y
to a (potentially infinite) number of normal distributions.  The individual
normal distributions from a mixture of normals can be inferred.  Following the
method described in Escobar (1994) <doi:10.2307/2291223> we use a Dirichlet
Process Prior (DPP) to describe stochastically our prior assumptions about the
dimensionality of the data.")
    (license license:expat)))

(define-public r-dpmr
  (package
    (name "r-dpmr")
    (version "0.1.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dpmr" version))
       (sha256
        (base32 "1cnjywkvjb4fhbf4shjmsrq47f1fg2x21hcm1q5512bm0wg9i6jd"))))
    (properties `((upstream-name . "dpmr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rio r-magrittr r-jsonlite r-httr r-digest))
    (home-page "http://cran.r-project.org/package=dpmr")
    (synopsis "Data Package Manager for R")
    (description
     "Create, install, and summarise data packages that follow the Open Knowledge
Foundation's Data Package Protocol.")
    (license license:gpl3)))

(define-public r-dpm
  (package
    (name "r-dpm")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dpm" version))
       (sha256
        (base32 "1wg492r19rd1hplq6ccngwr0z615m4yx5jln0v01gbz4pm47dpmi"))))
    (properties `((upstream-name . "dpm")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-rlang
                             r-panelr
                             r-lavaan
                             r-jtools
                             r-formula
                             r-dplyr
                             r-crayon))
    (home-page "https://github.com/jacob-long/dpm")
    (synopsis "Dynamic Panel Models Fit with Maximum Likelihood")
    (description
     "This package implements the dynamic panel models described by Allison, Williams,
and Moral-Benito (2017 <doi:10.1177/2378023117710578>) in R. This class of
models uses structural equation modeling to specify dynamic (lagged dependent
variable) models with fixed effects for panel data.  Additionally, models may
have predictors that are only weakly exogenous, i.e., are affected by prior
values of the dependent variable.  Options also allow for random effects,
dropping the lagged dependent variable, and a number of other specification
choices.")
    (license license:expat)))

(define-public r-dplyrassist
  (package
    (name "r-dplyrassist")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dplyrAssist" version))
       (sha256
        (base32 "1lqizh70b1apyr4578917gv6s0i7p84ak96a57kvwipmh36a4ywn"))))
    (properties `((upstream-name . "dplyrAssist")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyverse
                             r-tidyr
                             r-stringr
                             r-shinywidgets
                             r-shinyace
                             r-shiny
                             r-rstudioapi
                             r-plyr
                             r-miniui
                             r-magrittr
                             r-dt))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/cardiomoon/dplyrAssist")
    (synopsis
     "RStudio Addin for Teaching and Learning Data Manipulation Using 'dplyr'")
    (description
     "An RStudio addin for teaching and learning data manipulation using the dplyr
package.  You can learn each steps of data manipulation by clicking your mouse
without coding.  You can get resultant data (as a tibble') and the code for data
manipulation.")
    (license license:gpl3)))

(define-public r-dplr
  (package
    (name "r-dplr")
    (version "1.7.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dplR" version))
       (sha256
        (base32 "1gdjrpa0x6clafiybqcc7119i350k2hx34j5ksgljwr7lb9a8d8f"))))
    (properties `((upstream-name . "dplR")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml
                             r-stringr
                             r-stringi
                             r-signal
                             r-r-utils
                             r-png
                             r-matrixstats
                             r-matrix
                             r-lattice
                             r-digest
                             r-boot))
    (native-inputs (list gfortran))
    (home-page "https://github.com/OpenDendro/dplR")
    (synopsis "Dendrochronology Program Library in R")
    (description
     "Perform tree-ring analyses such as detrending, chronology building, and cross
dating.  Read and write standard file formats used in dendrochronology.")
    (license license:gpl2+)))

(define-public r-dpit
  (package
    (name "r-dpit")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Dpit" version))
       (sha256
        (base32 "02pnc00sk3bwxmxrg27638x0q62r7nsx2nr14zjjc5q880prdisv"))))
    (properties `((upstream-name . "Dpit")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam r-moments r-gsl r-fitdistrplus))
    (home-page "https://cran.r-project.org/package=Dpit")
    (synopsis "Distribution Pitting")
    (description
     "Compares distributions with one another in terms of their fit to each sample in
a dataset that contains multiple samples, as described in Joo, Aguinis, and
Bradley (in press).  Users can examine the fit of seven distributions per
sample: pure power law, lognormal, exponential, power law with an exponential
cutoff, normal, Poisson, and Weibull.  Automation features allow the user to
compare all distributions for all samples with a single command line, which
creates a separate row containing results for each sample until the entire
dataset has been analyzed.")
    (license license:gpl2+)))

(define-public r-dpcp
  (package
    (name "r-dpcp")
    (version "2.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dPCP" version))
       (sha256
        (base32 "023m9qzn64m7f992f12y4vf67jpj4zpajvwqyw4qlf4grsr9qfv5"))))
    (properties `((upstream-name . "dPCP")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-shinyjs
                             r-shiny
                             r-scales
                             r-rlist
                             r-raster
                             r-ggpubr
                             r-ggplot2
                             r-exactci
                             r-e1071
                             r-dbscan
                             r-cluster))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/alfodefalco/dPCP")
    (synopsis "Automated Analysis of Multiplex Digital PCR Data")
    (description
     "The automated clustering and quantification of the digital PCR data is based on
the combination of DBSCAN (Hahsler et al. (2019) <doi:10.18637/jss.v091.i01>)
and c-means (Bezdek et al. (1981) <doi:10.1007/978-1-4757-0450-1>) algorithms.
The analysis is independent of multiplexing geometry, @code{dPCR} system, and
input amount.  The details about input data and parameters are available in the
vignette.")
    (license license:expat)))

(define-public r-dpcc
  (package
    (name "r-dpcc")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dpcc" version))
       (sha256
        (base32 "1f4c68bvkwg82k1zanjhqqika2bfjv83mbr2khl5lhvfjwvpi1m0"))))
    (properties `((upstream-name . "dpcc")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://cran.r-project.org/package=dpcc")
    (synopsis "Dynamic Programming for Convex Clustering")
    (description
     "Use dynamic programming method to solve l1 convex clustering with identical
weights.")
    (license license:expat)))

(define-public r-dpbbm
  (package
    (name "r-dpbbm")
    (version "0.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DPBBM" version))
       (sha256
        (base32 "1qypxrcm3sb727lqb09ssjf3hblixqayw3qsyql01imrxwm609i2"))))
    (properties `((upstream-name . "DPBBM")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam r-tmvtnorm r-gplots r-ceoptim))
    (home-page "https://cran.r-project.org/package=DPBBM")
    (synopsis "Dirichlet Process Beta-Binomial Mixture")
    (description
     "Beta-binomial Mixture Model is used to infer the pattern from count data.  It
can be used for clustering of RNA methylation sequencing data.")
    (license license:gpl2+)))

(define-public r-dpasurv
  (package
    (name "r-dpasurv")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dpasurv" version))
       (sha256
        (base32 "1dzlry0pr8i39ix0hnhg19fi00kz5jf2l568230mc1k6fv7fidbv"))))
    (properties `((upstream-name . "dpasurv")))
    (build-system r-build-system)
    (propagated-inputs (list r-timereg
                             r-tidyr
                             r-survival
                             r-rlang
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "http://opensource.nibr.com/dpasurv/")
    (synopsis
     "Dynamic Path Analysis of Survival Data via Aalen's Additive Hazards Model")
    (description
     "Dynamic path analysis with estimation of the corresponding direct, indirect, and
total effects, based on Fosen et al., (2006) <doi:10.1007/s10985-006-9004-2>.
The main outcome of interest is a counting process from survival analysis (or
recurrent events) data.  At each time of event, ordinary linear regression is
used to estimate the relation between the covariates, while Aalen's additive
hazard model is used for the regression of the counting process on the
covariates.")
    (license license:expat)))

(define-public r-dparser
  (package
    (name "r-dparser")
    (version "1.3.1-12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dparser" version))
       (sha256
        (base32 "108hzzcvczfbcf3ldl3dg51cf9mr8sdpn9m0chiz48awngvjc9hh"))))
    (properties `((upstream-name . "dparser")))
    (build-system r-build-system)
    (propagated-inputs (list r-digest))
    (home-page "https://nlmixr2.github.io/dparser-R/")
    (synopsis "Port of 'Dparser' Package")
    (description
     "This package provides a Scannerless GLR parser/parser generator.  Note that GLR
standing for \"generalized LR\", where L stands for \"left-to-right\" and R stands
for \"rightmost (derivation)\".  For more information see
<https://en.wikipedia.org/wiki/GLR_parser>.  This parser is based on the Tomita
(1987) algorithm. (Paper can be found at
<https://aclanthology.org/P84-1073.pdf>).  The original dparser package
documentation can be found at <https://dparser.sourceforge.net/>.  This allows
you to add mini-languages to R (like rxode2's ODE mini-language Wang, Hallow,
and James 2015 <DOI:10.1002/psp4.12052>) or to parse other languages like NONMEM
to automatically translate them to R code.  To use this in your code, add a
@code{LinkingTo} dparser in your DESCRIPTION file and instead of using #include
<dparse.h> use #include <dparser.h>.  This also provides a R-based port of the
make_dparser <https://dparser.sourceforge.net/d/make_dparser.cat> command called
mkdparser().  Additionally you can parse an arbitrary grammar within R using the
dparse() function, which works on most OSes and is mainly for grammar testing.
The fastest parsing, of course, occurs at the C level, and is suggested.")
    (license license:bsd-3)))

(define-public r-doypacolors
  (package
    (name "r-doypacolors")
    (version "0.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DOYPAColors" version))
       (sha256
        (base32 "0ranqbczq65gdqm0csanmphcnnqxkxm8jiw61f1z1cz3rb7bhd5n"))))
    (properties `((upstream-name . "DOYPAColors")))
    (build-system r-build-system)
    (propagated-inputs (list r-gridextra r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jmestret/DOYPAColors")
    (synopsis "Don't Overthink Your Palette of Colors")
    (description
     "Access diverse ggplot2'-compatible color palettes for simplified data
visualization.")
    (license license:expat)))

(define-public r-dowser
  (package
    (name "r-dowser")
    (version "2.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dowser" version))
       (sha256
        (base32 "05fjca2zfa66fq360swywmncjxz7pvjp0d5h7a0axinvy9wiccg6"))))
    (properties `((upstream-name . "dowser")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-stringr
                             r-shazam
                             r-rlang
                             r-rcolorbrewer
                             r-phylotate
                             r-phangorn
                             r-markdown
                             r-gridextra
                             r-ggtree
                             r-ggplot2
                             r-dplyr
                             r-biostrings
                             r-ape
                             r-alakazam))
    (native-inputs (list r-knitr))
    (home-page "https://dowser.readthedocs.io")
    (synopsis "B Cell Receptor Phylogenetics Toolkit")
    (description
     "This package provides a set of functions for inferring, visualizing, and
analyzing B cell phylogenetic trees.  Provides methods to 1) reconstruct
unmutated ancestral sequences, 2) build B cell phylogenetic trees using multiple
methods, 3) visualize trees with metadata at the tips, 4) reconstruct
intermediate sequences, 5) detect biased ancestor-descendant relationships among
metadata types Workflow examples available at documentation site (see URL).
Citations: Hoehn et al (2022) <doi:10.1371/journal.pcbi.1009885>, Hoehn et al
(2021) <doi:10.1101/2021.01.06.425648>.")
    (license license:agpl3)))

(define-public r-downsize
  (package
    (name "r-downsize")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "downsize" version))
       (sha256
        (base32 "0yx62nx5ga835ng9gwrkwivxjhjrkygdldnd1hswc6wnvfs1qz8s"))))
    (properties `((upstream-name . "downsize")))
    (build-system r-build-system)
    (propagated-inputs (list r-r-utils r-magrittr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/wlandau/downsize")
    (synopsis "Tool to Downsize Large Analysis Projects for Testing")
    (description
     "Toggles the test and production versions of a large data analysis project.")
    (license license:gpl3+)))

(define-public r-downscale
  (package
    (name "r-downscale")
    (version "5.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "downscale" version))
       (sha256
        (base32 "1rcmn5f30l004rp8a7pmn0w5izsy31n9lwsk3sgj01fjzk0333wc"))))
    (properties `((upstream-name . "downscale")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra r-sf r-rmpfr r-minpack-lm r-cubature))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/charliem2003/downscale")
    (synopsis "Downscaling Species Occupancy")
    (description
     "Uses species occupancy at coarse grain sizes to predict species occupancy at
fine grain sizes.  Ten models are provided to fit and extrapolate the
occupancy-area relationship, as well as methods for preparing atlas data for
modelling.  See Marsh et.  al. (2018) <doi:10.18637/jss.v086.c03>.")
    (license license:gpl2)))

(define-public r-downloadthis
  (package
    (name "r-downloadthis")
    (version "0.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "downloadthis" version))
       (sha256
        (base32 "09hbcb9yj45l6v9iyv5pr4wz01l8624b34x45107d7a62djil1x9"))))
    (properties `((upstream-name . "downloadthis")))
    (build-system r-build-system)
    (propagated-inputs (list r-zip
                             r-writexl
                             r-readr
                             r-mime
                             r-magrittr
                             r-htmltools
                             r-ggplot2
                             r-fs
                             r-bsplus
                             r-b64))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/fmmattioni/downloadthis")
    (synopsis "Implement Download Buttons in 'rmarkdown'")
    (description
     "Implement download buttons in HTML output from rmarkdown without the need for
runtime:shiny'.")
    (license license:expat)))

(define-public r-dowd
  (package
    (name "r-dowd")
    (version "0.12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Dowd" version))
       (sha256
        (base32 "1fgaq22n7gm8pqxdfkiayqgjfqjn7knjjjr1x12jgv77cv08xyjk"))))
    (properties `((upstream-name . "Dowd")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-forecast r-bootstrap))
    (home-page "https://cran.r-project.org/package=Dowd")
    (synopsis
     "Functions Ported from 'MMR2' Toolbox Offered in Kevin Dowd's Book Measuring Market Risk")
    (description
     "Kevin Dowd's book Measuring Market Risk is a widely read book in the area of
risk measurement by students and practitioners alike.  As he claims, MATLAB
indeed might have been the most suitable language when he originally wrote the
functions, but, with growing popularity of R it is not entirely valid.  As
Dowd's code was not intended to be error free and were mainly for reference,
some functions in this package have inherited those errors.  An attempt will be
made in future releases to identify and correct them.  Dowd's original code can
be downloaded from www.kevindowd.org/measuring-market-risk/.  It should be noted
that Dowd offers both MMR2 and MMR1 toolboxes.  Only MMR2 was ported to R. MMR2
is more recent version of MMR1 toolbox and they both have mostly similar
function.  The toolbox mainly contains different parametric and non parametric
methods for measurement of market risk as well as backtesting risk measurement
methods.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-dove
  (package
    (name "r-dove")
    (version "1.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DOVE" version))
       (sha256
        (base32 "1n37f0mb95d5r2vszfwwysnvn0xv9m85j3mpz7qzz5cp9fb9k38c"))))
    (properties `((upstream-name . "DOVE")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rcpparmadillo r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DOVE")
    (synopsis "Durability of Vaccine Efficacy")
    (description
     "This package implements maximum likelihood methods for evaluating the durability
of vaccine efficacy in a randomized, placebo-controlled clinical trial with
staggered enrollment of participants and potential crossover of placebo
recipients before the end of the trial.  Lin, D. Y., Zeng, D., and Gilbert, P.
B. (2021) <doi:10.1093/cid/ciab226> and Lin, D. Y., Gu, Y., Zeng, D., Janes, H.
E., and Gilbert, P. B. (2021) <doi:10.1093/cid/ciab630>.")
    (license license:gpl2)))

(define-public r-dovalidation
  (package
    (name "r-dovalidation")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DOvalidation" version))
       (sha256
        (base32 "1mzws3w7djpxnfqxjcqwgia7p17kb0qlnzj6qcfg2m1vamb1cn2z"))))
    (properties `((upstream-name . "DOvalidation")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DOvalidation")
    (synopsis
     "Kernel Hazard Estimation with Best One-Sided and Double One-Sided Cross-Validation")
    (description
     "Local linear hazard estimator and its multiplicatively bias correction,
including three bandwidth selection methods: best one-sided cross-validation,
double one-sided cross-validation, and standard cross-validation.")
    (license license:gpl2)))

(define-public r-doudpackage
  (package
    (name "r-doudpackage")
    (version "2.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "doudpackage" version))
       (sha256
        (base32 "02zr80ps7x5bq388px9jfpf3b5krvba63ydrsi9big2v5x73hfv9"))))
    (properties `((upstream-name . "doudpackage")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringi
                             r-purrr
                             r-kableextra
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=doudpackage")
    (synopsis "Create Elegant Table 1 in HTML for Bio-Statistics")
    (description
     "This package creates the \"table one\" of bio-medical papers.  Fill it with your
data and the name of the variable which you'll make the group(s) out of and it
will make univariate, bivariate analysis and parse it into HTML. It also allows
you to visualize all your data with graphic representation.")
    (license license:gpl3+)))

(define-public r-douconca
  (package
    (name "r-douconca")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "douconca" version))
       (sha256
        (base32 "17hdmmik25n04hs7h1s7dhgkkvw8avmp6d26qyjnvgch3xs72rdn"))))
    (properties `((upstream-name . "douconca")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-rlang
                             r-permute
                             r-gridextra
                             r-ggrepel
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Biometris/douconca")
    (synopsis
     "Double Constrained Correspondence Analysis for Trait-Environment Analysis in Ecology")
    (description
     "Double constrained correspondence analysis (dc-CA) analyzes (multi-)trait
(multi-)environment ecological data by using the vegan package and native R
code.  Throughout the two step algorithm of ter Braak et al. (2018) is used.
This algorithm combines and extends community- (sample-) and species-level
analyses, i.e.  the usual community weighted means (CWM)-based regression
analysis and the species-level analysis of species-niche centroids (SNC)-based
regression analysis.  The two steps use canonical correspondence analysis to
regress the abundance data on to the traits and (weighted) redundancy analysis
to regress the CWM of the orthonormalized traits on to the environmental
predictors.  The function dc_CA() has an option to divide the abundance data of
a site by the site total, giving equal site weights.  This division has the
advantage that the multivariate analysis corresponds with an unweighted
(multi-trait) community-level analysis, instead of being weighted.  The first
step of the algorithm uses vegan::cca().  The second step uses wrda() but
vegan::rda() if the site weights are equal.  This version has a predict()
function.  For details see ter Braak et al.  2018
<doi:10.1007/s10651-017-0395-x>.")
    (license license:gpl3)))

(define-public r-doubt
  (package
    (name "r-doubt")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "doubt" version))
       (sha256
        (base32 "16avp0f7ks2zd4ckakvfm57zng2jk0fg3fz6vbm05lzhqymh6y30"))))
    (properties `((upstream-name . "doubt")))
    (build-system r-build-system)
    (propagated-inputs (list r-unglue))
    (home-page "https://cran.r-project.org/package=doubt")
    (synopsis "Enable Operators Containing the '?' Symbol")
    (description
     "Overload utils::'? to build unary and binary operators from existing functions,
piping operators of different precedence, and flexible syntaxes.")
    (license license:gpl3)))

(define-public r-doublin
  (package
    (name "r-doublin")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "doublIn" version))
       (sha256
        (base32 "0x22q6i07f49cjyhy9i2b9h818sgadxbhb6zwym2qilgf3mxj57g"))))
    (properties `((upstream-name . "doublIn")))
    (build-system r-build-system)
    (propagated-inputs (list r-xtable
                             r-visnetwork
                             r-tidyverse
                             r-shinywidgets
                             r-shinythemes
                             r-shinydashboard
                             r-shiny
                             r-rjags
                             r-plotly
                             r-mstats
                             r-magrittr
                             r-lubridate
                             r-ggplot2
                             r-flexsurv
                             r-epicontacts
                             r-dt
                             r-dplyr
                             r-coda))
    (home-page "https://cran.r-project.org/package=doublIn")
    (synopsis
     "Estimate Incubation or Latency Time using Doubly Interval Censored Observations")
    (description
     "Visualize contact tracing data using a shiny app and estimate the incubation or
latency time of an infectious disease respecting the following characteristics
in the analysis; (i) doubly interval censoring with (partly) overlapping or
distinct windows; (ii) an infection risk corresponding to exponential growth;
(iii) right truncation allowing for individual truncation times; (iv) different
choices concerning the family of the distribution.  For our earlier work, we
refer to Arntzen et al. (2023) <doi:10.1002/sim.9726>.  A paper describing our
approach in detail will follow.")
    (license license:gpl3+)))

(define-public r-doubleml
  (package
    (name "r-doubleml")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DoubleML" version))
       (sha256
        (base32 "0qk7zjpzz0dpzvczssfbp4gbqxazyxn0dsc8h9jnqb3syzdscc27"))))
    (properties `((upstream-name . "DoubleML")))
    (build-system r-build-system)
    (propagated-inputs (list r-readstata13
                             r-r6
                             r-mvtnorm
                             r-mlr3tuning
                             r-mlr3misc
                             r-mlr3learners
                             r-mlr3
                             r-data-table
                             r-clustergeneration
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://docs.doubleml.org/stable/index.html")
    (synopsis "Double Machine Learning in R")
    (description
     "Implementation of the double/debiased machine learning framework of Chernozhukov
et al. (2018) <doi:10.1111/ectj.12097> for partially linear regression models,
partially linear instrumental variable regression models, interactive regression
models and interactive instrumental variable regression models. @code{DoubleML}
allows estimation of the nuisance parts in these models by machine learning
methods and computation of the Neyman orthogonal score functions.
@code{DoubleML} is built on top of mlr3 and the mlr3 ecosystem.  The
object-oriented implementation of @code{DoubleML} based on the R6 package is
very flexible.  More information available in the publication in the Journal of
Statistical Software: <doi:10.18637/jss.v108.i03>.")
    (license license:expat)))

(define-public r-doubleexpseq
  (package
    (name "r-doubleexpseq")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DoubleExpSeq" version))
       (sha256
        (base32 "00xpj5xmpgmvp6h76imkmghrnlfk6c50ydvv0jram6m6ix3z8323"))))
    (properties `((upstream-name . "DoubleExpSeq")))
    (build-system r-build-system)
    (propagated-inputs (list r-numderiv))
    (home-page "https://cran.r-project.org/package=DoubleExpSeq")
    (synopsis
     "Differential Exon Usage Test for RNA-Seq Data via Empirical Bayes Shrinkage of the Dispersion Parameter")
    (description
     "Differential exon usage test for RNA-Seq data via an empirical Bayes shrinkage
method for the dispersion parameter the utilizes inclusion-exclusion data to
analyze the propensity to skip an exon across groups.  The input data consists
of two matrices where each row represents an exon and the columns represent the
biological samples.  The first matrix is the count of the number of reads
expressing the exon for each sample.  The second matrix is the count of the
number of reads that either express the exon or explicitly skip the exon across
the samples, a.k.a.  the total count matrix.  Dividing the two matrices yields
proportions representing the propensity to express the exon versus skipping the
exon for each sample.")
    (license license:gpl3)))

(define-public r-doublecone
  (package
    (name "r-doublecone")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DoubleCone" version))
       (sha256
        (base32 "1kbvsj93nn2306s6pgqiiznmlcn2nqsgcxinihl613ivczxhzpqg"))))
    (properties `((upstream-name . "DoubleCone")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-mass r-coneproj))
    (home-page "https://cran.r-project.org/package=DoubleCone")
    (synopsis "Test Against Parametric Regression Function")
    (description
     "This package performs hypothesis tests concerning a regression function in a
least-squares model, where the null is a parametric function, and the
alternative is the union of large-dimensional convex polyhedral cones.  See
Bodhisattva Sen and Mary C Meyer (2016) <doi:10.1111/rssb.12178> for more
details.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-double-truncation
  (package
    (name "r-double-truncation")
    (version "1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "double.truncation" version))
       (sha256
        (base32 "0hrb1qli7i4jhc705rb02zbq2nyk0i406bb8gpy4jrzygjjbq3g0"))))
    (properties `((upstream-name . "double.truncation")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=double.truncation")
    (synopsis "Analysis of Doubly-Truncated Data")
    (description
     "Likelihood-based inference methods with doubly-truncated data are developed
under various models.  Nonparametric models are based on Efron and Petrosian
(1999) <doi:10.1080/01621459.1999.10474187> and Emura, Konno, and Michimae
(2015) <doi:10.1007/s10985-014-9297-5>.  Parametric models from the special
exponential family (SEF) are based on Hu and Emura (2015)
<doi:10.1007/s00180-015-0564-z> and Emura, Hu and Konno (2017)
<doi:10.1007/s00362-015-0730-y>.  The parametric location-scale models are based
on Dorre et al. (2020) <doi:10.1007/s00180-020-01027-6>.")
    (license license:gpl2)))

(define-public r-doubcens
  (package
    (name "r-doubcens")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "doubcens" version))
       (sha256
        (base32 "1hn65n67by3xqbcnaf5jja5pli0g6wpbbz2sfzd7i2nms7kiywhp"))))
    (properties `((upstream-name . "doubcens")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=doubcens")
    (synopsis
     "Survivor Function Estimation for Doubly Interval-Censored Failure Time Data")
    (description
     "This package contains the discrete nonparametric survivor function estimation
algorithm of De Gruttola and Lagakos for doubly interval-censored failure time
data and the discrete nonparametric survivor function estimation algorithm of
Sun for doubly interval-censored left-truncated failure time data [Victor De
Gruttola & Stephen W. Lagakos (1989) <doi:10.2307/2532030>] [Jianguo Sun (1995)
<doi:10.2307/2533008>].")
    (license license:gpl2)))

(define-public r-dotwhisker
  (package
    (name "r-dotwhisker")
    (version "0.8.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dotwhisker" version))
       (sha256
        (base32 "0p1l0750cy31ray9f9xm8yrc0zin4zb93rvbix51m3r4snhvjlnl"))))
    (properties `((upstream-name . "dotwhisker")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-rlang
                             r-purrr
                             r-performance
                             r-patchwork
                             r-parameters
                             r-gtable
                             r-gridextra
                             r-ggstance
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://fsolt.org/dotwhisker/")
    (synopsis "Dot-and-Whisker Plots of Regression Results")
    (description
     "Create quick and easy dot-and-whisker plots of regression results.  It takes as
input either (1) a coefficient table in standard form or (2) one (or a list of)
fitted model objects (of any type that has methods implemented in the parameters
package).  It returns ggplot objects that can be further customized using tools
from the ggplot2 package.  The package also includes helper functions for tasks
such as rescaling coefficients or relabeling predictor variables.  See more
methodological discussion of the visualization and data management methods used
in this package in Kastellec and Leoni (2007) <doi:10.1017/S1537592707072209>
and Gelman (2008) <doi:10.1002/sim.3107>.")
    (license license:expat)))

(define-public r-dotty
  (package
    (name "r-dotty")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dotty" version))
       (sha256
        (base32 "1w41cm1h6g2r1r6iqwyfw0m0qyg296yv5nbsav90vg9a9knq56cf"))))
    (properties `((upstream-name . "dotty")))
    (build-system r-build-system)
    (home-page "https://kevinushey.github.io/dotty/")
    (synopsis "The Unpacking Dot Operator")
    (description
     "This package provides a `.` object which can be used for unpacking assignments.
For example, `.[rows, columns] <- dim(cars)` could be used to pull the number of
rows and number of columns from `dim(cars)` into individual variables `rows` and
`columns` in a single step.")
    (license license:expat)))

(define-public r-dotsviolin
  (package
    (name "r-dotsviolin")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dotsViolin" version))
       (sha256
        (base32 "0pyxs899429qsyhnm1n36n06wxwrk1i20qd9pyz62n4n6x706ajq"))))
    (properties `((upstream-name . "dotsViolin")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-stringr
                             r-scales
                             r-rlang
                             r-magrittr
                             r-lazyeval
                             r-gtools
                             r-gridextra
                             r-ggplot2
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=dotsViolin")
    (synopsis "Dot Plots Mimicking Violin Plots")
    (description
     "Modifies dot plots to have different sizes of dots mimicking violin plots and
identifies modes or peaks for them based on frequency and kernel density
estimates (Rosenblatt, 1956) <doi:10.1214/aoms/1177728190> (Parzen, 1962)
<doi:10.1214/aoms/1177704472>.")
    (license license:gpl2+)))

(define-public r-dots
  (package
    (name "r-dots")
    (version "0.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dots" version))
       (sha256
        (base32 "0g4wvb6qp66dm0pfckjr9xgij58dzlji2iq45m5cz98jzivfd9gm"))))
    (properties `((upstream-name . "dots")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra
                             r-sp
                             r-sf
                             r-rmapshaper
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/christopherkenny/dots")
    (synopsis "Dot Density Maps")
    (description
     "Generate point data for representing people within spatial data.  This collects
a suite of tools for creating simple dot density maps.  Several functions from
different spatial packages are standardized to take the same arguments so that
they can be easily substituted for each other.")
    (license license:expat)))

(define-public r-dotprofile
  (package
    (name "r-dotprofile")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dotprofile" version))
       (sha256
        (base32 "10vm8s1sk4i2930zzswgwy1y873x8byfr7xfb8xq6cdk9ci7l741"))))
    (properties `((upstream-name . "dotprofile")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6 r-cli))
    (home-page "https://github.com/jeanmathieupotvin/dotprofile")
    (synopsis "Create and Manage Configuration Profiles")
    (description
     "This package provides a toolbox to create and manage metadata files and
configuration profiles: files used to configure the parameters and initial
settings for some computer programs.")
    (license license:expat)))

(define-public r-dotgen
  (package
    (name "r-dotgen")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dotgen" version))
       (sha256
        (base32 "12dvn52ggmkj2q6whi8s2hh9fpg7jcg20bgx32jxzh4cb1zxnksz"))))
    (properties `((upstream-name . "dotgen")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm))
    (home-page "https://github.com/xiaoran831213/dotgen")
    (synopsis
     "Gene-Set Analysis via Decorrelation by Orthogonal Transformation")
    (description
     "Decorrelates a set of summary statistics (i.e., Z-scores or P-values per SNP)
via Decorrelation by Orthogonal Transformation (DOT) approach and performs
gene-set analyses by combining transformed statistic values; operations are
performed with algorithms that rely only on the association summary results and
the linkage disequilibrium (LD).  For more details on DOT and its power, see
Olga (2020) <doi:10.1371/journal.pcbi.1007819>.")
    (license license:gpl2+)))

(define-public r-dotenv
  (package
    (name "r-dotenv")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dotenv" version))
       (sha256
        (base32 "0dclwqg2hxdly8z3cckcskcll3dfax6g14h1xzjzdfwahhrbr5wb"))))
    (properties `((upstream-name . "dotenv")))
    (build-system r-build-system)
    (home-page "https://github.com/gaborcsardi/dotenv")
    (synopsis "Load Environment Variables from '.env'")
    (description
     "Load configuration from a .env file, that is in the current working directory,
into environment variables.")
    (license license:expat)))

(define-public r-dostats
  (package
    (name "r-dostats")
    (version "1.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dostats" version))
       (sha256
        (base32 "0nq5965rlpvad8wyz3yr98wxy4w7jb4v4xfbbfa6c2vnc6w7w884"))))
    (properties `((upstream-name . "dostats")))
    (build-system r-build-system)
    (home-page "https://github.com/halpo/dostats")
    (synopsis "Compute Statistics Helper Functions")
    (description
     "This package provides a small package containing helper utilities for creating
functions for computing statistics.")
    (license license:gpl3+)))

(define-public r-dosresmeta
  (package
    (name "r-dosresmeta")
    (version "2.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dosresmeta" version))
       (sha256
        (base32 "0qdalzdk7q4wx3vl5f3i64m8cb7vhi4pqzghar32j0a7l6gla04z"))))
    (properties `((upstream-name . "dosresmeta")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvmeta))
    (native-inputs (list r-knitr))
    (home-page "https://alecri.github.io/software/dosresmeta.html")
    (synopsis "Multivariate Dose-Response Meta-Analysis")
    (description
     "Estimates dose-response relations from summarized dose-response data and to
combines them according to principles of (multivariate) random-effects models.")
    (license license:gpl2)))

(define-public r-dosportfolio
  (package
    (name "r-dosportfolio")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DOSPortfolio" version))
       (sha256
        (base32 "1aw40xlwahzvikf31y4cbzdrlmgwg3y765bsjzlvc8wqrjig3ghs"))))
    (properties `((upstream-name . "DOSPortfolio")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack))
    (native-inputs (list r-knitr))
    (home-page
     "https://github.com/Statistics-In-Portfolio-Theory/DOSportfolio")
    (synopsis "Dynamic Optimal Shrinkage Portfolio")
    (description
     "Constructs dynamic optimal shrinkage estimators for the weights of the global
minimum variance portfolio which are reconstructed at given reallocation points
as derived in Bodnar, Parolya, and ThorsÃ©n (2021) (<@code{arXiv:2106.02131>}).
Two dynamic shrinkage estimators are available in this package.  One using
overlapping samples while the other use nonoverlapping samples.")
    (license license:gpl3)))

(define-public r-dosesens
  (package
    (name "r-dosesens")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "doseSens" version))
       (sha256
        (base32 "1srxxfadxsrxpd2ksn59ilmijw5iifjik3mz9q38rsvjdxqls5d6"))))
    (properties `((upstream-name . "doseSens")))
    (build-system r-build-system)
    (propagated-inputs (list r-gtools r-dplyr))
    (home-page "https://cran.r-project.org/package=doseSens")
    (synopsis
     "Conduct Sensitivity Analysis with Continuous Exposures and Binary Outcomes")
    (description
     "This package performs sensitivity analysis for the sharp null and attributable
effects in matched studies with continuous exposures and binary outcomes as
described in Zhang, Small, Heng (2024) <@code{arXiv:2401.06909>}.  Two of the
functions require installation of the Gurobi optimizer.  Please see
<https://www.gurobi.com/documentation/9.0/refman/ins_the_r_package.html> for
guidance.")
    (license license:expat)))

(define-public r-doseminer
  (package
    (name "r-doseminer")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "doseminer" version))
       (sha256
        (base32 "0y03k14adyqf0cyzqrr4rk47dabwgzzjkxbf11a5b8xlyy19mjr1"))))
    (properties `((upstream-name . "doseminer")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-magrittr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=doseminer")
    (synopsis "Extract Drug Dosages from Free-Text Prescriptions")
    (description
     "Utilities for converting unstructured electronic prescribing instructions into
structured medication data.  Extracts drug dose, units, daily dosing frequency
and intervals from English-language prescriptions.  Based on Karystianis et al.
(2015) <doi:10.1186/s12911-016-0255-x>.")
    (license license:expat)))

(define-public r-dosefinding
  (package
    (name "r-dosefinding")
    (version "1.2-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DoseFinding" version))
       (sha256
        (base32 "0chy4xl7faflp3cf27sf2ayzkvay13vf2cgdxmihsrbxkib2f01f"))))
    (properties `((upstream-name . "DoseFinding")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-lattice r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/openpharma/DoseFinding")
    (synopsis "Planning and Analyzing Dose Finding Experiments")
    (description
     "The @code{DoseFinding} package provides functions for the design and analysis of
dose-finding experiments (with focus on pharmaceutical Phase II clinical
trials).  It provides functions for: multiple contrast tests, fitting non-linear
dose-response models (using Bayesian and non-Bayesian estimation), calculating
optimal designs and an implementation of the MCPMod methodology (Pinheiro et al.
(2014) <doi:10.1002/sim.6052>).")
    (license license:gpl3)))

(define-public r-dosedesignr
  (package
    (name "r-dosedesignr")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dosedesignR" version))
       (sha256
        (base32 "0s25nv3vdbnl1sn8gdhr45l7paiby452b2986xfkc3cvrdlsrhjw"))))
    (properties `((upstream-name . "dosedesignR")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-shinywidgets
                             r-shinyjs
                             r-shinybs
                             r-shiny
                             r-rsolnp
                             r-readxl
                             r-purrr
                             r-latticeextra
                             r-knitr
                             r-kableextra
                             r-ggplot2
                             r-dt
                             r-dosefinding))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dosedesignR")
    (synopsis "Interactive Designing of Dose Finding Studies")
    (description
     "This package provides the user with an interactive application which can be used
to facilitate the planning of dose finding studies by applying the theory of
optimal experimental design.")
    (license license:gpl3)))

(define-public r-dosearch
  (package
    (name "r-dosearch")
    (version "1.0.11")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dosearch" version))
       (sha256
        (base32 "0ghwk0h9rrfg4i6xdiybirqvrpzm3rv0w41jqqlhm43jf7796pmj"))))
    (properties `((upstream-name . "dosearch")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/santikka/dosearch")
    (synopsis
     "Causal Effect Identification from Multiple Incomplete Data Sources")
    (description
     "Identification of causal effects from arbitrary observational and experimental
probability distributions via do-calculus and standard probability manipulations
using a search-based algorithm by Tikka, Hyttinen and Karvanen (2021)
<doi:10.18637/jss.v099.i05>.  Allows for the presence of mechanisms related to
selection bias (Bareinboim and Tian, 2015) <doi:10.1609/aaai.v29i1.9679>,
transportability (Bareinboim and Pearl, 2014)
<http://ftp.cs.ucla.edu/pub/stat_ser/r443.pdf>, missing data (Mohan, Pearl, and
Tian, 2013) <http://ftp.cs.ucla.edu/pub/stat_ser/r410.pdf>) and arbitrary
combinations of these.  Also supports identification in the presence of
context-specific independence (CSI) relations through labeled directed acyclic
graphs (LDAG).  For details on CSIs see (Corander et al., 2019)
<doi:10.1016/j.apal.2019.04.004>.")
    (license license:gpl3+)))

(define-public r-dos2
  (package
    (name "r-dos2")
    (version "0.5.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DOS2" version))
       (sha256
        (base32 "0lcqk2fxfl5pdnxlpppqiqnyc23jyhp1kcxwci8ilagjv4djipmw"))))
    (properties `((upstream-name . "DOS2")))
    (build-system r-build-system)
    (propagated-inputs (list r-senstrat r-sensitivitymv r-sensitivitymult
                             r-sensitivity2x2xk r-mass))
    (home-page "https://cran.r-project.org/package=DOS2")
    (synopsis
     "Design of Observational Studies, Companion to the Second Edition")
    (description
     "This package contains data sets, examples and software from the Second Edition
of \"Design of Observational Studies\"; see Rosenbaum, P.R. (2010)
<doi:10.1007/978-1-4419-1213-8>.")
    (license license:gpl2)))

(define-public r-dos
  (package
    (name "r-dos")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DOS" version))
       (sha256
        (base32 "0vvkwn4wfvspbk74nb6124hdx9158h6yfksib14xqq7rx7c97ad4"))))
    (properties `((upstream-name . "DOS")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=DOS")
    (synopsis "Design of Observational Studies")
    (description
     "This package contains data sets, examples and software from the book Design of
Observational Studies by Paul R. Rosenbaum, New York: Springer,
<doi:10.1007/978-1-4419-1213-8>, ISBN 978-1-4419-1212-1.")
    (license license:gpl2)))

(define-public r-doremi
  (package
    (name "r-doremi")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "doremi" version))
       (sha256
        (base32 "005kp6f4jh8y1ykhri3mjnvc9w66b1a51bji574rkbxd1ans6mal"))))
    (properties `((upstream-name . "doremi")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-lmertest
                             r-lme4
                             r-gridextra
                             r-ggplot2
                             r-futile-logger
                             r-desolve
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/dcourvoisier/doremi")
    (synopsis "Dynamics of Return to Equilibrium During Multiple Inputs")
    (description
     "This package provides models to fit the dynamics of a regulated system
experiencing exogenous inputs.  The underlying models use differential equations
and linear mixed-effects regressions to estimate the coefficients of the
equation.  With them, the functions can provide an estimated signal.  The
package provides simulation and analysis functions and also print, summary, plot
and predict methods, adapted to the function outputs, for easy implementation
and presentation of results.")
    (license license:gpl3)))

(define-public r-doredis
  (package
    (name "r-doredis")
    (version "3.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "doRedis" version))
       (sha256
        (base32 "0vl81hy9aspaxns823m7wsbfxfcbx2xbxl140ci3l79pvz3rwyf5"))))
    (properties `((upstream-name . "doRedis")))
    (build-system r-build-system)
    (propagated-inputs (list r-redux r-iterators r-foreach))
    (home-page "https://cran.r-project.org/package=doRedis")
    (synopsis "'Foreach' Parallel Adapter Using the 'Redis' Database")
    (description
     "Create and manage fault-tolerant task queues for the foreach package using the
Redis key/value database.")
    (license license:gpl2)))

(define-public r-dope
  (package
    (name "r-dope")
    (version "2.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DOPE" version))
       (sha256
        (base32 "1ccg0sgxvv4c9522f2wynp9j37cnlf4gdaymxgi1jxdlikm3ls5r"))))
    (properties `((upstream-name . "DOPE")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidytext r-tibble r-stringr r-magrittr r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://ctn-0094.github.io/DOPE/")
    (synopsis "Drug Ontology Parsing Engine")
    (description
     "This package provides information on drug names (brand, generic and street) for
drugs tracked by the DEA. There are functions that will search synonyms and
return the drug names and types.  The vignettes have extensive information on
the work done to create the data for the package.")
    (license license:expat)))

(define-public r-doolkit
  (package
    (name "r-doolkit")
    (version "1.42.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "doolkit" version))
       (sha256
        (base32 "0hyqbpnhzjsx7ml0z6n9z60yhp5c0dyicm3jfc841aykvb1ifqbp"))))
    (properties `((upstream-name . "doolkit")))
    (build-system r-build-system)
    (propagated-inputs (list r-usethis
                             r-tis
                             r-sp
                             r-rvcg
                             r-rgl
                             r-morpho
                             r-mass
                             r-igraph
                             r-ggplot2
                             r-concaveman))
    (home-page "https://cran.r-project.org/package=doolkit")
    (synopsis "Exploration of Dental Surface Topography")
    (description
     "This package provides tools for exploring the topography of 3d triangle meshes.
The functions were developed with dental surfaces in mind, but could be applied
to any triangle mesh of class mesh3d'.  More specifically, doolkit allows to
isolate the border of a mesh, or a subpart of the mesh using the polygon
networks method; crop a mesh; compute basic descriptors (elevation, orientation,
footprint area); compute slope, angularity and relief index (Ungar and
Williamson (2000) <https://palaeo-electronica.org/2000_1/gorilla/issue1_00.htm>;
Boyer (2008) <doi:10.1016/j.jhevol.2008.08.002>), inclination and occlusal
relief index or gamma (Guy et al. (2013) <doi:10.1371/journal.pone.0066142>),
OPC (Evans et al. (2007) <doi:10.1038/nature05433>), OPCR (Wilson et al. (2012)
<doi:10.1038/nature10880>), DNE (Bunn et al. (2011) <doi:10.1002/ajpa.21489>;
Pampush et al. (2016) <doi:10.1007/s10914-016-9326-0>), form factor (Horton
(1932) <doi:10.1029/TR013i001p00350>), basin elongation (Schum (1956)
<doi:10.1130/0016-7606(1956)67[597:EODSAS]2.0.CO;2>), lemniscate ratio (Chorley
et al; (1957) <doi:10.2475/ajs.255.2.138>), enamel-dentine distance (Guy et al.
(2015) <doi:10.1371/journal.pone.0138802>; Thiery et al. (2017)
<doi:10.3389/fphys.2017.00524>), absolute crown strength (Schwartz et al. (2020)
<doi:10.1098/rsbl.2019.0671>), relief rate (Thiery et al. (2019)
<doi:10.1002/ajpa.23916>) and area-relative curvature; draw cumulative profiles
of a topographic variable; and map a variable over a 3d triangle mesh.")
    (license license:gpl3)))

(define-public r-doofa
  (package
    (name "r-doofa")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "doofa" version))
       (sha256
        (base32 "0pwy27jhmabmpd617pjdw46l7gcy8dz0w37if5901kfsc0cr27kc"))))
    (properties `((upstream-name . "doofa")))
    (build-system r-build-system)
    (propagated-inputs (list r-lpsolve r-combinat))
    (home-page "https://cran.r-project.org/package=doofa")
    (synopsis "Designs for Order-of-Addition Experiments")
    (description
     "This package provides a facility to generate efficient designs for
order-of-additions experiments under pair-wise-order model, see Dennis K. J. Lin
and Jiayu Peng (2019).\"Order-of-addition experiments: A review and some new
thoughts\".  Quality Engineering, 31:1, 49-59,
<doi:10.1080/08982112.2018.1548021>.  It also provides a facility to generate
component orthogonal arrays under component position model, see Jian-Feng Yang,
Fasheng Sun & Hongquan Xu (2020): \"A Component Position Model, Analysis and
Design for Order-of-Addition Experiments\".  Technometrics,
<doi:10.1080/00401706.2020.1764394>.")
    (license license:gpl2+)))

(define-public r-donutsk
  (package
    (name "r-donutsk")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "donutsk" version))
       (sha256
        (base32 "1mmpxdjhyl06wwkcmczbai0j9pll01sh7zc4vl70mbvk6yx9khfg"))))
    (properties `((upstream-name . "donutsk")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-glue r-ggplot2 r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/dkibalnikov/donutsk")
    (synopsis "Construct Advanced Donut Charts")
    (description
     "Build donut/pie charts with ggplot2 layer by layer, exploiting the advantages of
polar symmetry.  Leverage layouts to distribute labels effectively.  Connect
labels to donut segments using pins.  Streamline annotation and highlighting.")
    (license license:expat)))

(define-public r-donut
  (package
    (name "r-donut")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "donut" version))
       (sha256
        (base32 "1vrarv850dja286s5l8y0fng7idai9rqr156z67zrwx347bdr4n2"))))
    (properties `((upstream-name . "donut")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/paulnorthrop/donut")
    (synopsis "Nearest Neighbour Search with Variables on a Torus")
    (description
     "Finds the k nearest neighbours in a dataset of specified points, adding the
option to wrap certain variables on a torus.  The user chooses the algorithm to
use to find the nearest neighbours.  Two such algorithms, provided by the
packages RANN <https://cran.r-project.org/package=RANN>, and nabor
<https://cran.r-project.org/package=nabor>, are suggested.")
    (license license:gpl2+)))

(define-public r-dompi
  (package
    (name "r-dompi")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "doMPI" version))
       (sha256
        (base32 "0ahwm17p3gq1yvc8v6sr6sb8z7i6zws8d1pf46qynl0gd4amg938"))))
    (properties `((upstream-name . "doMPI")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmpi r-iterators r-foreach))
    (home-page "https://cran.r-project.org/package=doMPI")
    (synopsis "Foreach Parallel Adaptor for the Rmpi Package")
    (description
     "This package provides a parallel backend for the %dopar% function using the Rmpi
package.")
    (license license:gpl2)))

(define-public r-domir
  (package
    (name "r-domir")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "domir" version))
       (sha256
        (base32 "0jqbigk1kd0b2n9y0q7cavh8f73ydii4fnp7w4msiy39nmpkn08k"))))
    (properties `((upstream-name . "domir")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jluchman/domir")
    (synopsis "Tools to Support Relative Importance Analysis")
    (description
     "This package provides methods to apply decomposition-based relative importance
analysis for R functions.  This package supports the application of
decomposition methods by providing lapply'- or Map'-like meta-functions that
compute dominance analysis (Azen, R., & Budescu, D. V. (2003)
<doi:10.1037/1082-989X.8.2.129>; GrÃ¶mping, U. (2007)
<doi:10.1198/000313007X188252>) an extension of Shapley value regression
(Lipovetsky, S., & Conklin, M. (2001) <doi:10.1002/asmb.446>) based on the
values returned from other functions.")
    (license license:gpl3+)))

(define-public r-dominodatar
  (package
    (name "r-dominodatar")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DominoDataR" version))
       (sha256
        (base32 "1awiy32sm0n2v1z48v4agqm89jnkgqazbjh9zixmj7yd0db78a9v"))))
    (properties `((upstream-name . "DominoDataR")))
    (build-system r-build-system)
    (propagated-inputs (list r-reticulate r-httr r-configparser r-arrow))
    (home-page "https://github.com/dominodatalab/DominoDataR")
    (synopsis "'Domino Data R SDK'")
    (description
     "This package provides a wrapper on top of the Domino Data Python SDK library.
It lets you query and access Domino Data Sources directly from your R
environment.  Under the hood, Domino Data R SDK leverages the API provided by
the Domino Data Python SDK', which must be installed as a prerequisite.  Domino
is a platform that makes it easy to run your code on scalable hardware, with
integrated version control and collaboration features designed for analytical
workflows.  See
<https://docs.dominodatalab.com/en/latest/api_guide/140b48/domino-data-api> for
more information.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-domino
  (package
    (name "r-domino")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "domino" version))
       (sha256
        (base32 "0f67w0z5jy82kgm3l1rji430ayigw30vmmwp3i1nz0xibsx7jxv4"))))
    (properties `((upstream-name . "domino")))
    (build-system r-build-system)
    (home-page "http://www.dominodatalab.com")
    (synopsis "R Console Bindings for the 'Domino Command-Line Client'")
    (description
     "This package provides a wrapper on top of the Domino Command-Line Client'.  It
lets you run Domino commands (e.g., \"run\", \"upload\", \"download\") directly from
your R environment.  Under the hood, it uses R's system function to run the
Domino executable, which must be installed as a prerequisite.  Domino is a
service that makes it easy to run your code on scalable hardware, with
integrated version control and collaboration features designed for analytical
workflows (see <http://www.dominodatalab.com> for more information).")
    (license license:expat)))

(define-public r-dominanceanalysis
  (package
    (name "r-dominanceanalysis")
    (version "2.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dominanceanalysis" version))
       (sha256
        (base32 "1kp8x77j20ak5xgp67f2ny00s22q6yr8qz5lc5kdmvdrimqkpnah"))))
    (properties `((upstream-name . "dominanceanalysis")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dominanceanalysis")
    (synopsis "Dominance Analysis")
    (description
     "Dominance analysis is a method that allows to compare the relative importance of
predictors in multiple regression models: ordinary least squares, generalized
linear models, hierarchical linear models, beta regression and dynamic linear
models.  The main principles and methods of dominance analysis are described in
Budescu, D. V. (1993) <doi:10.1037/0033-2909.114.3.542> and Azen, R., & Budescu,
D. V. (2003) <doi:10.1037/1082-989X.8.2.129> for ordinary least squares
regression.  Subsequently, the extensions for multivariate regression, logistic
regression and hierarchical linear models were described in Azen, R., & Budescu,
D. V. (2006) <doi:10.3102/10769986031002157>, Azen, R., & Traxel, N. (2009)
<doi:10.3102/1076998609332754> and Luo, W., & Azen, R. (2013)
<doi:10.3102/1076998612458319>, respectively.")
    (license license:gpl2)))

(define-public r-dogesr
  (package
    (name "r-dogesr")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dogesr" version))
       (sha256
        (base32 "0w5qps781c406br5rba6mv127yrlgq7rzchk55j7mndrm7hwia63"))))
    (properties `((upstream-name . "dogesr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmarkdown
                             r-rdpack
                             r-qpdf
                             r-knitr
                             r-igraph
                             r-ggthemes
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dogesr")
    (synopsis "Work with the Doges/Dogaresse Dataset")
    (description
     "Work with data on Venetian doges and dogaresse and the noble families of the
Republic of Venice, and use it for social network analysis, as used in Merelo
(2022) <@code{arXiv:2209.07334>}.")
    (license license:gpl3)))

(define-public r-doex
  (package
    (name "r-doex")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "doex" version))
       (sha256
        (base32 "1r999z30ipa04pgck0hfalqxihb1bj8sdhlkkhf4plb7maaz3qm3"))))
    (properties `((upstream-name . "doex")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=doex")
    (synopsis "The One-Way Heteroscedastic ANOVA Tests")
    (description
     "This package contains the heteroscedastic ANOVA tests for normal and
two-parameter exponential distributed populations.  For normal distributions,
Alexander-Govern test by Alexandern and Govern (1994) <doi:10.2307/1165140>,
Alvandi et al.  Generalized F test by Alvandi et al. (2012)
<doi:10.1080/03610926.2011.573160>, Approximate F test by Asiribo and Gurland
(1990) <doi:10.1080/03610929008830427>, Box F test by Box (1954)
<doi:10.1214/aoms/1177728786>, Brown-Forsythe test by Brown and Forsythe (1974)
<do:10.2307/1267501>, B2 test by Ozdemir and Kurt (2006)
<http://sjam.selcuk.edu.tr/sjam/article/view/174>, Cochran F test by Cochran
(1937) <https://www.jstor.org/stable/pdf/2984123.pdf>, Fiducial Approach test by
Li et al. (2011) <doi:10.1016/j.csda.2010.12.009>, Generalized F test by
Weerahandi (1995) <doi:10.2307/2532947>, Johansen F test by Johansen (1980)
<doi:10.1093/biomet/67.1.85>, Modified Brown-Forsythe test by Mehrotra (1997)
<doi:10.1080/03610919708813431>, Modified Welch test by Hartung et al.(2002)
<doi:10.1007/s00362-002-0097-8>, One-Stage test by Chen and Chen (1998)
<doi:10.1080/03610919808813501>, One-Stage Range test by Chen and Chen (2000)
<doi:10.1080/01966324.2000.10737505>, Parametric Bootstrap test by
Krishnamoorhty et al.(2007) <doi:10.1016/j.csda.2006.09.039>, Permutation F test
by Berry and Mielke (2002) <doi:10.2466/pr0.2002.90.2.495>, Scott-Smith test by
Scott and Smith (1971) <doi:10.2307/2346757>, Welch test by Welch(1951)
<doi:10.2307/2332579>, and Welch-Aspin test by Aspin (1948)
<doi:10.1093/biomet/35.1-2.88>.  These tests are used to test the equality of
group means under unequal variance.  Also, a modified version of Generalized
F-test is improved to test the equality of non-normal group means under unequal
variances and a revised version of Generalized F-test is given to test the
equality of non-normal group means caused by skewness.  Furthermore, it consists
some procedures for testing equality of several two-parameter exponentially
distributed population means under unequal scale parameters such as generalized
p-value, parametric bootstrap and fiducial approach test by Malekzadeh and
Jafari (2019) <doi:10.1080/03610918.2018.1538452>.  There is also Hsieh test by
Hsieh (1986) <doi:10.2307/1270452> for testing equality of location parameters
of two-parameter exponentially distributed populations under unequal scale
parameters.")
    (license license:gpl2+)))

(define-public r-doestrare
  (package
    (name "r-doestrare")
    (version "0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DoEstRare" version))
       (sha256
        (base32 "0y9ymw7114jk1rwiasq400bpgvkxv6rpc954c7v9mgxd3c2nfza7"))))
    (properties `((upstream-name . "DoEstRare")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DoEstRare")
    (synopsis
     "Rare Variant Association Test Based on Position Density Estimation")
    (description
     "Rare variant association test integrating variant position information.  It aims
to identify the presence of clusters of disease-risk variants in specific gene
regions.  For more details, please read the publication from Persyn et al.
(2017) <doi:10.1371/journal.pone.0179364>.")
    (license license:gpl2+)))

(define-public r-doem
  (package
    (name "r-doem")
    (version "0.0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DOEM" version))
       (sha256
        (base32 "0xfc4wzbh7gp4c8y7141kyycjxy5avjc8wwxzqyvf70l2if7x4id"))))
    (properties `((upstream-name . "DOEM")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DOEM")
    (synopsis
     "The Distributed Online Expectation Maximization Algorithms to Solve Parameters of Poisson Mixture Models")
    (description
     "The distributed online expectation maximization algorithms are used to solve
parameters of Poisson mixture models.  The philosophy of the package is
described in Guo, G. (2022) <doi:10.1080/02664763.2022.2053949>.")
    (license license:expat)))

(define-public r-doebioresearch
  (package
    (name "r-doebioresearch")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "doebioresearch" version))
       (sha256
        (base32 "1rmvb6pa71frvjszpsjaw3ahm70kyykrq6zfjqk8smgcg397k9pi"))))
    (properties `((upstream-name . "doebioresearch")))
    (build-system r-build-system)
    (propagated-inputs (list r-agricolae))
    (home-page "https://cran.r-project.org/package=doebioresearch")
    (synopsis "Analysis of Design of Experiments for Biological Research")
    (description
     "This package performs analysis of popular experimental designs used in the field
of biological research.  The designs covered are completely randomized design,
randomized complete block design, factorial completely randomized design,
factorial randomized complete block design, split plot design, strip plot design
and latin square design.  The analysis include analysis of variance, coefficient
of determination, normality test of residuals, standard error of mean, standard
error of difference and multiple comparison test of means.  The package has
functions for transformation of data and yield data conversion.  Some datasets
are also added in order to facilitate examples.")
    (license license:gpl3)))

(define-public r-doe-wrapper
  (package
    (name "r-doe-wrapper")
    (version "0.12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DoE.wrapper" version))
       (sha256
        (base32 "0n6z27gf7xcbyzjdq0kjm7ghddg5gygxyp3r9a7s5h40s0pfxbdm"))))
    (properties `((upstream-name . "DoE.wrapper")))
    (build-system r-build-system)
    (propagated-inputs (list r-rsm
                             r-lhs
                             r-frf2
                             r-doe-base
                             r-dicedesign
                             r-algdesign))
    (home-page "https://prof.bht-berlin.de/groemping/DoE/")
    (synopsis "Wrapper Package for Design of Experiments Functionality")
    (description
     "Various kinds of designs for (industrial) experiments can be created.  The
package uses, and sometimes enhances, design generation routines from other
packages.  So far, response surface designs from package rsm', Latin hypercube
samples from packages lhs and @code{DiceDesign}', and D-optimal designs from
package @code{AlgDesign} have been implemented.")
    (license license:gpl2+)))

(define-public r-doe-miparray
  (package
    (name "r-doe-miparray")
    (version "1.0-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DoE.MIParray" version))
       (sha256
        (base32 "0ginm4wqax2azcns4c17rgdfpclbmn058nq0lmpx90s4q7jfppax"))))
    (properties `((upstream-name . "DoE.MIParray")))
    (build-system r-build-system)
    (propagated-inputs (list r-doe-base r-combinat))
    (home-page "https://cran.r-project.org/package=DoE.MIParray")
    (synopsis "Creation of Arrays by Mixed Integer Programming")
    (description
     "CRAN packages @code{DoE.base} and Rmosek and non-'CRAN package gurobi are
enhanced with functionality for the creation of optimized arrays for
experimentation, where optimization is in terms of generalized minimum
aberration.  It is also possible to optimally extend existing arrays to larger
run size.  The package writes MPS (Mathematical Programming System) files for
use with any mixed integer optimization software that can process such files.
If at least one of the commercial products Gurobi or Mosek (free academic
licenses available for both) is available, the package also creates arrays by
optimization.  For installing Gurobi and its R package gurobi', follow
instructions at <https://www.gurobi.com/products/gurobi-optimizer/> and
<https://www.gurobi.com/documentation/7.5/refman/r_api_overview.html> (or higher
version).  For installing Mosek and its R package Rmosek', follow instructions
at <https://www.mosek.com/downloads/> and
<https://docs.mosek.com/8.1/rmosek/install-interface.html>, or use the
functionality in the stump CRAN R package Rmosek'.")
    (license license:gpl2+)))

(define-public r-doe-base
  (package
    (name "r-doe-base")
    (version "1.2-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DoE.base" version))
       (sha256
        (base32 "0lz0ilz145lhymb42b9yk4ysvm5zlbigc7ba600736cwnlgc0wn0"))))
    (properties `((upstream-name . "DoE.base")))
    (build-system r-build-system)
    (propagated-inputs (list r-vcd
                             r-partitions
                             r-numbers
                             r-mass
                             r-lattice
                             r-conf-design
                             r-combinat))
    (home-page "https://prof.bht-berlin.de/groemping/DoE/")
    (synopsis
     "Full Factorials, Orthogonal Arrays and Base Utilities for DoE Packages")
    (description
     "This package creates full factorial experimental designs and designs based on
orthogonal arrays for (industrial) experiments.  Provides diverse quality
criteria.  Provides utility functions for the class design, which is also used
by other packages for designed experiments.")
    (license license:gpl2+)))

(define-public r-dodgr
  (package
    (name "r-dodgr")
    (version "0.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dodgr" version))
       (sha256
        (base32 "12vsw3yi99jalhz41fiq67fhb4jk0rrcfwb06gfkrifalp2p9jws"))))
    (properties `((upstream-name . "dodgr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppthread
                             r-rcppparallel
                             r-rcpp
                             r-osmdata
                             r-memoise
                             r-magrittr
                             r-fs
                             r-digest
                             r-callr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/UrbanAnalyst/dodgr")
    (synopsis "Distances on Directed Graphs")
    (description
     "Distances on dual-weighted directed graphs using priority-queue shortest paths
(Padgham (2019) <doi:10.32866/6945>).  Weighted directed graphs have weights
from A to B which may differ from those from B to A. Dual-weighted directed
graphs have two sets of such weights.  A canonical example is a street network
to be used for routing in which routes are calculated by weighting distances
according to the type of way and mode of transport, yet lengths of routes must
be calculated from direct distances.")
    (license license:gpl3)))

(define-public r-dodge
  (package
    (name "r-dodge")
    (version "0.9-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Dodge" version))
       (sha256
        (base32 "0767n6hyspqrv5cgx3ghhai0qffj6haga7s86pv7mq8zvjcxjlzv"))))
    (properties `((upstream-name . "Dodge")))
    (build-system r-build-system)
    (home-page "https://github.com/ajrgodfrey/Dodge")
    (synopsis "Acceptance Sampling Ideas Originated by H.F. Dodge")
    (description
     "This package provides a variety of sampling plans are able to be compared using
evaluations of their operating characteristics (OC), average outgoing quality
(OQ), average total inspection (ATI) etc.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-docxtractr
  (package
    (name "r-docxtractr")
    (version "0.6.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "docxtractr" version))
       (sha256
        (base32 "1kki49g0sfhbx2d4swrkv21akws8ayrsd4h3v148xmzdlsrvhhiw"))))
    (properties `((upstream-name . "docxtractr")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2 r-purrr r-magrittr r-httr r-dplyr))
    (home-page "http://gitlab.com/hrbrmstr/docxtractr")
    (synopsis
     "Extract Data Tables and Comments from 'Microsoft' 'Word' Documents")
    (description
     "Microsoft Word docx files provide an XML structure that is fairly
straightforward to navigate, especially when it applies to Word tables and
comments.  Tools are provided to determine table count/structure, comment count
and also to extract/clean tables and comments from Microsoft Word docx
documents.  There is also nascent support for .doc and .pptx files.")
    (license license:expat)))

(define-public r-docusignr
  (package
    (name "r-docusignr")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "docuSignr" version))
       (sha256
        (base32 "0q90z31svbdnvylfr0yj2f0gahvpi089c1d5llvwqy8qc5p9fbqw"))))
    (properties `((upstream-name . "docuSignr")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-jsonlite r-httr))
    (home-page "https://github.com/CannaData/docuSignr")
    (synopsis "Connect to 'DocuSign' API")
    (description
     "Connect to the @code{DocuSign} Rest API
<https://www.docusign.com/p/RESTAPIGuide/RESTAPIGuide.htm>, which supports
embedded signing, and sending of documents.")
    (license license:gpl3)))

(define-public r-documenter
  (package
    (name "r-documenter")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "documenter" version))
       (sha256
        (base32 "0azwak0hm7xydamvaj42hy1kl8an9f90i2lm91va7n08vmn8k064"))))
    (properties `((upstream-name . "documenter")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml r-officer r-magrittr r-htmltools))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=documenter")
    (synopsis "Documents Files")
    (description
     "It is sometimes necessary to create documentation for all files in a directory.
Doing so by hand can be very tedious.  This task is made fast and reproducible
using the functionality of documenter'.  It aggregates all text files in a
directory and its subdirectories into a single word document in a semi-automated
fashion.")
    (license license:expat)))

(define-public r-document
  (package
    (name "r-document")
    (version "4.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "document" version))
       (sha256
        (base32 "1bkpyd1cg5r6g1jcwf6xqy0bviwd88i3k2jfzggzxpnva2s02y8y"))))
    (properties `((upstream-name . "document")))
    (build-system r-build-system)
    (propagated-inputs (list r-rstudioapi
                             r-roxygen2
                             r-rcmdcheck
                             r-fritools
                             r-desc
                             r-checkmate
                             r-callr))
    (native-inputs (list r-knitr))
    (home-page "https://gitlab.com/fvafrcu/document")
    (synopsis "Run 'roxygen2' on (Chunks of) Single Code Files")
    (description
     "Have you ever been tempted to create roxygen2'-style documentation comments for
one of your functions that was not part of one of your packages (yet)? This is
exactly what this package is about: running roxygen2 on (chunks of) a single
code file.")
    (license license:bsd-2)))

(define-public r-doctest
  (package
    (name "r-doctest")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "doctest" version))
       (sha256
        (base32 "04gicrh3fc3639ccwsg5c41axbsl7vkj5al6qcwlrf3jx8vaad64"))))
    (properties `((upstream-name . "doctest")))
    (build-system r-build-system)
    (propagated-inputs (list r-testthat
                             r-roxygen2
                             r-rlang
                             r-purrr
                             r-pkgload
                             r-fs
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://hughjonesd.github.io/doctest/")
    (synopsis "Generate Tests from Examples Using 'roxygen' and 'testthat'")
    (description
     "This package creates testthat tests from roxygen examples using simple tags.")
    (license license:expat)))

(define-public r-docstring
  (package
    (name "r-docstring")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "docstring" version))
       (sha256
        (base32 "19z5frhxbdc5c4vrkckgqbh9mx4d9w1icw8szsw9yadvbg48nlhl"))))
    (properties `((upstream-name . "docstring")))
    (build-system r-build-system)
    (propagated-inputs (list r-roxygen2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/dasonk/docstring")
    (synopsis "Provides Docstring Capabilities to R Functions")
    (description
     "This package provides the ability to display something analogous to Python's
docstrings within R. By allowing the user to document their functions as
comments at the beginning of their function without requiring putting the
function into a package we allow more users to easily provide documentation for
their functions.  The documentation can be viewed just like any other help files
for functions provided by packages as well.")
    (license license:gpl2)))

(define-public r-docore
  (package
    (name "r-docore")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "docore" version))
       (sha256
        (base32 "0x6c2yqr05v62ksn9a5swf44q8w7acfk00589mkipw643rg4l64y"))))
    (properties `((upstream-name . "docore")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma r-bit64))
    (home-page "https://cran.r-project.org/package=docore")
    (synopsis "Utility Functions for Scientific Coding")
    (description
     "Basic routines used in scientific coding, such as timing routines, vector/array
handing functions and I/O support routines.")
    (license license:gpl3)))

(define-public r-docopulae
  (package
    (name "r-docopulae")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "docopulae" version))
       (sha256
        (base32 "186mfiy4ygx6spnv7yrm5h0k6nf2g1xhk1l05iij39j5al5d9j21"))))
    (properties `((upstream-name . "docopulae")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=docopulae")
    (synopsis "Optimal Designs for Copula Models")
    (description
     "This package provides a direct approach to optimal designs for copula models
based on the Fisher information.  Provides flexible functions for building joint
PDFs, evaluating the Fisher information and finding optimal designs.  It
includes an extensible solution to summation and integration called nint',
functions for transforming, plotting and comparing designs, as well as a set of
tools for common low-level tasks.")
    (license license:expat)))

(define-public r-doconv
  (package
    (name "r-doconv")
    (version "0.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "doconv" version))
       (sha256
        (base32 "1ppzryd1kv5v96b2dwfzfy6cj7wx5sx8insj06gf2m2f442c8aph"))))
    (properties `((upstream-name . "doconv")))
    (build-system r-build-system)
    (inputs (list libreoffice))
    (propagated-inputs (list r-processx r-pdftools r-magick r-locatexec))
    (home-page "https://cran.r-project.org/package=doconv")
    (synopsis "Document Conversion to 'PDF' or 'PNG'")
    (description
     "It provides the ability to generate images from documents of different types.
Three main features are provided: functions for generating document thumbnails,
functions for performing visual tests of documents and a function for updating
fields and table of contents of a Microsoft Word or RTF document.  In order to
work, @code{LibreOffice} must be installed on the machine and or Microsoft
Word'.  If the latter is available, it can be used to produce PDF documents or
images identical to the originals; otherwise, @code{LibreOffice} is used and the
rendering can be sometimes different from the original documents.")
    (license license:expat)))

(define-public r-docknitr
  (package
    (name "r-docknitr")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "docknitr" version))
       (sha256
        (base32 "1mhdjv6yznzyx911f0m3m0i7jlzj7h12ikkxb9b6zj68bdplv30b"))))
    (properties `((upstream-name . "docknitr")))
    (build-system r-build-system)
    (inputs (list docker))
    (propagated-inputs (list r-sys r-rstudioapi r-knitr))
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=docknitr")
    (synopsis "Use Docker Images to Process Rmarkdown Blocks")
    (description
     "Gives you the ability to use arbitrary Docker images (including custom ones) to
process Rmarkdown code chunks.")
    (license license:expat)))

(define-public r-docket
  (package
    (name "r-docket")
    (version "1.33")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "docket" version))
       (sha256
        (base32 "0hwmnclknik9pkzncbnqabvln276lcyb3rh5dy1wxibq85qax84f"))))
    (properties `((upstream-name . "docket")))
    (build-system r-build-system)
    (propagated-inputs (list r-zip r-xml2 r-xml r-stringr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/JonathanConrad98/docket")
    (synopsis "Insert R Data into 'Word' Documents")
    (description
     "Populate data from an R environment into .doc and .docx templates.  Create a
template document in a program such as Word', and add strings encased in
guillemet characters to create flags (Â«exampleÂ»).  Use @code{getDictionary}()
to create a dictionary of flags and replacement values, then call docket() to
generate a populated document.")
    (license license:expat)))

(define-public r-dockerparallel
  (package
    (name "r-dockerparallel")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DockerParallel" version))
       (sha256
        (base32 "1fgs2f5czb05fiqxqp00qggni041ml4s3x05h9n4mmka9mwxi34b"))))
    (properties `((upstream-name . "DockerParallel")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Jiefei-Wang/DockerParallel")
    (synopsis
     "Using the Docker Container to Create R Workers on Local or Cloud Platform")
    (description
     "This is the core package that provides both the user API and developer API to
deploy the parallel cluster on the cloud using the container service.  The user
can call @code{clusterPreset}() to define the cloud service provider and
container and @code{makeDockerCluster}() to create the cluster.  The developer
should see \"developer's cookbook\" on how to define the cloud provider and
container.")
    (license license:gpl3)))

(define-public r-dockerfiler
  (package
    (name "r-dockerfiler")
    (version "0.2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dockerfiler" version))
       (sha256
        (base32 "0axiqvd3hbrb6br56qhjc5cpxv230x4j02ly9aa98gcrwwpc1w59"))))
    (properties `((upstream-name . "dockerfiler")))
    (build-system r-build-system)
    (propagated-inputs (list r-usethis
                             r-remotes
                             r-r6
                             r-purrr
                             r-pkgbuild
                             r-pak
                             r-memoise
                             r-jsonlite
                             r-glue
                             r-fs
                             r-desc
                             r-cli
                             r-attempt))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ThinkR-open/dockerfiler")
    (synopsis "Easy Dockerfile Creation from R")
    (description
     "Build a Dockerfile straight from your R session.  dockerfiler allows you to
create step by step a Dockerfile, and provide convenient tools to wrap R code
inside this Dockerfile.")
    (license license:expat)))

(define-public r-doc2concrete
  (package
    (name "r-doc2concrete")
    (version "0.6.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "doc2concrete" version))
       (sha256
        (base32 "13rgh3s13bbjgw3svh4sxz3kpv08p9gwxi9g55lb377nxachdzxr"))))
    (properties `((upstream-name . "doc2concrete")))
    (build-system r-build-system)
    (propagated-inputs (list r-tm
                             r-textstem
                             r-stringr
                             r-stringi
                             r-snowballc
                             r-quanteda
                             r-glmnet
                             r-english))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=doc2concrete")
    (synopsis "Measuring Concreteness in Natural Language")
    (description
     "Models for detecting concreteness in natural language.  This package is built in
support of Yeomans (2021) <doi:10.1016/j.obhdp.2020.10.008>, which reviews
linguistic models of concreteness in several domains.  Here, we provide an
implementation of the best-performing domain-general model (from Brysbaert et
al., (2014) <doi:10.3758/s13428-013-0403-5>) as well as two pre-trained models
for the feedback and plan-making domains.")
    (license license:expat)))

(define-public r-dobson
  (package
    (name "r-dobson")
    (version "0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dobson" version))
       (sha256
        (base32 "0xfn7s3wzrv1md40bdjrnjfiqyxg5c6lrcpnvayjdgrhxq161hhq"))))
    (properties `((upstream-name . "dobson")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dobson")
    (synopsis "Data from the GLM Book by Dobson and Barnett")
    (description
     "Example datasets from the book \"An Introduction to Generalised Linear Models\"
(Year: 2018, ISBN:9781138741515) by Dobson and Barnett.")
    (license license:gpl2)))

(define-public r-dobin
  (package
    (name "r-dobin")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dobin" version))
       (sha256
        (base32 "0j10f3smzkwv5j7k4szydn2jlspsb05mf91nzl8fzj803g5657ky"))))
    (properties `((upstream-name . "dobin")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma r-ggplot2 r-dbscan))
    (native-inputs (list r-knitr))
    (home-page "https://sevvandi.github.io/dobin/")
    (synopsis "Dimension Reduction for Outlier Detection")
    (description
     "This package provides a dimension reduction technique for outlier detection.
DOBIN: a Distance based Outlier @code{BasIs} using Neighbours, constructs a set
of basis vectors for outlier detection.  This is not an outlier detection
method; rather it is a pre-processing method for outlier detection.  It brings
outliers to the fore-front using fewer basis vectors (Kandanaarachchi, Hyndman
2020) <doi:10.1080/10618600.2020.1807353>.")
    (license license:expat)))

(define-public r-do3pca
  (package
    (name "r-do3pca")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "do3PCA" version))
       (sha256
        (base32 "11ilwy7iqia6nxqphycq526crg5q1y0giqfy8q66ibj3zzql8xbs"))))
    (properties `((upstream-name . "do3PCA")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdimtools
                             r-ratematrix
                             r-phytools
                             r-nloptr
                             r-mclust
                             r-matrixcalc
                             r-ape))
    (home-page "https://cran.r-project.org/package=do3PCA")
    (synopsis "Probabilistic Phylogenetic Principal Component Analysis")
    (description
     "Estimates probabilistic phylogenetic Principal Component Analysis (PCA) and
non-phylogenetic probabilistic PCA. Provides methods to implement alternative
models of trait evolution including Brownian motion (BM), Ornstein-Uhlenbeck
(OU), Early Burst (EB), and Pagel's lambda.  Also provides flexible biplot
functions.")
    (license license:gpl2+)))

(define-public r-do
  (package
    (name "r-do")
    (version "2.0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "do" version))
       (sha256
        (base32 "1qfhlhlyd1yg1jfsf492nhxv9n8giqjc2rdv7wgxd4bpgcx6vi9h"))))
    (properties `((upstream-name . "do")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-usethis
                             r-tmcn
                             r-tidyselect
                             r-tidyr
                             r-stringr
                             r-rvest
                             r-rstudioapi
                             r-reshape2
                             r-plyr
                             r-openxlsx
                             r-httr
                             r-desc
                             r-data-table
                             r-crayon))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/yikeshu0611/do")
    (synopsis "Data Operator")
    (description
     "Flexibly convert data between long and wide format using just two functions:
reshape_@code{toLong}() and reshape_@code{toWide}().")
    (license license:gpl3)))

(define-public r-dnr
  (package
    (name "r-dnr")
    (version "0.3.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dnr" version))
       (sha256
        (base32 "16s06jvwmvhxgvrmfav1xfszjrn7j2cm4jw5xyx6w5lb5434kzcq"))))
    (properties `((upstream-name . "dnr")))
    (build-system r-build-system)
    (propagated-inputs (list r-sna
                             r-network
                             r-igraph
                             r-glmnet
                             r-ergm
                             r-arm))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dnr")
    (synopsis
     "Simulate Dynamic Networks using Exponential Random Graph Models (ERGM) Family")
    (description
     "This package provides functions are provided to fit temporal lag models to
dynamic networks.  The models are build on top of exponential random graph
models (ERGM) framework.  There are functions for simulating or forecasting
networks for future time points.  Abhirup Mallik & Zack W. Almquist (2019)
Stable Multiple Time Step Simulation/Prediction From Lagged Dynamic Network
Regression Models, Journal of Computational and Graphical Statistics, 28:4,
967-979, <DOI: 10.1080/10618600.2019.1594834>.")
    (license license:gpl3)))

(define-public r-dnn
  (package
    (name "r-dnn")
    (version "0.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dnn" version))
       (sha256
        (base32 "0mij6d69hhzrcp3yvqwmajhn4bm2bnc3lk9hrkh5ly2a21g46yg4"))))
    (properties `((upstream-name . "dnn")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rcpparmadillo r-rcpp r-ggplot2))
    (home-page "https://cran.r-project.org/package=dnn")
    (synopsis "Deep Neural Network Tools for Probability and Statistic Models")
    (description
     "This package contains tools to build deep neural network with flexible users
define loss function and probability models.  Several applications included in
this package are, 1) The (@code{deepAFT}) model, a deep neural network model for
accelerated failure time (AFT) model for survival data.  2) The (@code{deepGLM})
model, a deep neural network model for generalized linear model (glm) for
continuous, categorical and Poisson data.")
    (license license:gpl2+)))

(define-public r-dnmf
  (package
    (name "r-dnmf")
    (version "1.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DNMF" version))
       (sha256
        (base32 "10zzbi0jywlnq4hxqb0dh7xrn8gj75asd4yc1mcl2dbjpi68sn56"))))
    (properties `((upstream-name . "DNMF")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-gplots r-foreach r-doparallel))
    (home-page "https://github.com/zhilongjia/DNMF")
    (synopsis "Discriminant Non-Negative Matrix Factorization")
    (description
     "Discriminant Non-Negative Matrix Factorization aims to extend the Non-negative
Matrix Factorization algorithm in order to extract features that enforce not
only the spatial locality, but also the separability between classes in a
discriminant manner.  It refers to three article, Zafeiriou, Stefanos, et al.
\"Exploiting discriminant information in nonnegative matrix factorization with
application to frontal face verification.\" Neural Networks, IEEE Transactions on
17.3 (2006): 683-695.  Kim, Bo-Kyeong, and Soo-Young Lee. \"Spectral Feature
Extraction Using @code{dNMF} for Emotion Recognition in Vowel Sounds.\" Neural
Information Processing.  Springer Berlin Heidelberg, 2013.  and Lee, Soo-Young,
Hyun-Ah Song, and Shun-ichi Amari. \"A new discriminant NMF algorithm and its
application to the extraction of subtle emotional differences in speech.\"
Cognitive neurodynamics 6.6 (2012): 525-535.")
    (license license:gpl2+)))

(define-public r-dnlc
  (package
    (name "r-dnlc")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DNLC" version))
       (sha256
        (base32 "05410xgpfjsydjmnzry454qcjpws9vhh252q2xq7l0scdj87ly00"))))
    (properties `((upstream-name . "DNLC")))
    (build-system r-build-system)
    (propagated-inputs (list r-spdep
                             r-mvtnorm
                             r-locfdr
                             r-igraph
                             r-gostats
                             r-fdrtool
                             r-catools))
    (home-page "https://cran.r-project.org/package=DNLC")
    (synopsis "Differential Network Local Consistency Analysis")
    (description
     "Using Local Moran's I for detection of differential network local consistency.")
    (license license:gpl2+)))

(define-public r-dnh4
  (package
    (name "r-dnh4")
    (version "0.1.12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DNH4" version))
       (sha256
        (base32 "0g3ibacsbsk34b6411j3n3q9dxqq1iqdnisppmmq7s2bp94ab771"))))
    (properties `((upstream-name . "DNH4")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-tibble r-rvest r-httr))
    (home-page "https://forkonlp.github.io/DNH4/")
    (synopsis "Crawling for Daum News Text")
    (description
     "This package provides some utils to get Korean text sample from news articles in
Daum which is popular news portal service in Korea.")
    (license license:expat)))

(define-public r-dng
  (package
    (name "r-dng")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dng" version))
       (sha256
        (base32 "0yi1fs4yvlsy3j128l7s5kwq8mhdd5fr74y2bzj7cjrxi7wgz2hg"))))
    (properties `((upstream-name . "dng")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://github.com/feng-li/dng/")
    (synopsis "Distributions and Gradients")
    (description
     "This package provides density, distribution function, quantile function and
random generation for the split normal and split-t distributions, and computes
their mean, variance, skewness and kurtosis for the two distributions (Li, F,
Villani, M. and Kohn, R. (2010) <doi:10.1016/j.jspi.2010.04.031>).")
    (license license:gpl2+)))

(define-public r-dnetfinder
  (package
    (name "r-dnetfinder")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DNetFinder" version))
       (sha256
        (base32 "1hd3yx3f71rwxn2iqjk7v3vwb6p3z20fi09csnhjkq5l3wk4bkp9"))))
    (properties `((upstream-name . "DNetFinder")))
    (build-system r-build-system)
    (propagated-inputs (list r-flare))
    (home-page "https://cran.r-project.org/package=DNetFinder")
    (synopsis
     "Estimating Differential Networks under Semiparametric Gaussian Graphical Models")
    (description
     "This package provides a modified hierarchical test (Liu (2017)
<doi:10.1214/17-AOS1539>) for detecting the structural difference between two
Semiparametric Gaussian graphical models.  The multiple testing procedure
asymptotically controls the false discovery rate (FDR) at a user-specified
level.  To construct the test statistic, a truncated estimator is used to
approximate the transformation functions and two R functions including
@code{lassoGGM}() and @code{lassoNPN}() are provided to compute the lasso
estimates of the regression coefficients.")
    (license license:gpl3)))

(define-public r-dndr
  (package
    (name "r-dndr")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dndR" version))
       (sha256
        (base32 "1m1s48acsdfa5sn4ikqx4kp804q7v2a5w93qxz3pr5a9g1s57yng"))))
    (properties `((upstream-name . "dndR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-purrr
                             r-magrittr
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://njlyon0.github.io/dndR/")
    (synopsis "Dungeons & Dragons Functions for Players and Dungeon Masters")
    (description
     "The goal of @code{dndR} is to provide a suite of Dungeons & Dragons related
functions.  This package is meant to be useful both to players and Dungeon
Masters (DMs).  All functions currently focus on Fifth Edition (a.k.a. \"5e\") but
once the next edition is published functions will likely be expanded to include
any rule changes.")
    (license license:expat)))

(define-public r-dnatools
  (package
    (name "r-dnatools")
    (version "0.2-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DNAtools" version))
       (sha256
        (base32 "1xcpp5jw5xq6a6ccq8jsd4d7ailv3iv8k7b1bbz531vhy9im2dzs"))))
    (properties `((upstream-name . "DNAtools")))
    (build-system r-build-system)
    (propagated-inputs (list r-rsolnp r-rcppprogress r-rcppparallel r-rcpp
                             r-multicool))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DNAtools")
    (synopsis "Tools for Analysing Forensic Genetic DNA Data")
    (description
     "Computationally efficient tools for comparing all pairs of profiles in a DNA
database.  The expectation and covariance of the summary statistic is
implemented for fast computing.  Routines for estimating proportions of close
related individuals are available.  The use of wildcards (also called F-
designation) is implemented.  Dedicated functions ease plotting the results.
See Tvedebrink et al. (2012) <doi:10.1016/j.fsigen.2011.08.001>.  Compute the
distribution of the numbers of alleles in DNA mixtures.  See Tvedebrink (2013)
<doi:10.1016/j.fsigss.2013.10.142>.")
    (license (list license:gpl2+
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-dnaseqtest
  (package
    (name "r-dnaseqtest")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DNAseqtest" version))
       (sha256
        (base32 "1mpmf40vrpw8m75rlqchsnyrz12pgg5bkz7wfca5yy5sbbiwk5pf"))))
    (properties `((upstream-name . "DNAseqtest")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DNAseqtest")
    (synopsis "Generating and Testing DNA Sequences")
    (description
     "Generates DNA sequences based on Markov model techniques for matched sequences.
This can be generalized to several sequences.  The sequences (taxa) are then
arranged in an evolutionary tree (phylogenetic tree) depicting how taxa diverge
from their common ancestors.  This gives the tests and estimation methods for
the parameters of different models.  Standard phylogenetic methods assume
stationarity, homogeneity and reversibility for the Markov processes, and often
impose further restrictions on the parameters.")
    (license license:gpl2)))

(define-public r-dnamotif
  (package
    (name "r-dnamotif")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DNAmotif" version))
       (sha256
        (base32 "1cdbickgjdf766m4cka9vl3x4zdw071w54ycj3l60xhcd8gxn8b1"))))
    (properties `((upstream-name . "DNAmotif")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-biostrings))
    (home-page "https://cran.r-project.org/package=DNAmotif")
    (synopsis "DNA Sequence Motifs")
    (description
     "Motifs within biological sequences show a significant role.  This package
utilizes a user-defined threshold value (window size and similarity) to create
consensus segments or motifs through local alignment of dynamic programming with
gap and it calculates the frequency of each identified motif, offering a
detailed view of their prevalence within the dataset.  It allows for thorough
exploration and understanding of sequence patterns and their biological
importance.")
    (license license:gpl3)))

(define-public r-dnamixtureslite
  (package
    (name "r-dnamixtureslite")
    (version "0.0-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DNAmixturesLite" version))
       (sha256
        (base32 "14f373an89ra7v2q3mlc4s7svriydzs7jp8zp3arsbg4ali1g037"))))
    (properties `((upstream-name . "DNAmixturesLite")))
    (build-system r-build-system)
    (propagated-inputs (list r-rsolnp r-numderiv r-matrix r-grbase r-graven))
    (home-page "https://cran.r-project.org/package=DNAmixturesLite")
    (synopsis "Statistical Inference for Mixed Traces of DNA (Lite-Version)")
    (description
     "Statistical methods for DNA mixture analysis.  This package is a lite-version of
the DNAmixtures package to allow users without a HUGIN software license to
experiment with the statistical methodology.  While the lite-version aims to
provide the full functionality it is noticeably less efficient than the original
DNAmixtures package.  For details on implementation and methodology see
<https://dnamixtures.r-forge.r-project.org/>.")
    (license license:gpl2+)))

(define-public r-dmutate
  (package
    (name "r-dmutate")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dmutate" version))
       (sha256
        (base32 "1dxx4v9fg0cd2m5lwk3j6n9g6n9zqr7rs75yiz3m3q8cpw1pjqpk"))))
    (properties `((upstream-name . "dmutate")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-dplyr))
    (home-page "https://github.com/kylebaron/dmutate")
    (synopsis "Mutate Data Frames with Random Variates")
    (description
     "Work within the dplyr workflow to add random variates to your data frame.
Variates can be added at any level of an existing column.  Also, bounds can be
specified for simulated variates.")
    (license license:gpl2+)))

(define-public r-dmtools
  (package
    (name "r-dmtools")
    (version "0.2.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dmtools" version))
       (sha256
        (base32 "0z77whal18sxmfqalv39w85vnc84c838yh3dp144v7w198n095fy"))))
    (properties `((upstream-name . "dmtools")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-readxl
                             r-purrr
                             r-progress
                             r-magrittr
                             r-lubridate
                             r-httr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/KonstantinRyabov/dmtools")
    (synopsis "Tools for Clinical Data Management")
    (description
     "For checking the dataset from EDC(Electronic Data Capture) in clinical trials.
dmtools reshape your dataset in a tidy view and check events.  You can reshape
the dataset and choose your target to check, for example, the laboratory
reference range.")
    (license license:expat)))

(define-public r-dmtl
  (package
    (name "r-dmtl")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DMTL" version))
       (sha256
        (base32 "0z6l1sylw4ib1mgqjnrmxh2q56vazg2i7xxiw1g4gm28iq44r2n0"))))
    (properties `((upstream-name . "DMTL")))
    (build-system r-build-system)
    (propagated-inputs (list r-randomforest r-ks r-kernlab r-glmnet r-caret))
    (home-page "https://github.com/dhruba018/DMTL")
    (synopsis
     "Tools for Applying Distribution Mapping Based Transfer Learning")
    (description
     "Implementation of a transfer learning framework employing distribution mapping
based domain transfer.  Uses the renowned concept of histogram matching (see
Gonzalez and Fittes (1977) <doi:10.1016/0094-114X(77)90062-3>, Gonzalez and
Woods (2008) <isbn:9780131687288>) and extends it to include distribution
measures like kernel density estimates (KDE; see Wand and Jones (1995)
<isbn:978-0-412-55270-0>, Jones et al. (1996) <doi:10.2307/2291420).  In the
typical application scenario, one can use the underlying sample distributions
(histogram or KDE) to generate a map between two distinct but related domains to
transfer the target data to the source domain and utilize the available source
data for better predictive modeling design.  Suitable for the case where a
one-to-one sample matching is not possible, thus one needs to transform the
underlying data distribution to utilize the more available data for modeling.")
    (license license:gpl3)))

(define-public r-dmtest
  (package
    (name "r-dmtest")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DMtest" version))
       (sha256
        (base32 "1bziiyv63lcbmd79fykjj6b63igbbw0pwiq37k7q9l5vij6jfcj9"))))
    (properties `((upstream-name . "DMtest")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrixstats r-foreach r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DMtest")
    (synopsis "Differential Methylation Tests (DMtest)")
    (description
     "Several tests for differential methylation in methylation array data, including
one-sided differential mean and variance test.  Methods used in the package
refer to Dai, J, Wang, X, Chen, H and others (2021) \"Incorporating increased
variability in discovering cancer methylation markers\", Biostatistics,
submitted.")
    (license license:gpl2+)))

(define-public r-dmrnet
  (package
    (name "r-dmrnet")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DMRnet" version))
       (sha256
        (base32 "11niqsnkyrcwsirrsjp7gkdcjgdlddah92i5mndw4idadjg0cnrc"))))
    (properties `((upstream-name . "DMRnet")))
    (build-system r-build-system)
    (propagated-inputs (list r-hclust1d r-grpreg r-glmnet))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/SzymonNowakowski/DMRnet")
    (synopsis
     "Delete or Merge Regressors Algorithms for Linear and Logistic Model Selection and High-Dimensional Data")
    (description
     "Model selection algorithms for regression and classification, where the
predictors can be continuous or categorical and the number of regressors may
exceed the number of observations.  The selected model consists of a subset of
numerical regressors and partitions of levels of factors.  Szymon Nowakowski,
Piotr Pokarowski, Wojciech Rejchel and Agnieszka SoÅtys, 2023.  Improving Group
Lasso for High-Dimensional Categorical Data.  In: Computational Science â ICCS
2023.  Lecture Notes in Computer Science, vol 14074, p.  455-470.  Springer,
Cham. <doi:10.1007/978-3-031-36021-3_47>.  Aleksandra Maj-KaÅska, Piotr
Pokarowski and Agnieszka Prochenka, 2015.  Delete or merge regressors for linear
model selection.  Electronic Journal of Statistics 9(2): 1749-1778.
<doi:10.1214/15-EJS1050>.  Piotr Pokarowski and Jan Mielniczuk, 2015.  Combined
l1 and greedy l0 penalized least squares for linear model selection.  Journal of
Machine Learning Research 16(29): 961-992.
<https://www.jmlr.org/papers/volume16/pokarowski15a/pokarowski15a.pdf>.  Piotr
Pokarowski, Wojciech Rejchel, Agnieszka SoÅtys, MichaÅ Frej and Jan
Mielniczuk, 2022.  Improving Lasso for model selection and prediction.
Scandinavian Journal of Statistics, 49(2): 831â863. <doi:10.1111/sjos.12546>.")
    (license license:gpl2)))

(define-public r-dmri-tracking
  (package
    (name "r-dmri-tracking")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dmri.tracking" version))
       (sha256
        (base32 "0aij0n5p6cp75r5b3bfpmhnmz2nixbb4kwacixg66g6kilwj3sis"))))
    (properties `((upstream-name . "dmri.tracking")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgl))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/vic-dragon/dmri.tracking")
    (synopsis "DiST - Diffusion Direction Smoothing and Tracking")
    (description
     "It provides functions to apply the deterministic tracking algorithm -
@code{DiST} (Wong et al 2016) <doi:10.1214/15-AOAS880> and to plot tractography
results.")
    (license license:expat)))

(define-public r-dmq
  (package
    (name "r-dmq")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DMQ" version))
       (sha256
        (base32 "1ygaqznvblzr3r1x7zl1l8sazh3sbs1zgagawwlwl42g8sdl57az"))))
    (properties `((upstream-name . "DMQ")))
    (build-system r-build-system)
    (propagated-inputs (list r-rsolnp r-rcpparmadillo r-rcpp r-mass r-deoptim))
    (home-page "https://cran.r-project.org/package=DMQ")
    (synopsis "Dynamic Multiple Quantile (DMQ) Model")
    (description
     "Perform estimation, prediction, and simulations using the Dynamic Multiple
Quantile model of Catania and Luati (2023) <doi:10.1016/j.jeconom.2022.11.002>.
Can be used to estimate a set of conditional time-varying quantiles of a time
series that do not cross.")
    (license license:gpl3)))

(define-public r-dmod
  (package
    (name "r-dmod")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dMod" version))
       (sha256
        (base32 "1fnv3f5xlng8f3df5hvxncfnnadzwcsdiklrb2g67llf3m06bq74"))))
    (properties `((upstream-name . "dMod")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-rootsolve
                             r-plyr
                             r-ggplot2
                             r-foreach
                             r-dplyr
                             r-doparallel
                             r-desolve
                             r-code))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dMod")
    (synopsis "Dynamic Modeling and Parameter Estimation in ODE Models")
    (description
     "The framework provides functions to generate ODEs of reaction networks,
parameter transformations, observation functions, residual functions, etc.  The
framework follows the paradigm that derivative information should be used for
optimization whenever possible.  Therefore, all major functions produce and can
handle expressions for symbolic derivatives.  The methods used in @code{dMod}
were published in Kaschek et al, 2019, <doi:10.18637/jss.v088.i10>.")
    (license license:gpl2+)))

(define-public r-dmmf
  (package
    (name "r-dmmf")
    (version "0.5.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DMMF" version))
       (sha256
        (base32 "0bda65253q45m9bj923zylafnlwnxwyyk730pjqynz11z8vyibj6"))))
    (properties `((upstream-name . "DMMF")))
    (build-system r-build-system)
    (propagated-inputs (list r-raster))
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=DMMF")
    (synopsis "Daily Based Morgan-Morgan-Finney (DMMF) Soil Erosion Model")
    (description
     "This package implements the daily based Morgan-Morgan-Finney (DMMF) soil erosion
model (Choi et al., 2017 <doi:10.3390/w9040278>) for estimating surface runoff
and sediment budgets from a field or a catchment on a daily basis.")
    (license license:gpl2+)))

(define-public r-dmm
  (package
    (name "r-dmm")
    (version "2.1-10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dmm" version))
       (sha256
        (base32 "1p4g0nb246val8p6l2jj665yp0aa4jxxjyi384i2jcwxyy5hmiyb"))))
    (properties `((upstream-name . "dmm")))
    (build-system r-build-system)
    (propagated-inputs (list r-robustbase r-pls r-nadiv r-matrix r-mass))
    (home-page "https://cran.r-project.org/package=dmm")
    (synopsis "Dyadic Mixed Model for Pedigree Data")
    (description
     "Dyadic mixed model analysis with multi-trait responses and pedigree-based
partitioning of individual variation into a range of environmental and genetic
variance components for individual and maternal effects.  Method documented in
@code{dmmOverview.pdf}; dmm is an implementation of dispersion mean model
described by Searle et al. (1992) \"Variance Components\", Wiley, NY.")
    (license (list license:gpl2 license:gpl2+ license:gpl3))))

(define-public r-dmlalg
  (package
    (name "r-dmlalg")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dmlalg" version))
       (sha256
        (base32 "1ixjpalg3q0wnddrli6v66kky3pxf90sjgiia8jhk4nds0h58a72"))))
    (properties `((upstream-name . "dmlalg")))
    (build-system r-build-system)
    (propagated-inputs (list r-randomforest r-matrixcalc r-lme4 r-glmnet))
    (home-page "https://gitlab.math.ethz.ch/ecorinne/dmlalg.git")
    (synopsis "Double Machine Learning Algorithms")
    (description
     "Implementation of double machine learning (DML) algorithms in R, based on
Emmenegger and Buehlmann (2021) \"Regularizing Double Machine Learning in
Partially Linear Endogenous Models\" <@code{arXiv:2101.12525>} and Emmenegger and
Buehlmann (2021) <@code{arXiv:2108.13657>} \"Double Machine Learning for
Partially Linear Mixed-Effects Models with Repeated Measurements\".  First part:
our goal is to perform inference for the linear parameter in partially linear
models with confounding variables.  The standard DML estimator of the linear
parameter has a two-stage least squares interpretation, which can lead to a
large variance and overwide confidence intervals.  We apply regularization to
reduce the variance of the estimator, which produces narrower confidence
intervals that are approximately valid.  Nuisance terms can be flexibly
estimated with machine learning algorithms.  Second part: our goal is to
estimate and perform inference for the linear coefficient in a partially linear
mixed-effects model with DML. Machine learning algorithms allows us to
incorporate more complex interaction structures and high-dimensional variables.")
    (license license:gpl3+)))

(define-public r-dml
  (package
    (name "r-dml")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dml" version))
       (sha256
        (base32 "0z1dalgxh5nhrac49vh60d5awzjylc8b8mn5fk379c324milm59l"))))
    (properties `((upstream-name . "dml")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-lfda))
    (home-page "https://github.com/terrytangyuan/dml")
    (synopsis "Distance Metric Learning in R")
    (description
     "The state-of-the-art algorithms for distance metric learning, including global
and local methods such as Relevant Component Analysis, Discriminative Component
Analysis, Local Fisher Discriminant Analysis, etc.  These distance metric
learning methods are widely applied in feature extraction, dimensionality
reduction, clustering, classification, information retrieval, and computer
vision problems.")
    (license license:expat)))

(define-public r-dmetatools
  (package
    (name "r-dmetatools")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dmetatools" version))
       (sha256
        (base32 "0n62lfga8br3p3vn10rs56mbrbsrr7b6m8cb15za52nm2qn9m3a5"))))
    (properties `((upstream-name . "dmetatools")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-mada))
    (home-page "https://cran.r-project.org/package=dmetatools")
    (synopsis
     "Computational Tools for Meta-Analysis of Diagnostic Accuracy Test")
    (description
     "Computational tools for meta-analysis of diagnostic accuracy test.
Bootstrap-based computational methods of the confidence interval for AUC of
summary ROC curve and some related AUC-based inference methods are available
(Noma et al. (2021) <doi:10.1080/23737484.2021.1894408>).")
    (license license:gpl3)))

(define-public r-dmcfun
  (package
    (name "r-dmcfun")
    (version "4.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DMCfun" version))
       (sha256
        (base32 "0r68ax8yic138wwy5ndf72vfsjlw12f3v5afyn748is86s6vnj76"))))
    (properties `((upstream-name . "DMCfun")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rcpp
                             r-pbapply
                             r-dplyr
                             r-deoptim
                             r-bh))
    (home-page "https://github.com/igmmgi/DMCfun")
    (synopsis "Diffusion Model of Conflict (DMC) in Reaction Time Tasks")
    (description
     "DMC model simulation detailed in Ulrich, R., Schroeter, H., Leuthold, H., &
Birngruber, T. (2015).  Automatic and controlled stimulus processing in conflict
tasks: Superimposed diffusion processes and delta functions.  Cognitive
Psychology, 78, 148-174.  Ulrich et al. (2015)
<doi:10.1016/j.cogpsych.2015.02.005>.  Decision processes within choice
reaction-time (CRT) tasks are often modelled using evidence accumulation models
(EAMs), a variation of which is the Diffusion Decision Model (DDM, for a review,
see Ratcliff & @code{McKoon}, 2008).  Ulrich et al. (2015) introduced a
Diffusion Model for Conflict tasks (DMC).  The DMC model combines common
features from within standard diffusion models with the addition of superimposed
controlled and automatic activation.  The DMC model is used to explain
distributional reaction time (and error rate) patterns in common behavioural
conflict-like tasks (e.g., Flanker task, Simon task).  This R-package implements
the DMC model and provides functionality to fit the model to observed data.
Further details are provided in the following paper: Mackenzie, I.G., &
Dudschig, C. (2021).  DMCfun: An R package for fitting Diffusion Model of
Conflict (DMC) to reaction time and error rate data.  Methods in Psychology,
100074. <doi:10.1016/j.metip.2021.100074>.")
    (license license:expat)))

(define-public r-dmbc
  (package
    (name "r-dmbc")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dmbc" version))
       (sha256
        (base32 "0rbahb7590sy6d975wd0g00x5xxfxjzsgywzcc7wqd6lyqkmn3v3"))))
    (properties `((upstream-name . "dmbc")))
    (build-system r-build-system)
    (propagated-inputs (list r-robustx
                             r-robustbase
                             r-rcppprogress
                             r-rcpparmadillo
                             r-rcpp
                             r-modeltools
                             r-ggrepel
                             r-ggplot2
                             r-coda
                             r-bayesplot
                             r-abind))
    (home-page "https://cran.r-project.org/package=dmbc")
    (synopsis "Model Based Clustering of Binary Dissimilarity Measurements")
    (description
     "This package provides functions for fitting a Bayesian model for grouping binary
dissimilarity matrices in homogeneous clusters.  Currently, it includes methods
only for binary data (<doi:10.18637/jss.v100.i16>).")
    (license license:gpl2+)))

(define-public r-dmai
  (package
    (name "r-dmai")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dmai" version))
       (sha256
        (base32 "0fdcvy524cc0gmr04mn82023y4xvfx0477l3h41sjbwk1qrfpdk4"))))
    (properties `((upstream-name . "dmai")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-magrittr
                             r-ggplot2
                             r-dplyr))
    (home-page "https://github.com/myaseen208/dmai/")
    (synopsis "Divisia Monetary Aggregates Index")
    (description
     "This package provides functions to calculate Divisia monetary aggregates index
as given in Barnett, W. A. (1980) (<DOI:10.1016/0304-4076(80)90070-6>).")
    (license license:gpl2)))

(define-public r-dma
  (package
    (name "r-dma")
    (version "1.4-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dma" version))
       (sha256
        (base32 "003snr09hazszwqnvjrbv8vyz6ihgcfcfhrlshg451dddn920615"))))
    (properties `((upstream-name . "dma")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=dma")
    (synopsis "Dynamic Model Averaging")
    (description "Dynamic model averaging for binary and continuous outcomes.")
    (license license:gpl2)))

(define-public r-dm
  (package
    (name "r-dm")
    (version "1.0.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dm" version))
       (sha256
        (base32 "0ngh74kkzngpq6qrz8aabsv7jgmbxggbplin5jbgjalyi21gfm40"))))
    (properties `((upstream-name . "dm")))
    (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-tidyselect
                             r-tidyr
                             r-tibble
                             r-rlang
                             r-purrr
                             r-memoise
                             r-lifecycle
                             r-igraph
                             r-glue
                             r-dplyr
                             r-cli
                             r-backports))
    (native-inputs (list r-knitr esbuild))
    (home-page "https://dm.cynkra.com/")
    (synopsis "Relational Data Models")
    (description
     "This package provides tools for working with multiple related tables, stored as
data frames or in a relational database.  Multiple tables (data and metadata)
are stored in a compound object, which can then be manipulated with a
pipe-friendly syntax.")
    (license license:expat)))

(define-public r-dlstats
  (package
    (name "r-dlstats")
    (version "0.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dlstats" version))
       (sha256
        (base32 "1qc7gp2glkbhnblqckz3l7jmlsarf3jlsp6cqm4wm0s87z038r9a"))))
    (properties `((upstream-name . "dlstats")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales r-rcolorbrewer r-magrittr r-jsonlite
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/GuangchuangYu/dlstats")
    (synopsis "Download Stats of R Packages")
    (description
     "Monthly download stats of CRAN and Bioconductor packages.  Download stats of
CRAN packages is from the RStudio CRAN mirror', see
<https://cranlogs.r-pkg.org:443>.  Bioconductor package download stats is at
<https://bioconductor.org/packages/stats/>.")
    (license license:artistic2.0)))

(define-public r-dlsem
  (package
    (name "r-dlsem")
    (version "2.4.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dlsem" version))
       (sha256
        (base32 "1h3bwqqpfjkl41b2mbfhsj0pi9kri0h0i28wiid6arjrmm87nsf8"))))
    (properties `((upstream-name . "dlsem")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgraphviz r-graph))
    (home-page "https://cran.r-project.org/package=dlsem")
    (synopsis "Distributed-Lag Linear Structural Equation Models")
    (description
     "Inference functionalities for distributed-lag linear structural equation models
(DLSEMs).  DLSEMs are Markovian structural causal models where each factor of
the joint probability distribution is a distributed-lag linear regression with
constrained lag shapes (Magrini, 2018 <doi:10.2478/bile-2018-0012>; Magrini et
al., 2019 <doi:10.1007/s11135-019-00855-z>).  DLSEMs account for temporal delays
in the dependence relationships among the variables through a single parameter
per covariate, thus allowing to perform dynamic causal inference in a feasible
fashion.  Endpoint-constrained quadratic, quadratic decreasing, linearly
decreasing and gamma lag shapes are available.")
    (license license:gpl2)))

(define-public r-dlr
  (package
    (name "r-dlr")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dlr" version))
       (sha256
        (base32 "13gr8rk8igbypq9mg00pyk2pjczxr1ghkj5287gijxnxch7zdknc"))))
    (properties `((upstream-name . "dlr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-rappdirs r-fs r-digest))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/macmillancontentscience/dlr")
    (synopsis "Download and Cache Files Safely")
    (description
     "The goal of dlr is to provide a friendly wrapper around the common pattern of
downloading a file if that file does not already exist locally.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-dlpca
  (package
    (name "r-dlpca")
    (version "0.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DLPCA" version))
       (sha256
        (base32 "1fjpkn32rx8m18k6pr2cf180wqr01f9kviqibwsghnkrhbzcgpiy"))))
    (properties `((upstream-name . "DLPCA")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DLPCA")
    (synopsis "The Distributed Local PCA Algorithm")
    (description
     "Algorithm to handle with optimal subset selection for distributed local
principal component analysis.  The philosophy of the package is described in Guo
G. (2020) <doi:10.1080/02331888.2020.1823979>.")
    (license license:expat)))

(define-public r-dlookr
  (package
    (name "r-dlookr")
    (version "0.6.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dlookr" version))
       (sha256
        (base32 "047f616pcjvv9bd7crphrbvql5qn6j50495px9244fl50vyklzx6"))))
    (properties `((upstream-name . "dlookr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-sysfonts
                             r-showtext
                             r-shiny
                             r-rpart
                             r-rmarkdown
                             r-rlang
                             r-reactable
                             r-purrr
                             r-pagedown
                             r-mice
                             r-knitr
                             r-kableextra
                             r-htmltools
                             r-hrbrthemes
                             r-gridextra
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/choonghyunryu/dlookr/")
    (synopsis "Tools for Data Diagnosis, Exploration, Transformation")
    (description
     "This package provides a collection of tools that support data diagnosis,
exploration, and transformation.  Data diagnostics provides information and
visualization of missing values, outliers, and unique and negative values to
help you understand the distribution and quality of your data.  Data exploration
provides information and visualization of the descriptive statistics of
univariate variables, normality tests and outliers, correlation of two
variables, and the relationship between the target variable and predictor.  Data
transformation supports binning for categorizing continuous variables, imputes
missing values and outliers, and resolves skewness.  And it creates automated
reports that support these three tasks.")
    (license license:gpl2)))

(define-public r-dlnm
  (package
    (name "r-dlnm")
    (version "2.4.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dlnm" version))
       (sha256
        (base32 "0mbww28n95vnd6wrn1b4mfsdvnyffa8mr6ws4jqmqdc23nydl9p4"))))
    (properties `((upstream-name . "dlnm")))
    (build-system r-build-system)
    (propagated-inputs (list r-tsmodel r-nlme r-mgcv))
    (home-page "https://github.com/gasparrini/dlnm")
    (synopsis "Distributed Lag Non-Linear Models")
    (description
     "Collection of functions for distributed lag linear and non-linear models.")
    (license license:gpl2+)))

(define-public r-dlmtree
  (package
    (name "r-dlmtree")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dlmtree" version))
       (sha256
        (base32 "01nzhi1ysbvfl8f3asba9l2n72aidk632njv5m50k9xjfcjhayqb"))))
    (properties `((upstream-name . "dlmtree")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-shinythemes
                             r-shiny
                             r-rcppeigen
                             r-rcpparmadillo
                             r-rcpp
                             r-mgcv
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list gfortran))
    (home-page "https://github.com/danielmork/dlmtree")
    (synopsis "Bayesian Treed Distributed Lag Models")
    (description
     "Estimation of distributed lag models (DLMs) based on a Bayesian additive
regression trees framework.  Includes several extensions of DLMs: treed DLMs and
distributed lag mixture models (Mork and Wilson, 2023) <doi:10.1111/biom.13568>;
treed distributed lag nonlinear models (Mork and Wilson, 2022)
<doi:10.1093/biostatistics/kxaa051>; heterogeneous DLMs (Mork, et.  al., 2024)
<doi:10.1080/01621459.2023.2258595>; monotone DLMs (Mork and Wilson, 2024)
<doi:10.1214/23-BA1412>.  The package also includes visualization tools and a
shiny interface to help interpret results.")
    (license license:gpl3+)))

(define-public r-dlmtool
  (package
    (name "r-dlmtool")
    (version "6.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DLMtool" version))
       (sha256
        (base32 "1lhskk4022vzvmwki08jkwpz3scirbdr0imkpzb9dqfhvmsdyafx"))))
    (properties `((upstream-name . "DLMtool")))
    (build-system r-build-system)
    (propagated-inputs (list r-tmb
                             r-rcppeigen
                             r-rcpp
                             r-msetool
                             r-ggplot2
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=DLMtool")
    (synopsis "Data-Limited Methods Toolkit")
    (description
     "This package provides a collection of data-limited management procedures that
can be evaluated with management strategy evaluation with the MSEtool package,
or applied to fishery data to provide management recommendations.")
    (license license:gpl3)))

(define-public r-dll
  (package
    (name "r-dll")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DLL" version))
       (sha256
        (base32 "00xj6r1i4qhv0lq9ky88pw26nkc3ywhl23j9rsh2z5jn4dqpwpcg"))))
    (properties `((upstream-name . "DLL")))
    (build-system r-build-system)
    (propagated-inputs (list r-sam r-mass r-locpol r-glmnet))
    (home-page "https://github.com/zijguo/HighDim-Additive-Inference")
    (synopsis "Decorrelated Local Linear Estimator")
    (description
     "Implementation of the Decorrelated Local Linear estimator proposed in
<arxiv:1907.12732>.  It constructs the confidence interval for the derivative of
the function of interest under the high-dimensional sparse additive model.")
    (license license:gpl3)))

(define-public r-dlim
  (package
    (name "r-dlim")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dlim" version))
       (sha256
        (base32 "12sa1bpslans836v9fvma2wj8qspnc521saaw02q9iygkh7kf1sy"))))
    (properties `((upstream-name . "dlim")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis
                             r-tsmodel
                             r-rlang
                             r-reshape2
                             r-mgcv
                             r-ggplot2
                             r-dlnm))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dlim")
    (synopsis "Distributed Lag Interaction Model")
    (description
     "Collection of functions for fitting and interpreting distributed lag interaction
models (DLIM).  A DLIM regresses a scalar outcome on repeated measures of
exposure and allows for modification by a continuous variable.  Includes a
dlim() function for fitting, predict() function for inference, and plotting
functions for visualization.  Details on methodology are described in Demateis
et al. (2024) <doi:10.1002/env.2843>.")
    (license license:gpl3)))

(define-public r-dlib
  (package
    (name "r-dlib")
    (version "1.0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dlib" version))
       (sha256
        (base32 "1rchl4f3zj0azz8d4n139daba2gz6vnm60jq45vgc9gphk2mrnnb"))))
    (properties `((upstream-name . "dlib")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://cran.r-project.org/package=dlib")
    (synopsis "Allow Access to the 'Dlib' C++ Library")
    (description
     "Interface for Rcpp users to dlib <http://dlib.net> which is a C++ toolkit
containing machine learning algorithms and computer vision tools.  It is used in
a wide range of domains including robotics, embedded devices, mobile phones, and
large high performance computing environments.  This package allows R users to
use dlib through Rcpp'.")
    (license (license:fsdg-compatible "BSL-1.0"))))

(define-public r-dlegfm
  (package
    (name "r-dlegfm")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DLEGFM" version))
       (sha256
        (base32 "1k7dpr9kq3rmvh6dvvgldmx4ar3vcs1l1gsj7piqqb811d90mh47"))))
    (properties `((upstream-name . "DLEGFM")))
    (build-system r-build-system)
    (propagated-inputs (list r-elasticnet))
    (home-page "https://cran.r-project.org/package=DLEGFM")
    (synopsis "Distributed Loading Estimation for General Factor Model")
    (description
     "The load estimation method is based on a general factor model to solve the
estimates of load and specific variance.  The philosophy of the package is
described in Guangbao Guo. (2022). <doi:10.1007/s00180-022-01270-z>.")
    (license license:expat)))

(define-public r-dlbayes
  (package
    (name "r-dlbayes")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dlbayes" version))
       (sha256
        (base32 "058kkh67npai2ffrjdpjn4pzj8f233znl16nj6yx8wz8lkb17cb0"))))
    (properties `((upstream-name . "dlbayes")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-laplacesdemon r-glmnet r-gigrvg r-expm))
    (home-page "https://cran.r-project.org/package=dlbayes")
    (synopsis
     "Use Dirichlet Laplace Prior to Solve Linear Regression Problem and Do Variable Selection")
    (description
     "The Dirichlet Laplace shrinkage prior in Bayesian linear regression and variable
selection, featuring: utility functions in implementing Dirichlet-Laplace priors
such as visualization; scalability in Bayesian linear regression; penalized
credible regions for variable selection.")
    (license license:expat)))

(define-public r-dlasso
  (package
    (name "r-dlasso")
    (version "2.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DLASSO" version))
       (sha256
        (base32 "0xdygf6h89d9z4kqb46iqfxgdzq9dmkrxf9ypw78l4d8n9xx2gaa"))))
    (properties `((upstream-name . "DLASSO")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "http://hamedhaseli.webs.com")
    (synopsis
     "Implementation of Adaptive or Non-Adaptive Differentiable Lasso and SCAD Penalties in Linear Models")
    (description
     "An implementation of the differentiable lasso (dlasso) and SCAD (@code{dSCAD})
using iterative ridge algorithm.  This package allows selecting the tuning
parameter by AIC, BIC, GIC and GIC.")
    (license license:gpl2+)))

(define-public r-dlagm
  (package
    (name "r-dlagm")
    (version "1.1.13")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dLagM" version))
       (sha256
        (base32 "0wn09qdmnahn0imi17yq4flcnr69cms832si1z03l9xwcjkfjxfm"))))
    (properties `((upstream-name . "dLagM")))
    (build-system r-build-system)
    (propagated-inputs (list r-wavethresh
                             r-strucchange
                             r-sandwich
                             r-roll
                             r-plyr
                             r-nardl
                             r-mass
                             r-lmtest
                             r-formula-tools
                             r-dynlm
                             r-aer))
    (home-page "https://cran.r-project.org/package=dLagM")
    (synopsis "Time Series Regression Models with Distributed Lag Models")
    (description
     "This package provides time series regression models with one predictor using
finite distributed lag models, polynomial (Almon) distributed lag models,
geometric distributed lag models with Koyck transformation, and autoregressive
distributed lag models.  It also consists of functions for computation of h-step
ahead forecasts from these models.  See Demirhan
(2020)(<doi:10.1371/journal.pone.0228812>) and Baltagi
(2011)(<doi:10.1007/978-3-642-20059-5>) for more information.")
    (license license:gpl3)))

(define-public r-dkanr
  (package
    (name "r-dkanr")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dkanr" version))
       (sha256
        (base32 "1zic7qhwq3s9w70zi1f6qyf7pzm69k5a1p5fd4n3z4nbga54njxd"))))
    (properties `((upstream-name . "dkanr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-purrr
                             r-jsonlite
                             r-httr
                             r-dplyr
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dkanr")
    (synopsis "Client for the 'DKAN' API")
    (description
     "This package provides functions to facilitate access to the DKAN API
(<https://dkan.readthedocs.io/en/latest/apis/index.html>), including the DKAN
REST API (metadata), and the DKAN datastore API (data).  Includes functions to
list, create, retrieve, update, and delete datasets and resources nodes.  It
also includes functions to search and retrieve data from the DKAN datastore.")
    (license license:expat)))

(define-public r-djl
  (package
    (name "r-djl")
    (version "3.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DJL" version))
       (sha256
        (base32 "0q82b35ln0ligxgnk726bn5cynh6sd529hk6v3prrzbvdnsrqxcg"))))
    (properties `((upstream-name . "DJL")))
    (build-system r-build-system)
    (propagated-inputs (list r-lpsolveapi r-car))
    (home-page "https://cran.r-project.org/package=DJL")
    (synopsis "Distance Measure Based Judgment and Learning")
    (description
     "This package implements various decision support tools related to the
Econometrics & Technometrics.  Subroutines include correlation reliability test,
Mahalanobis distance measure for outlier detection, combinatorial search (all
possible subset regression), non-parametric efficiency analysis measures: DDF
(directional distance function), DEA (data envelopment analysis), HDF
(hyperbolic distance function), SBM (slack-based measure), and SF (shortage
function), benchmarking, Malmquist productivity analysis, risk analysis,
technology adoption model, new product target setting, network DEA, dynamic DEA,
intertemporal budgeting, etc.")
    (license license:gpl2)))

(define-public r-dizutils
  (package
    (name "r-dizutils")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIZutils" version))
       (sha256
        (base32 "1kra2b1qbbs6yf5aqlianszqbybni4iqzks0gxg5hdmdzphzb0hb"))))
    (properties `((upstream-name . "DIZutils")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-rpostgres
                             r-rjsonio
                             r-rjdbc
                             r-psych
                             r-hmisc
                             r-diztools
                             r-dbi
                             r-data-table))
    (home-page "https://github.com/miracum/misc-dizutils")
    (synopsis "Utilities for 'DIZ' R Package Development")
    (description
     "Utility functions used for the R package development infrastructure inside the
data integration centers ('DIZ') to standardize and facilitate repetitive tasks
such as setting up a database connection or issuing notification messages and to
avoid redundancy.")
    (license license:gpl3)))

(define-public r-diztools
  (package
    (name "r-diztools")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIZtools" version))
       (sha256
        (base32 "0i42k7h82x9g0mha8ppk17h3srgfjgwb9ysnib80pkjnp59kmpa5"))))
    (properties `((upstream-name . "DIZtools")))
    (build-system r-build-system)
    (propagated-inputs (list r-r-utils
                             r-parsedate
                             r-magrittr
                             r-logger
                             r-data-table
                             r-config
                             r-clear))
    (home-page "https://github.com/miracum/misc-diztools")
    (synopsis "Lightweight Utilities for 'DIZ' R Package Development")
    (description
     "Lightweight utility functions used for the R package development infrastructure
inside the data integration centers ('DIZ') to standardize and facilitate
repetitive tasks such as setting up a database connection or issuing
notification messages and to avoid redundancy.")
    (license license:gpl3)))

(define-public r-diyar
  (package
    (name "r-diyar")
    (version "0.5.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diyar" version))
       (sha256
        (base32 "0md7hrjcla4z3ck9kb387x4cmf8ca7sm9qw4a9mby9xj6abkd8id"))))
    (properties `((upstream-name . "diyar")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://olisansonwu.github.io/diyar/index.html")
    (synopsis "Record Linkage and Epidemiological Case Definitions in 'R'")
    (description
     "An R package for iterative and batched record linkage, and applying
epidemiological case definitions.  diyar can be used for deterministic and
probabilistic record linkage, or multistage record linkage combining both
approaches.  It features the implementation of nested match criteria, and
mechanisms to address missing data and conflicting matches during stepwise
record linkage.  Case definitions are implemented by assigning records to groups
based on match criteria such as person or place, and overlapping time or
duration of events e.g. sample collection dates or periods of hospital stays.
Matching records are assigned a unique group ID. Index and duplicate records are
removed or further analyses as required.")
    (license license:gpl3)))

(define-public r-dixon
  (package
    (name "r-dixon")
    (version "0.0-9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dixon" version))
       (sha256
        (base32 "1lgmhg3d0f59x5mfa6j9cs009yqxyzfzv7jfz5d93jrbs0p7glnk"))))
    (properties `((upstream-name . "dixon")))
    (build-system r-build-system)
    (propagated-inputs (list r-splancs r-spatstat-geom r-spatstat))
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=dixon")
    (synopsis "Nearest Neighbour Contingency Table Analysis")
    (description
     "Function to test spatial segregation and association based in contingency table
analysis of nearest neighbour counts following Dixon (2002)
<doi:10.1080/11956860.2002.11682700>.  Some Fortran code has been included to
the original dixon2002() function of the ecespa package to improve speed.")
    (license license:gpl2+)))

(define-public r-divvy
  (package
    (name "r-divvy")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "divvy" version))
       (sha256
        (base32 "03s76pkywxcx6kkdq7dpa0l2rvhwibzp48sb9mqbbhf713a621pi"))))
    (properties `((upstream-name . "divvy")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-units
                             r-terra
                             r-sf
                             r-rdpack
                             r-inext))
    (native-inputs (list r-knitr))
    (home-page "https://gawainantell.github.io/divvy/")
    (synopsis "Spatial Subsampling of Biodiversity Occurrence Data")
    (description
     "Divide taxonomic occurrence data into geographic regions of fair comparison,
with three customisable methods to standardise area and extent.  Calculate
common biodiversity and range-size metrics on subsampled data.  Background
theory and practical considerations for the methods are described in Antell and
others (2023) <doi:10.31223/X5997Z>.")
    (license license:gpl3+)))

(define-public r-divseg
  (package
    (name "r-divseg")
    (version "0.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "divseg" version))
       (sha256
        (base32 "0fbh5qpjszpmkrvb2p7f9rbbc4zj1dchhwk28zclnbxazlg116fs"))))
    (properties `((upstream-name . "divseg")))
    (build-system r-build-system)
    (propagated-inputs (list r-units
                             r-tidyselect
                             r-tibble
                             r-sf
                             r-rlang
                             r-magrittr
                             r-dplyr))
    (home-page "https://github.com/christopherkenny/divseg/")
    (synopsis "Calculate Diversity and Segregation Indices")
    (description
     "This package implements common measures of diversity and spatial segregation.
This package has tools to compute the majority of measures are reviewed in
Massey and Denton (1988) <doi:10.2307/2579183>.  Multiple common measures of
within-geography diversity are implemented as well.  All functions operate on
data frames with a tidyselect based workflow.")
    (license license:expat)))

(define-public r-divraster
  (package
    (name "r-divraster")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "divraster" version))
       (sha256
        (base32 "0w603c5czvzqj0ydbmmxy9xn8p0r25c6i5m90219p6jv4nb1afrz"))))
    (properties `((upstream-name . "divraster")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra r-sesraster r-bat))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/flaviomoc/divraster")
    (synopsis "Diversity Metrics Calculations for Rasterized Data")
    (description
     "Alpha and beta diversity for taxonomic (TD), functional (FD), and phylogenetic
(PD) dimensions based on rasters.  Spatial and temporal beta diversity can be
partitioned into replacement and richness difference components.  It also
calculates standardized effect size for FD and PD alpha diversity and the
average individual traits across multilayer rasters.  The layers of the raster
represent species, while the cells represent communities.  Methods details can
be found at Cardoso et al.  2022 <https://CRAN.R-project.org/package=BAT> and
Heming et al.  2023 <https://CRAN.R-project.org/package=SESraster>.")
    (license license:gpl3+)))

(define-public r-divo
  (package
    (name "r-divo")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "divo" version))
       (sha256
        (base32 "06c4kjl6llvvdr2gk480jcmj2abmqwph7x4vk5nflxm7piimvg7v"))))
    (properties `((upstream-name . "divo")))
    (build-system r-build-system)
    (propagated-inputs (list r-cluster))
    (home-page "https://cran.r-project.org/package=divo")
    (synopsis
     "Tools for Analysis of Diversity and Similarity in Biological Systems")
    (description
     "This package provides a set of tools for empirical analysis of diversity (a
number and frequency of different types in population) and similarity (a number
and frequency of shared types in two populations) in biological or ecological
systems.")
    (license license:gpl3+)))

(define-public r-divest
  (package
    (name "r-divest")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "divest" version))
       (sha256
        (base32 "15d1bfdmav5hdvl1x0vfp6k0ab0apw8kqb3xc05ng9ys0557xz1z"))))
    (properties `((upstream-name . "divest")))
    (build-system r-build-system)
    (propagated-inputs (list r-rnifti r-rcpp))
    (native-inputs (list pkg-config))
    (home-page "https://github.com/jonclayden/divest")
    (synopsis "Get Images Out of DICOM Format Quickly")
    (description
     "This package provides tools to sort DICOM-format medical image files, and
convert them to N@code{IfTI-1} format.")
    (license (license:fsdg-compatible "BSD_3_clause + file LICENCE"))))

(define-public r-diversityforest
  (package
    (name "r-diversityforest")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diversityForest" version))
       (sha256
        (base32 "0p4kk896y6cidy9nh8blvg9ghcy21dhjnw9hcpg90bq4j8s82gms"))))
    (properties `((upstream-name . "diversityForest")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-sgeostat
                             r-scales
                             r-rms
                             r-rlang
                             r-rcppeigen
                             r-rcpp
                             r-rcolorbrewer
                             r-patchwork
                             r-nnet
                             r-matrix
                             r-mapgam
                             r-ggpubr
                             r-ggplot2
                             r-gam))
    (home-page "https://cran.r-project.org/package=diversityForest")
    (synopsis
     "Innovative Complex Split Procedures in Random Forests Through Candidate Split Sampling")
    (description
     "Implementations of three diversity forest (DF) (Hornung, 2022,
<doi:10.1007/s42979-021-00920-1>) variants.  The DF algorithm is a split-finding
approach that allows complex split procedures to be realized in random forest
variants.  The three DF variants implemented are: 1.  interaction forests (IFs)
(Hornung & Boulesteix, 2022, <doi:10.1016/j.csda.2022.107460>): Model
quantitative and qualitative interaction effects using bivariable splitting.
Come with the Effect Importance Measure (EIM), which can be used to identify
variable pairs that have well-interpretable quantitative and qualitative
interaction effects with high predictive relevance.  2.  multi forests
(@code{MuFs}) (Hornung & Hapfelmeier, 2024,
<doi:10.48550/@code{arXiv.2409.08925>}): Model multi-class outcomes using
multi-way and binary splitting.  Come with two variable importance measures
(VIMs): The multi-class VIM measures the degree to which the variables are
specifically associated with one or more outcome classes, and the discriminatory
VIM, similar to conventional VIMs, measures the overall influence strength of
the variables.  3.  the basic form of diversity forests that uses conventional
univariable, binary splitting (Hornung, 2022).  Except for multi forests, which
are tailored for multi-class outcomes, all included diversity forest variants
support categorical, metric, and survival outcomes.  The package also includes
plotting functions that make it possible to learn about the forms of the effects
identified using IFs and @code{MuFs}.  This is a fork of the R package ranger
(main author: Marvin N. Wright), which implements random forests using an
efficient C++ implementation.")
    (license license:gpl3)))

(define-public r-diversificationr
  (package
    (name "r-diversificationr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiversificationR" version))
       (sha256
        (base32 "1gybzpv5bl17lp1nxhqzsvj585j3lylfd388vp401lmri3k8r4cs"))))
    (properties `((upstream-name . "DiversificationR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DiversificationR")
    (synopsis "Econometric Tools to Measure Portfolio Diversification")
    (description
     "Diversification is one of the most important concepts in portfolio management.
This framework offers scholars, practitioners and policymakers a useful toolbox
to measure diversification.  Specifically, this framework provides recent
diversification measures from the recent literature.  These diversification
measures are based on the works of Rudin and Morgan (2006)
<doi:10.3905/jpm.2006.611807>, Choueifaty and Coignard (2008)
<doi:10.3905/JPM.2008.35.1.40>, Vermorken et al. (2012)
<doi:10.3905/jpm.2012.39.1.067>, Flores et al. (2017)
<doi:10.3905/jpm.2017.43.4.112>, Calvet et al. (2007) <doi:10.1086/524204>, and
Candelon, Fuerst and Hasse (2020).")
    (license license:gpl3)))

(define-public r-diverse
  (package
    (name "r-diverse")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diverse" version))
       (sha256
        (base32 "10kmx3qv58xhqs1icsxqq0y0cm8y2hx9ysb65brd3hhg33alzvk3"))))
    (properties `((upstream-name . "diverse")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2 r-proxy r-foreign))
    (home-page "https://github.com/mguevara/diverse")
    (synopsis "Diversity Measures for Complex Systems")
    (description
     "Computes the most common diversity measures used in social and other sciences,
and includes new measures from interdisciplinary research.")
    (license license:cc-by-sa4.0)))

(define-public r-diverge
  (package
    (name "r-diverge")
    (version "2.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diverge" version))
       (sha256
        (base32 "0rgmzcy2kk1bc6v27qcj4ckyvidzvldqx3cz1prccq5bhw2m8cdz"))))
    (properties `((upstream-name . "diverge")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncnorm))
    (home-page "https://cran.r-project.org/package=diverge")
    (synopsis
     "Evolutionary Trait Divergence Between Sister Species and Other Paired Lineages")
    (description
     "Compares the fit of alternative models of continuous trait differentiation
between sister species and other paired lineages.  Differences in trait means
between two lineages arise as they diverge from a common ancestor, and
alternative processes of evolutionary divergence are expected to leave unique
signatures in the distribution of trait differentiation in datasets comprised of
many lineage pairs.  Models include approximations of divergent selection,
drift, and stabilizing selection.  A variety of model extensions facilitate the
testing of process-to-pattern hypotheses.  Users supply trait data and
divergence times for each lineage pair.  The fit of alternative models is
compared in a likelihood framework.")
    (license license:gpl2+)))

(define-public r-diver
  (package
    (name "r-diver")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diveR" version))
       (sha256
        (base32 "0n0ldc3k0ryr20794kvqxpnk8m3qc13lkl6rxw043pkwbjqj7291"))))
    (properties `((upstream-name . "diveR")))
    (build-system r-build-system)
    (propagated-inputs (list r-zenplots
                             r-rstudioapi
                             r-loon-tourr
                             r-loon-shiny
                             r-loon-ggplot
                             r-loon-data
                             r-loon
                             r-ggmulti
                             r-crayon
                             r-cli))
    (home-page "https://github.com/great-northern-diver/diver/")
    (synopsis "Easily Install and Load Interactive Data Visualization Tools")
    (description
     "This package provides a suite of loon related packages providing data analytic
tools for Direct Interactive Visual Exploration in R ('@code{diveR}').  These
tools work with and complement those of the tidyverse suite, extending the
grammar of ggplot2 to become a grammar of interactive graphics.  The suite
provides many visual tools designed for moderately (100s of variables) high
dimensional data analysis, through zenplots and novel tools in loon', and
extends the ggplot2 grammar to provide parallel coordinates, Andrews plots, and
arbitrary glyphs through ggmulti'.  The @code{diveR} package gathers together
and installs all these related packages in a single step.")
    (license license:gpl2)))

(define-public r-divemove
  (package
    (name "r-divemove")
    (version "1.6.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diveMove" version))
       (sha256
        (base32 "18g335912rx49vwdjw577v0jxc25y204whzb48cpg51ihrc91ngf"))))
    (properties `((upstream-name . "diveMove")))
    (build-system r-build-system)
    (propagated-inputs (list r-unireg r-quantreg r-plotly r-kernsmooth
                             r-geosphere))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/spluque/diveMove")
    (synopsis "Dive Analysis and Calibration")
    (description
     "Utilities to represent, visualize, filter, analyse, and summarize time-depth
recorder (TDR) data.  Miscellaneous functions for handling location data are
also provided.")
    (license license:gpl3)))

(define-public r-dive
  (package
    (name "r-dive")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DivE" version))
       (sha256
        (base32 "1nab00wkq2986sxi8z5hmhadxyzhy181akhzj8vc6bfznrcrnbig"))))
    (properties `((upstream-name . "DivE")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp r-fme r-desolve))
    (home-page "https://cran.r-project.org/package=DivE")
    (synopsis "Diversity Estimator")
    (description
     "This package contains functions for the @code{DivE} estimator
<doi:10.1371/journal.pcbi.1003646>.  The @code{DivE} estimator is a heuristic
approach to estimate the number of classes or the number of species (species
richness) in a population.")
    (license license:gpl2+)))

(define-public r-divdyn
  (package
    (name "r-divdyn")
    (version "0.8.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "divDyn" version))
       (sha256
        (base32 "1rqk7ih0j6d3ykx7d0r0c33bcbksw4paman5f92ragw2a96d04cf"))))
    (properties `((upstream-name . "divDyn")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=divDyn")
    (synopsis "Diversity Dynamics using Fossil Sampling Data")
    (description
     "This package provides functions to describe sampling and diversity dynamics of
fossil occurrence datasets (e.g. from the Paleobiology Database).  The package
includes methods to calculate range- and occurrence-based metrics of taxonomic
richness, extinction and origination rates, along with traditional sampling
measures.  A powerful subsampling tool is also included that implements
frequently used sampling standardization methods in a multiple bin-framework.
The plotting of time series and the occurrence data can be simplified by the
functions incorporated in the package, as well as other calculations, such as
environmental affinities and extinction selectivity testing.  Details can be
found in: Kocsis, A.T.; Reddin, C.J.; Alroy, J. and Kiessling, W. (2019)
<doi:10.1101/423780>.")
    (license (license:fsdg-compatible "CC BY 4.0"))))

(define-public r-div
  (package
    (name "r-div")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "div" version))
       (sha256
        (base32 "1k4c34wpwfj7yqnk1x9sjzn3dc2vdzhpy8g4c00aqs3nbgcknyn8"))))
    (properties `((upstream-name . "div")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyverse
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rpart
                             r-rlang
                             r-pryr
                             r-plotly
                             r-magrittr
                             r-kableextra
                             r-gridextra
                             r-ggplot2
                             r-dplyr))
    (home-page "http://www.de-brouwer.com/div/")
    (synopsis "Report on Diversity and Inclusion in a Corporate Setting")
    (description
     "Facilitate the analysis of teams in a corporate setting: assess the diversity
per grade and job, present the results, search for bias (in hiring and/or
promoting processes).  It also provides methods to simulate the effect of bias,
random team-data, etc.  White paper: Philippe J.S. De Brouwer (2021)
<http://www.de-brouwer.com/assets/div/div-white-paper.pdf>.  Book (chapter 36):
Philippe J.S. De Brouwer (2020, ISBN:978-1-119-63272-6) and Philippe J.S. De
Brouwer (2020) <doi:10.1002/9781119632757>.")
    (license license:agpl3+)))

(define-public r-dittoviz
  (package
    (name "r-dittoviz")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dittoViz" version))
       (sha256
        (base32 "1ma06cc4bdrmp9r7yxa3mrqzys5ap6i1sifsgsr31zjnl6yxfk0w"))))
    (properties `((upstream-name . "dittoViz")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggridges r-ggrepel r-ggplot2 r-cowplot))
    (home-page "https://github.com/dtm2451/dittoViz")
    (synopsis "User Friendly Data Visualization")
    (description
     "This package provides a comprehensive visualization toolkit built with coders of
all skill levels and color-vision impaired audiences in mind.  It allows
creation of finely-tuned, publication-quality figures from single function
calls.  Visualizations include scatter plots, compositional bar plots, violin,
box, and ridge plots, and more.  Customization ranges from size and title
adjustments to discrete-group circling and labeling, hidden data overlay upon
cursor hovering via ggplotly() conversion, and many more, all with simple,
discrete inputs.  Color blindness friendliness is powered by legend adjustments
(enlarged keys), and by allowing the use of shapes or letter-overlay in addition
to the carefully selected @code{dittoColors}().")
    (license (license:fsdg-compatible "MIT + file LICENCE"))))

(define-public r-dittodb
  (package
    (name "r-dittodb")
    (version "0.1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dittodb" version))
       (sha256
        (base32 "13w78vhl1skc9073k5aplxm21l0cny8aklp75qljhla5p6ggq02w"))))
    (properties `((upstream-name . "dittodb")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-lifecycle r-glue r-digest r-dbi))
    (native-inputs (list r-knitr))
    (home-page "https://dittodb.jonkeane.com/")
    (synopsis "Test Environment for Database Requests")
    (description
     "Testing and documenting code that communicates with remote databases can be
painful.  Although the interaction with R is usually relatively simple (e.g.
data(frames) passed to and from a database), because they rely on a separate
service and the data there, testing them can be difficult to set up,
unsustainable in a continuous integration environment, or impossible without
replicating an entire production cluster.  This package addresses that by
allowing you to make recordings from your database interactions and then play
them back while testing (or in other contexts) all without needing to spin up or
have access to the database your code would typically connect to.")
    (license license:asl2.0)))

(define-public r-disttools
  (package
    (name "r-disttools")
    (version "0.1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disttools" version))
       (sha256
        (base32 "1jm3nqyywdzpbfvk2mffmhp75al1hcvd5l4r21fbd3iz2anll0ma"))))
    (properties `((upstream-name . "disttools")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=disttools")
    (synopsis "Distance Object Manipulation Tools")
    (description
     "This package provides convenient methods for accessing the data in dist objects
with minimal memory and computational overhead.  disttools can be used to
extract the distance between any pair or combination of points encoded by a dist
object using only the indices of those points.  This is an improvement over
existing functionality, which requires either coercing a dist object into a
matrix or calculating the one dimensional index corresponding to a pair of
observations.  Coercion to a matrix is undesirable because doing so doubles the
amount of memory required for storage.  In contrast, there is no inherent
downside to the latter solution.  However, in part due to several edge cases,
correctly and efficiently implementing such a solution can be challenging.
disttools abstracts away these challenges and provides a simple interface to
access the data in a dist object using the latter approach.")
    (license license:expat)))

(define-public r-disttails
  (package
    (name "r-disttails")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distTails" version))
       (sha256
        (base32 "10p7rfqfkhcwq10lhz3cq9i4k1jdccks4y3791lajljsxz5jrca4"))))
    (properties `((upstream-name . "distTails")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-gsl r-ercv))
    (home-page "https://github.com/SergiVilardell/distTails")
    (synopsis "Collection of Full Defined Distribution Tails")
    (description
     "This package provides a full definition for Weibull tails and Full-Tails Gamma
and tools for fitting these distributions to empirical tails.  This package
build upon the paper by del Castillo, Joan & Daoudi, Jalila & Serra, Isabel.
(2012) <doi:10.1017/asb.2017.9>.")
    (license license:gpl3)))

(define-public r-distrtest
  (package
    (name "r-distrtest")
    (version "2.8.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distrTEst" version))
       (sha256
        (base32 "1fj0llq75hxy15wg1q4z10jmdxak2jcip62nl73fs25k1v9hr416"))))
    (properties `((upstream-name . "distrTEst")))
    (build-system r-build-system)
    (propagated-inputs (list r-startupmsg r-setrng r-distrsim))
    (home-page "http://distr.r-forge.r-project.org/")
    (synopsis "Estimation and Testing Classes Based on Package 'distr'")
    (description
     "Evaluation (S4-)classes based on package distr for evaluating procedures
(estimators/tests) at data/simulation in a unified way.")
    (license license:lgpl3)))

(define-public r-distrteach
  (package
    (name "r-distrteach")
    (version "2.9.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distrTeach" version))
       (sha256
        (base32 "0xfnq012hr1ngw6c5zdl8459qf908h6dpgdk6csnbpm9a706xypq"))))
    (properties `((upstream-name . "distrTeach")))
    (build-system r-build-system)
    (propagated-inputs (list r-startupmsg r-distrex r-distr))
    (home-page "http://distr.r-forge.r-project.org/")
    (synopsis
     "Extensions of Package 'distr' for Teaching Stochastics/Statistics in Secondary School")
    (description
     "This package provides flexible examples of LLN and CLT for teaching purposes in
secondary school.")
    (license license:lgpl3)))

(define-public r-distrsim
  (package
    (name "r-distrsim")
    (version "2.8.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distrSim" version))
       (sha256
        (base32 "0b2cyfz1ghbkz7ps4lzwkkfakxq9wc1yd53zh8pzd1r8zjkb9c7y"))))
    (properties `((upstream-name . "distrSim")))
    (build-system r-build-system)
    (propagated-inputs (list r-startupmsg r-setrng r-distr))
    (home-page "http://distr.r-forge.r-project.org/")
    (synopsis "Simulation Classes Based on Package 'distr'")
    (description
     "S4-classes for setting up a coherent framework for simulation within the distr
family of packages.")
    (license license:lgpl3)))

(define-public r-distrrmetrics
  (package
    (name "r-distrrmetrics")
    (version "2.8.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distrRmetrics" version))
       (sha256
        (base32 "12zrgaqs3cb7zpr3zjlm9s9x2d7qqhgcy9yaf9zgjbq5rnffrrx7"))))
    (properties `((upstream-name . "distrRmetrics")))
    (build-system r-build-system)
    (propagated-inputs (list r-startupmsg r-fgarch r-fbasics r-distr))
    (home-page "http://distr.r-forge.r-project.org/")
    (synopsis "Distribution Classes for Distributions from Rmetrics")
    (description
     "S4-distribution classes based on package distr for distributions from packages
@code{fBasics} and @code{fGarch}'.")
    (license license:lgpl3)))

(define-public r-distrr
  (package
    (name "r-distrr")
    (version "0.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distrr" version))
       (sha256
        (base32 "04lhrc92y6dqnfpqlmynjvn2dndzkknnvwsr5pf73dfpgv7n3s1f"))))
    (properties `((upstream-name . "distrr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-rlang r-magrittr r-dplyr))
    (home-page "https://gibonet.github.io/distrr")
    (synopsis "Estimate and Manage Empirical Distributions")
    (description
     "This package provides tools to estimate and manage empirical distributions,
which should work with survey data.  One of the main features is the possibility
to create data cubes of estimated statistics, that include all the combinations
of the variables of interest (see for example functions dcc5() and dcc6()).")
    (license license:gpl2)))

(define-public r-distrom
  (package
    (name "r-distrom")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distrom" version))
       (sha256
        (base32 "1j8k8cgh5r8av8jf8miq858j66hmkkcdjqhia77iivx97fg9pcjk"))))
    (properties `((upstream-name . "distrom")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-gamlr))
    (home-page "https://github.com/TaddyLab/distrom")
    (synopsis "Distributed Multinomial Regression")
    (description
     "Fast distributed/parallel estimation for multinomial logistic regression via
Poisson factorization and the gamlr package.  For details see: Taddy (2015,
@code{AoAS}), Distributed Multinomial Regression, <@code{arXiv:1311.6139>}.")
    (license license:gpl3)))

(define-public r-distro
  (package
    (name "r-distro")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distro" version))
       (sha256
        (base32 "03b8mkjhxxh93675mmj443a83mgfwhkdar7dfbf3agf6aqnadn2g"))))
    (properties `((upstream-name . "distro")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=distro")
    (synopsis "Linux Distribution Properties")
    (description
     "In order to provide unified access to Linux distribution details in R, this
package wraps the various files and commands that may exist on a system.  It is
similar in spirit to the lsb_release command and the Python package of the same
name.")
    (license license:asl2.0)))

(define-public r-distrmod
  (package
    (name "r-distrmod")
    (version "2.9.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distrMod" version))
       (sha256
        (base32 "15wjizl3kbv39ri3bnikrdzf61vbvfgq9r1vln8663y0da0sv7d8"))))
    (properties `((upstream-name . "distrMod")))
    (build-system r-build-system)
    (propagated-inputs (list r-startupmsg
                             r-sfsmisc
                             r-randvar
                             r-mass
                             r-distrex
                             r-distr))
    (home-page "http://distr.r-forge.r-project.org/")
    (synopsis "Object Oriented Implementation of Probability Models")
    (description
     "This package implements S4 classes for probability models based on packages
distr and @code{distrEx}'.")
    (license license:lgpl3)))

(define-public r-distributiontest
  (package
    (name "r-distributiontest")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DistributionTest" version))
       (sha256
        (base32 "11xhr6yv42s1i4qqlb1pvzm8q2116v10gjlkhl0ml3id6lx27nmj"))))
    (properties `((upstream-name . "DistributionTest")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=DistributionTest")
    (synopsis "Powerful Goodness-of-Fit Tests Based on the Likelihood Ratio")
    (description
     "This package provides new types of omnibus tests which are generally much more
powerful than traditional tests (including the Kolmogorov-Smirnov, Cramer-von
Mises and Anderson-Darling tests),see Zhang (2002)
<doi:10.1111/1467-9868.00337>.")
    (license license:gpl3+)))

(define-public r-distributionsrd
  (package
    (name "r-distributionsrd")
    (version "0.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distributionsrd" version))
       (sha256
        (base32 "0ykzxcxh5l9l5z3546iqlllryw2xyixz1hiynx19k8bsn8k7dxyp"))))
    (properties `((upstream-name . "distributionsrd")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-modeltools r-flexmix))
    (home-page "https://cran.r-project.org/package=distributionsrd")
    (synopsis "Distribution Fitting and Evaluation")
    (description
     "This package provides a library of density, distribution function, quantile
function, (bounded) raw moments and random generation for a collection of
distributions relevant for the firm size literature.  Additionally, the package
contains tools to fit these distributions using maximum likelihood and evaluate
these distributions based on (i) log-likelihood ratio and (ii) deviations
between the empirical and parametrically implied moments of the distributions.
We add flexibility by allowing the considered distributions to be combined into
piecewise composite or finite mixture distributions, as well as to be used when
truncated.  See Dewitte (2020) <https://hdl.handle.net/1854/LU-8644700> for a
description and application of methods available in this package.")
    (license license:gpl3)))

(define-public r-distributions3
  (package
    (name "r-distributions3")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distributions3" version))
       (sha256
        (base32 "0av16mpnr18ijj4g8fk85mdvvv7qxqj1i9cn1dm585qgg1q8hd0z"))))
    (properties `((upstream-name . "distributions3")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-glue r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/alexpghayes/distributions3")
    (synopsis "Probability Distributions as S3 Objects")
    (description
     "This package provides tools to create and manipulate probability distributions
using S3.  Generics pdf(), cdf(), quantile(), and random() provide replacements
for base R's d/p/q/r style functions.  Functions and arguments have been named
carefully to minimize confusion for students in intro stats courses.  The
documentation for each distribution contains detailed mathematical notes.")
    (license license:expat)))

(define-public r-distributionoptimization
  (package
    (name "r-distributionoptimization")
    (version "1.2.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DistributionOptimization" version))
       (sha256
        (base32 "0pp0f7c9szyx426bnnz4fz4vh5q73m8x896z6pqgx04b6v445361"))))
    (properties `((upstream-name . "DistributionOptimization")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma r-ggplot2 r-ga r-adaptgauss))
    (home-page "https://cran.r-project.org/package=DistributionOptimization")
    (synopsis "Distribution Optimization")
    (description
     "Fits Gaussian Mixtures by applying evolution.  As fitness function a mixture of
the chi square test for distributions and a novel measure for approximating the
common area under curves between multiple Gaussians is used.  The package
presents an alternative to the commonly used Likelihood Maximization as is used
in Expectation Maximization.  The algorithm and applications of this package are
published under: Lerch, F., Ultsch, A., Lotsch, J. (2020)
<doi:10.1038/s41598-020-57432-w>.  The evolution is based on the GA package:
Scrucca, L. (2013) <doi:10.18637/jss.v053.i04> while the Gaussian Mixture Logic
stems from @code{AdaptGauss}': Ultsch, A, et al. (2015)
<doi:10.3390/ijms161025897>.")
    (license license:expat)))

(define-public r-distributacalcul
  (package
    (name "r-distributacalcul")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Distributacalcul" version))
       (sha256
        (base32 "072km5alfd9ba2p4qvrysdfrqbm8dksjwn3hkcidh6sg5m0g7aiw"))))
    (properties `((upstream-name . "Distributacalcul")))
    (build-system r-build-system)
    (propagated-inputs (list r-statmod r-rlang r-dplyr))
    (home-page "https://alec42.github.io/Distributacalcul_Package/")
    (synopsis "Probability Distribution Functions")
    (description
     "Calculates expected values, variance, different moments (kth moment, truncated
mean), stop-loss, mean excess loss, Value-at-Risk (@code{VaR}) and Tail
Value-at-Risk (T@code{VaR}) as well as some density and cumulative (survival)
functions of continuous, discrete and compound distributions.  This package also
includes a visual Shiny component to enable students to visualize distributions
and understand the impact of their parameters.  This package is intended to
expand the stats package so as to enable students to develop an intuition for
probability.")
    (license license:expat)))

(define-public r-distrib
  (package
    (name "r-distrib")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DISTRIB" version))
       (sha256
        (base32 "0whwmmdx2k2vrjjkz4ww9v7z9ad3835819pby91119lyic27w727"))))
    (properties `((upstream-name . "DISTRIB")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DISTRIB")
    (synopsis
     "Four Essential Functions for Statistical Distributions Analysis: A New Functional Approach")
    (description
     "This package provides a different way for calculating pdf/pmf, cdf, quantile and
random data such that the user is able to consider the name of related
distribution as an argument and so easily can changed by a changing argument by
user.  It must be mentioned that the core and computation base of package
DISTRIB is package stats'.  Although similar functions are introduced previously
in package stats', but the package DISTRIB has some special applications in some
special computational programs.")
    (license license:lgpl3+)))

(define-public r-distrex
  (package
    (name "r-distrex")
    (version "2.9.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distrEx" version))
       (sha256
        (base32 "1zxw0ml9rs771n3zsxhv03hdyn1jb46zfrihy4ykdsnbbn8pj8g0"))))
    (properties `((upstream-name . "distrEx")))
    (build-system r-build-system)
    (propagated-inputs (list r-startupmsg r-distr))
    (home-page "http://distr.r-forge.r-project.org/")
    (synopsis "Extensions of Package 'distr'")
    (description
     "Extends package distr by functionals, distances, and conditional distributions.")
    (license license:lgpl3)))

(define-public r-distrellipse
  (package
    (name "r-distrellipse")
    (version "2.8.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distrEllipse" version))
       (sha256
        (base32 "08gq3yq71kjh0bm2xj2r1r90xkk3pppwc24laqsvgnd467a2mf7y"))))
    (properties `((upstream-name . "distrEllipse")))
    (build-system r-build-system)
    (propagated-inputs (list r-startupmsg
                             r-setrng
                             r-mvtnorm
                             r-distrsim
                             r-distrex
                             r-distr))
    (home-page "http://distr.r-forge.r-project.org/")
    (synopsis "S4 Classes for Elliptically Contoured Distributions")
    (description
     "Distribution (S4-)classes for elliptically contoured distributions (based on
package distr').")
    (license license:lgpl3)))

(define-public r-distreg-vis
  (package
    (name "r-distreg-vis")
    (version "1.7.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distreg.vis" version))
       (sha256
        (base32 "1phl1nj1l69l6aj9hsv0yqllvhh6msv2ss9la8zikl3m2s0f6ymw"))))
    (properties `((upstream-name . "distreg.vis")))
    (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-rhandsontable
                             r-magrittr
                             r-ggplot2
                             r-gamlss-dist
                             r-gamlss
                             r-formatr
                             r-betareg
                             r-bamlss))
    (native-inputs (list esbuild))
    (home-page "https://github.com/Stan125/distreg.vis")
    (synopsis
     "Framework for the Visualization of Distributional Regression Models")
    (description
     "This package provides functions for visualizing distributional regression models
fitted using the gamlss', bamlss or betareg R package.  The core of the package
consists of a shiny application, where the model results can be interactively
explored and visualized.")
    (license license:gpl3)))

(define-public r-distrdoc
  (package
    (name "r-distrdoc")
    (version "2.8.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distrDoc" version))
       (sha256
        (base32 "0acbmh2lxf82527gm4i3vvh8gqfdnycsmdnf0s5pwz29zs6ql12z"))))
    (properties `((upstream-name . "distrDoc")))
    (build-system r-build-system)
    (propagated-inputs (list r-startupmsg
                             r-randvar
                             r-mass
                             r-distrtest
                             r-distrteach
                             r-distrsim
                             r-distrmod
                             r-distrex
                             r-distr))
    (native-inputs (list r-knitr))
    (home-page "http://distr.r-forge.r-project.org/")
    (synopsis "Documentation for 'distr' Family of R Packages")
    (description
     "This package provides documentation in form of a common vignette to packages
distr', @code{distrEx}', @code{distrMod}', @code{distrSim}', @code{distrTEst}',
@code{distrTeach}', and @code{distrEllipse}'.")
    (license license:lgpl3)))

(define-public r-distr
  (package
    (name "r-distr")
    (version "2.9.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distr" version))
       (sha256
        (base32 "1zmgmcw118cg7pbzn15kdl3n59hjyma4907yz4nbqpywp5kq07az"))))
    (properties `((upstream-name . "distr")))
    (build-system r-build-system)
    (propagated-inputs (list r-startupmsg r-sfsmisc r-mass))
    (native-inputs (list r-knitr))
    (home-page "http://distr.r-forge.r-project.org/")
    (synopsis "Object Oriented Implementation of Distributions")
    (description "S4-classes and methods for distributions.")
    (license license:lgpl3)))

(define-public r-distplotter
  (package
    (name "r-distplotter")
    (version "0.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DistPlotter" version))
       (sha256
        (base32 "0aws4qs6802y42m07ca9m4i0lza282g6kfzx64q652y52md862gk"))))
    (properties `((upstream-name . "DistPlotter")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-stringi
                             r-shinywidgets
                             r-shinyjs
                             r-shinybs
                             r-shinyalert
                             r-shiny
                             r-scales
                             r-rio
                             r-ggplot2
                             r-extradistr
                             r-dt
                             r-dplyr
                             r-colourpicker))
    (home-page "https://github.com/ccasement/DistPlotter")
    (synopsis
     "Graphical User Interface for Plotting Common Univariate Distributions")
    (description
     "Package including an interactive Shiny application for plotting common
univariate distributions.")
    (license license:expat)))

(define-public r-distory
  (package
    (name "r-distory")
    (version "1.4.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distory" version))
       (sha256
        (base32 "16il7ymwapjps1nscf7h22crzgxqs9alh84dhgrl07v83aq37ivb"))))
    (properties `((upstream-name . "distory")))
    (build-system r-build-system)
    (propagated-inputs (list r-ape))
    (home-page "https://cran.r-project.org/package=distory")
    (synopsis "Distance Between Phylogenetic Histories")
    (description
     "Geodesic distance between phylogenetic trees and associated functions.  The
theoretical background of distory is published in Billera et al. (2001)
\"Geometry of the space of phylogenetic trees.\" <doi:10.1006/aama.2001.0759>.")
    (license license:bsd-3)))

(define-public r-distops
  (package
    (name "r-distops")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distops" version))
       (sha256
        (base32 "02r6zf4jmk29879gvlxg7mh0lf9r8d340vb48md2swis25nidgx1"))))
    (properties `((upstream-name . "distops")))
    (build-system r-build-system)
    (propagated-inputs (list r-usethis
                             r-rcppparallel
                             r-rcpp
                             r-glue
                             r-fs
                             r-desc
                             r-cli))
    (home-page "https://github.com/lmjl-alea/distops")
    (synopsis "Usual Operations for Distance Matrices in R")
    (description
     "It provides the subset operator for dist objects and a function to compute
medoid(s) that are fully parallelized leveraging the @code{RcppParallel}
package.  It also provides functions for package developers to easily implement
their own parallelized dist() function using a custom C++'-based distance
function.")
    (license license:expat)))

(define-public r-disto
  (package
    (name "r-disto")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disto" version))
       (sha256
        (base32 "09pafy8y1ifgglqmal32dy34acx06ypsq2bgwsn6fjiqr9kw401j"))))
    (properties `((upstream-name . "disto")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-proxy
                             r-pbapply
                             r-ggplot2
                             r-fastmatch
                             r-fastcluster
                             r-factoextra
                             r-dplyr
                             r-broom
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/talegari/disto")
    (synopsis
     "Unified Interface to Distance, Dissimilarity, Similarity Matrices")
    (description
     "This package provides a high level API to interface over sources storing
distance, dissimilarity, similarity matrices with matrix style extraction,
replacement and other utilities.  Currently, in-memory dist object backend is
supported.")
    (license license:gpl3)))

(define-public r-distinctiveness
  (package
    (name "r-distinctiveness")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distinctiveness" version))
       (sha256
        (base32 "0ckwxj1xsyfrpbj87gw2b3x1qnzf7a7i31zmg5ccfhi4z7vx13mz"))))
    (properties `((upstream-name . "distinctiveness")))
    (build-system r-build-system)
    (propagated-inputs (list r-igraph))
    (home-page "https://github.com/iandreafc/distinctiveness-R")
    (synopsis "Distinctiveness Centrality")
    (description
     "Calculates Distinctiveness Centrality in social networks.  For formulas and
descriptions, see Fronzetti Colladon and Naldi (2020)
<doi:10.1371/journal.pone.0233276>.")
    (license license:expat)))

(define-public r-distillml
  (package
    (name "r-distillml")
    (version "0.1.0.13")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distillML" version))
       (sha256
        (base32 "05pk6g3bjaw0ghb673yxfvnijqkvjy4bfxk2vpiwccm7hjszl62s"))))
    (properties `((upstream-name . "distillML")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rforestry
                             r-r6
                             r-purrr
                             r-mltools
                             r-gridextra
                             r-glmnet
                             r-ggplot2
                             r-dplyr
                             r-data-table
                             r-checkmate))
    (home-page "https://github.com/forestry-labs/distillML")
    (synopsis
     "Model Distillation and Interpretability Methods for Machine Learning Models")
    (description
     "This package provides several methods for model distillation and
interpretability for general black box machine learning models and treatment
effect estimation methods.  For details on the algorithms implemented, see
<https://forestry-labs.github.io/@code{distillML/index.html>} Brian Cho, Theo F.
Saarinen, Jasjeet S. Sekhon, Simon Walter.")
    (license license:gpl3+)))

(define-public r-distill
  (package
    (name "r-distill")
    (version "1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distill" version))
       (sha256
        (base32 "15lx82dyxxlp2w6lnfs3kvd9pq6pjhjhpv0v1y218lg9y5k6h3s6"))))
    (properties `((upstream-name . "distill")))
    (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-yaml
                             r-xml2
                             r-xfun
                             r-whisker
                             r-stringr
                             r-rstudioapi
                             r-rprojroot
                             r-rmarkdown
                             r-png
                             r-openssl
                             r-mime
                             r-lubridate
                             r-knitr
                             r-jsonlite
                             r-htmltools
                             r-downlit
                             r-digest
                             r-bookdown
                             r-base64enc))
    (native-inputs (list esbuild))
    (home-page "https://github.com/rstudio/distill")
    (synopsis "'R Markdown' Format for Scientific and Technical Writing")
    (description
     "Scientific and technical article format for the web.  Distill articles feature
attractive, reader-friendly typography, flexible layout options for
visualizations, and full support for footnotes and citations.")
    (license license:asl2.0)))

(define-public r-distfromq
  (package
    (name "r-distfromq")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distfromq" version))
       (sha256
        (base32 "0wls5151kcih7rljbk0zrhz2lqx0npr4l6s61whh70w958h9jshg"))))
    (properties `((upstream-name . "distfromq")))
    (build-system r-build-system)
    (propagated-inputs (list r-zeallot r-purrr r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "http://reichlab.io/distfromq/")
    (synopsis "Reconstruct a Distribution from a Collection of Quantiles")
    (description
     "Given a set of predictive quantiles from a distribution, estimate the
distribution and create `d`, `p`, `q`, and `r` functions to evaluate its density
function, distribution function, and quantile function, and generate random
samples.  On the interior of the provided quantiles, an interpolation method
such as a monotonic cubic spline is used; the tails are approximated by a
location-scale family.")
    (license license:gpl3+)))

(define-public r-distfree-cr
  (package
    (name "r-distfree-cr")
    (version "1.5.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distfree.cr" version))
       (sha256
        (base32 "0h7cywxnasxmqnl9f2f9wp4viwvv72hjx2drr78prqy3nn3lvqwx"))))
    (properties `((upstream-name . "distfree.cr")))
    (build-system r-build-system)
    (home-page "http://statgen.ualberta.ca")
    (synopsis "Distribution-Free Confidence Region")
    (description
     "Constructs confidence regions without the need to know the sampling distribution
of bivariate data.  The method was proposed by Zhiqiu Hu & Rong-cai Yang (2013)
<doi:10.1371/journal.pone.0081179.g001>.")
    (license license:gpl2+)))

(define-public r-distdichor
  (package
    (name "r-distdichor")
    (version "0.1-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distdichoR" version))
       (sha256
        (base32 "0v19m3n1jgipg65yrv75rm4v27b5aq58cbsmbp7lxvfxmj5ra328"))))
    (properties `((upstream-name . "distdichoR")))
    (build-system r-build-system)
    (propagated-inputs (list r-sn r-nlme r-emmeans r-boot))
    (home-page "https://arxiv.org/abs/1809.03279")
    (synopsis
     "Distributional Method for the Dichotomisation of Continuous Outcomes")
    (description
     "This package contains a range of functions covering the present development of
the distributional method for the dichotomisation of continuous outcomes.  The
method provides estimates with standard error of a comparison of proportions
(difference, odds ratio and risk ratio) derived, with similar precision, from a
comparison of means.  See the URL below or <@code{arXiv:1809.03279>} for more
information.")
    (license license:expat)))

(define-public r-distcrete
  (package
    (name "r-distcrete")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distcrete" version))
       (sha256
        (base32 "0sa6z2mpmk51ig1r7bmpbyv2jd8z6z7mixki2vlq1kybg8cx3wmi"))))
    (properties `((upstream-name . "distcrete")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/reconhub/distcrete")
    (synopsis "Discrete Distribution Approximations")
    (description
     "This package creates discretised versions of continuous distribution functions
by mapping continuous values to an underlying discrete grid, based on a
(uniform) frequency of discretisation, a valid discretisation point, and an
integration range.  For a review of discretisation methods, see Chakraborty
(2015) <doi:10.1186/s40488-015-0028-6>.")
    (license license:expat)))

(define-public r-distcomp
  (package
    (name "r-distcomp")
    (version "1.3-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distcomp" version))
       (sha256
        (base32 "01h8cczkb0vb6560rh4czvajwa7gbgp41pl2b5xw7a68cbjizv8n"))))
    (properties `((upstream-name . "distcomp")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-stringr
                             r-shiny
                             r-rlang
                             r-r6
                             r-magrittr
                             r-jsonlite
                             r-httr
                             r-homomorpher
                             r-gmp
                             r-dplyr
                             r-digest))
    (native-inputs (list r-knitr))
    (home-page "http://dx.doi.org/10.18637/jss.v077.i13")
    (synopsis "Computations over Distributed Data without Aggregation")
    (description
     "Implementing algorithms and fitting models when sites (possibly remote) share
computation summaries rather than actual data over HTTP with a master R process
(using opencpu', for example).  A stratified Cox model and a singular value
decomposition are provided.  The former makes direct use of code from the R
survival package. (That is, the underlying Cox model code is derived from that
in the R survival package.) Sites may provide data via several means: CSV files,
Redcap API, etc.  An extensible design allows for new methods to be added in the
future and includes facilities for local prototyping and testing.  Web
applications are provided (via shiny') for the implemented methods to help in
designing and deploying the computations.")
    (license license:lgpl2.0+)))

(define-public r-distatisr
  (package
    (name "r-distatisr")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DistatisR" version))
       (sha256
        (base32 "0r8gp84kbl8kbsw3kbp8sk0xc2gav074qc9qlkq06bp0sxycwhyw"))))
    (properties `((upstream-name . "DistatisR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidytext r-readxl r-prettygraphs r-dplyr r-car))
    (home-page "https://cran.r-project.org/package=DistatisR")
    (synopsis "DiSTATIS Three Way Metric Multidimensional Scaling")
    (description
     "Implement @code{DiSTATIS} and @code{CovSTATIS} (three-way multidimensional
scaling). @code{DiSTATIS} and @code{CovSTATIS} are used to analyze multiple
distance/covariance matrices collected on the same set of observations.  These
methods are based on Abdi, H., Williams, L.J., Valentin, D., & Bennani-Dosse, M.
(2012) <doi:10.1002/wics.198>.")
    (license license:gpl2)))

(define-public r-distantia
  (package
    (name "r-distantia")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distantia" version))
       (sha256
        (base32 "12d6xzhcxs3xxyj82ih6chrr638siy45gna1s22vhnqvjd5jixc6"))))
    (properties `((upstream-name . "distantia")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis
                             r-rcolorbrewer
                             r-plyr
                             r-iterators
                             r-foreach
                             r-fields
                             r-doparallel
                             r-data-table
                             r-arrangements))
    (home-page "https://blasbenito.github.io/distantia/")
    (synopsis "Assessing Dissimilarity Between Multivariate Time Series")
    (description
     "This package provides tools to assess the dissimilarity between multivariate
time-series.  It is based on the psi measure described by Birks and Gordon (1985
<doi:10.1002/jqs.3390020110>), which computes dissimilarity between irregular
time-series constrained by sample order.  However, in this package the original
idea has been extended to work with any kind of multivariate time-series, no
matter whether they are regular, irregular, aligned or unaligned.  Furthermore,
the package allows to assess the significance of dissimilarity values by
applying a restricted permutation test, allows to measure the contribution of
individual variables to dissimilarity, and offers tools to transfer attributes
(generally time or age, but other are possible) between sequences based on the
similarity of their samples.")
    (license license:gpl2+)))

(define-public r-distanceto
  (package
    (name "r-distanceto")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distanceto" version))
       (sha256
        (base32 "0xsqvmakys75rz11w7mkhs7674lzgz2ml9bwbkydq3lkrg14hyww"))))
    (properties `((upstream-name . "distanceto")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf r-nabor r-geodist))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/robitalec/distance-to")
    (synopsis "Calculate Distance to Features")
    (description
     "Calculates distances from point locations to features.  The usual approach for
eg.  resource selection function analyses is to generate a complete distance to
features surface then sample it with your observed and random points.  Since
these raster based approaches can be pretty costly with large areas, and often
lead to memory issues in R, the distanceto package opts to compute these
distances using efficient, vector based approaches.  As a helper, there's a
decidedly low-res raster based approach for visually inspecting your region's
distance surface.  But the workhorse is distance_to.")
    (license license:gpl3+)))

(define-public r-distances
  (package
    (name "r-distances")
    (version "0.1.11")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "distances" version))
       (sha256
        (base32 "0v2i1q16kcxr1v988zcgpqgrwvagzfcafzxjkkz06x72j8s63jrd"))))
    (properties `((upstream-name . "distances")))
    (build-system r-build-system)
    (home-page "https://github.com/fsavje/distances")
    (synopsis "Tools for Distance Metrics")
    (description
     "This package provides tools for constructing, manipulating and using distance
metrics.")
    (license license:gpl3+)))

(define-public r-distance
  (package
    (name "r-distance")
    (version "1.0.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Distance" version))
       (sha256
        (base32 "05krzbk1dzlsx00vaghz1ny0wf00giglwvdy29c3xa9353pfgyix"))))
    (properties `((upstream-name . "Distance")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-mrds r-dplyr))
    (home-page "https://github.com/DistanceDevelopment/Distance/")
    (synopsis "Distance Sampling Detection Function and Abundance Estimation")
    (description
     "This package provides a simple way of fitting detection functions to distance
sampling data for both line and point transects.  Adjustment term selection,
left and right truncation as well as monotonicity constraints and binning are
supported.  Abundance and density estimates can also be calculated (via a
Horvitz-Thompson-like estimator) if survey area information is provided.  See
Miller et al. (2019) <doi:10.18637/jss.v089.i01> for more information on methods
and <https://examples.distancesampling.org/> for example analyses.")
    (license license:gpl2+)))

(define-public r-dissmod
  (package
    (name "r-dissmod")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiSSMod" version))
       (sha256
        (base32 "199yipbc2sx2lsl51rpfyh80bfxaahfd2llqmfsp946gvj7339hv"))))
    (properties `((upstream-name . "DiSSMod")))
    (build-system r-build-system)
    (propagated-inputs (list r-sfsmisc r-psych r-matrixcalc r-mass))
    (home-page "https://cran.r-project.org/package=DiSSMod")
    (synopsis
     "Fitting Sample Selection Models for Discrete Response Variables")
    (description
     "This package provides tools to fit sample selection models in case of discrete
response variables, through a parametric formulation which represents a natural
extension of the well-known Heckman selection model are provided in the package.
 The response variable can be of Bernoulli, Poisson or Negative Binomial type.
The sample selection mechanism allows to choose among a Normal, Logistic or
Gumbel distribution.")
    (license license:gpl2)))

(define-public r-dissever
  (package
    (name "r-dissever")
    (version "0.2-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dissever" version))
       (sha256
        (base32 "1lgs5nmv3lpm4gsryxvcwiwibvvg9flv23q8maisp77x49c18qcp"))))
    (properties `((upstream-name . "dissever")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis
                             r-sp
                             r-raster
                             r-plyr
                             r-magrittr
                             r-foreach
                             r-dplyr
                             r-caret
                             r-boot))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/pierreroudier/dissever")
    (synopsis "Spatial Downscaling using the Dissever Algorithm")
    (description
     "Spatial downscaling of coarse grid mapping to fine grid mapping using predictive
covariates and a model fitted using the caret package.  The original dissever
algorithm was published by Malone et al. (2012)
<doi:10.1016/j.cageo.2011.08.021>, and extended by Roudier et al. (2017)
<doi:10.1016/j.compag.2017.08.021>.")
    (license license:gpl2)))

(define-public r-disscqn
  (package
    (name "r-disscqn")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dissCqN" version))
       (sha256
        (base32 "142f4ggzwdhf2vm9kisayna9a5j17mmy2jckhjrvxh4k5dc3ssf6"))))
    (properties `((upstream-name . "dissCqN")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://murphymv.github.io/dissCqN/")
    (synopsis "Multiple Assemblage Dissimilarity for Orders q = 0-N")
    (description
     "Calculate multiple or pairwise dissimilarity for orders q = 0-N (@code{CqN};
Chao et al.  2008 <doi:10/fcvn63>) for a set of species assemblages or
interaction networks.")
    (license license:gpl3+)))

(define-public r-disprose
  (package
    (name "r-disprose")
    (version "0.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disprose" version))
       (sha256
        (base32 "0jmn8xjwfr3dhrsmx3lq8kz7lq9pnk95mgr97gi72c86c7rap935"))))
    (properties `((upstream-name . "disprose")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=disprose")
    (synopsis "Discriminating Probes Selection")
    (description
     "Set of tools for molecular probes selection and design of a microarray, e.g. the
assessment of physical and chemical properties, blast performance, selection
according to sensitivity and selectivity.  Methods used in package are described
in: Lorenz R., Stephan H.B., HÃ¶ner zu Siederdissen C. et al. (2011)
<doi:10.1186/1748-7188-6-26>; Camacho C., Coulouris G., Avagyan V. et al. (2009)
<doi:10.1186/1471-2105-10-421>.")
    (license license:gpl3)))

(define-public r-disprofas
  (package
    (name "r-disprofas")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disprofas" version))
       (sha256
        (base32 "16d0r94lj2bxp1dpizp5grjcbh627v5qqwj5iw8j4k345m784pcl"))))
    (properties `((upstream-name . "disprofas")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-lifecycle r-ggplot2 r-boot))
    (home-page "https://github.com/piusdahinden/disprofas")
    (synopsis "Non-Parametric Dissolution Profile Analysis")
    (description
     "Similarity of dissolution profiles is assessed using the similarity factor f2
according to the EMA guideline (European Medicines Agency 2010) \"On the
investigation of bioequivalence\".  Dissolution profiles are regarded as similar
if the f2 value is between 50 and 100.  For the applicability of the similarity
factor f2, the variability between profiles needs to be within certain limits.
Often, this constraint is violated.  One possibility in this situation is to
resample the measured profiles in order to obtain a bootstrap estimate of f2
(Shah et al. (1998) <doi:10.1023/A:1011976615750>).  Other alternatives are the
model-independent non-parametric multivariate confidence region (MCR) procedure
(Tsong et al. (1996) <doi:10.1177/009286159603000427>) or the T2-test for
equivalence procedure (Hoffelder (2016)
<https://www.ecv.de/suse_item.php?@code{suseId=Z|pi|8430>}).  Functions for
estimation of f1, f2, bootstrap f2, MCR / T2-test for equivalence procedure are
implemented.")
    (license license:gpl2+)))

(define-public r-disprity
  (package
    (name "r-disprity")
    (version "1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dispRity" version))
       (sha256
        (base32 "0hng3g5mq75b7rvdypnz816xahbfa4fgyi2n6drxma258qskyd68"))))
    (properties `((upstream-name . "dispRity")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-vegan
                             r-scales
                             r-phylolm
                             r-phyclust
                             r-phangorn
                             r-mnormt
                             r-mass
                             r-get
                             r-geometry
                             r-ellipse
                             r-claddis
                             r-castor
                             r-ape
                             r-ade4))
    (home-page "https://github.com/TGuillerme/dispRity")
    (synopsis "Measuring Disparity")
    (description
     "This package provides a modular package for measuring disparity
(multidimensional space occupancy).  Disparity can be calculated from any matrix
defining a multidimensional space.  The package provides a set of implemented
metrics to measure properties of the space and allows users to provide and test
their own metrics.  The package also provides functions for looking at disparity
in a serial way (e.g. disparity through time) or per groups as well as
visualising the results.  Finally, this package provides several statistical
tests for disparity analysis.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-dispositioneffect
  (package
    (name "r-dispositioneffect")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dispositionEffect" version))
       (sha256
        (base32 "17rj63jb8f3a00sakrsyw13syl6p54pbkjxgxpsyi8yhc690yfrl"))))
    (properties `((upstream-name . "dispositionEffect")))
    (build-system r-build-system)
    (propagated-inputs (list r-purrr r-progress r-magrittr r-lubridate r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://marcozanotti.github.io/dispositionEffect/")
    (synopsis "Analysis of Disposition Effect on Financial Portfolios")
    (description
     "Evaluate the presence of disposition effect and others irrational investor's
behaviors based solely on investor's transactions and financial market data.
Experimental data can also be used to perform the analysis.  Four different
methodologies are implemented to account for the different nature of human
behaviors on financial markets.  Novel analyses such as portfolio driven and
time series disposition effect are also allowed.")
    (license license:expat)))

(define-public r-disposables
  (package
    (name "r-disposables")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disposables" version))
       (sha256
        (base32 "0q5wacjclspn2fh7z1pg2l67ll51n75wck5h2fdq2vxy3qn3vwis"))))
    (properties `((upstream-name . "disposables")))
    (build-system r-build-system)
    (home-page "https://github.com/gaborcsardi/disposables")
    (synopsis "Create Disposable R Packages for Testing")
    (description
     "Create disposable R packages for testing.  You can create, install and load
multiple R packages with a single function call, and then unload, uninstall and
destroy them with another function call.  This is handy when testing how some R
code or an R package behaves with respect to other packages.")
    (license license:expat)))

(define-public r-dispmod
  (package
    (name "r-dispmod")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dispmod" version))
       (sha256
        (base32 "16r6is0pchzc9mxpz0c44f72j76vsh3j9damalcxajrha06dkdq4"))))
    (properties `((upstream-name . "dispmod")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dispmod")
    (synopsis "Modelling Dispersion in GLM")
    (description
     "This package provides functions for estimating Gaussian dispersion regression
models (Aitkin, 1987 <doi:10.2307/2347792>), overdispersed binomial logit models
(Williams, 1987 <doi:10.2307/2347977>), and overdispersed Poisson log-linear
models (Breslow, 1984 <doi:10.2307/2347661>), using a quasi-likelihood approach.")
    (license license:gpl2+)))

(define-public r-disperse
  (package
    (name "r-disperse")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dispeRse" version))
       (sha256
        (base32 "08qs060zj58wb5y0ah20qcpm7qz7x99p7h5rblcfhcy2vf4pf239"))))
    (properties `((upstream-name . "dispeRse")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp r-sf r-raster))
    (home-page "https://cran.r-project.org/package=dispeRse")
    (synopsis "Simulation of Demic Diffusion with Environmental Constraints")
    (description
     "Simulates demic diffusion building on models previously developed for the
expansion of Neolithic and other food-producing economies during the Holocene
(Fort et al. (2012) <doi:10.7183/0002-7316.77.2.203>, Souza et al. (2021)
<doi:10.1098/rsif.2021.0499>).  Growth and emigration are modelled as
density-dependent processes using logistic growth and an asymptotic threshold
model.  Environmental and terrain layers, which can change over time, affect
carrying capacity, growth and mobility.  Multiple centres of origin with their
respective starting times can be specified.")
    (license license:expat)))

(define-public r-disparityfilter
  (package
    (name "r-disparityfilter")
    (version "2.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disparityfilter" version))
       (sha256
        (base32 "0dkk3qws631mf0g02di5rsrvh5954cykysyri0g8aqgik0j9dg06"))))
    (properties `((upstream-name . "disparityfilter")))
    (build-system r-build-system)
    (propagated-inputs (list r-igraph))
    (home-page "https://github.com/alessandrobessi/disparityfilter")
    (synopsis "Disparity Filter Algorithm for Weighted Networks")
    (description
     "The disparity filter algorithm is a network reduction technique to identify the
backbone structure of a weighted network without destroying its multi-scale
nature.  The algorithm is documented in M. Angeles Serrano, Marian Boguna and
Alessandro Vespignani in \"Extracting the multiscale backbone of complex weighted
networks\", Proceedings of the National Academy of Sciences 106 (16), 2009.  This
implementation of the algorithm supports both directed and undirected networks.")
    (license license:gpl2+)))

(define-public r-disordr
  (package
    (name "r-disordr")
    (version "0.9-8.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disordR" version))
       (sha256
        (base32 "07ydnyifqdsan0kp74mlxaviwj4ccnsh77z36gsh2cpyhda2la8d"))))
    (properties `((upstream-name . "disordR")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-digest))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/RobinHankin/disordR")
    (synopsis "Non-Ordered Vectors")
    (description
     "Functionality for manipulating values of associative maps.  The package is
designed to be used with the mvp class of packages that use the STL map class:
its purpose is to trap plausible idiom that is ill-defined
(implementation-specific) and return an informative error, rather than returning
a possibly incorrect result.  To cite the package in publications please use
Hankin (2022) <doi:10.48550/ARXIV.2210.03856>.")
    (license license:gpl2+)))

(define-public r-disk-frame
  (package
    (name "r-disk-frame")
    (version "0.8.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disk.frame" version))
       (sha256
        (base32 "0mkzvxbjr9iw2bmnw4s5s7glly1nnf4j83y6yzw5vg1gwqghynky"))))
    (properties `((upstream-name . "disk.frame")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-rlang
                             r-rcpp
                             r-purrr
                             r-pryr
                             r-jsonlite
                             r-glue
                             r-globals
                             r-future-apply
                             r-future
                             r-fst
                             r-fs
                             r-dplyr
                             r-data-table
                             r-crayon
                             r-bit64
                             r-bigreadr
                             r-benchmarkme
                             r-arrow))
    (home-page "https://diskframe.com")
    (synopsis "Larger-than-RAM Disk-Based Data Manipulation Framework")
    (description
     "This package provides a disk-based data manipulation tool for working with
large-than-RAM datasets.  Aims to lower the barrier-to-entry for manipulating
large datasets by adhering closely to popular and familiar data manipulation
paradigms like dplyr verbs and data.table syntax.")
    (license license:expat)))

(define-public r-disimpact
  (package
    (name "r-disimpact")
    (version "0.0.21")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DisImpact" version))
       (sha256
        (base32 "1vc2kwcb3cvcdbdg0s5qnjdzn8qa7lv6f86milhxdf609k2zwdkx"))))
    (properties `((upstream-name . "DisImpact")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-stringr
                             r-sets
                             r-rlang
                             r-purrr
                             r-glue
                             r-fst
                             r-duckdb
                             r-dplyr
                             r-dbi
                             r-data-table
                             r-collapse))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/vinhdizzo/DisImpact")
    (synopsis
     "Calculates Disproportionate Impact When Binary Success Data are Disaggregated by Subgroups")
    (description
     "This package implements methods for calculating disproportionate impact: the
percentage point gap, proportionality index, and the 80% index.  California
Community Colleges Chancellor's Office (2017).  Percentage Point Gap Method.
<https://www.cccco.edu/-/media/CCCCO-Website/About-Us/Divisions/Digital-Innovation-and-Infrastructure/Research/Files/@code{PercentagePointGapMethod2017.ashx>}.
 California Community Colleges Chancellor's Office (2014).  Guidelines for
Measuring Disproportionate Impact in Equity Plans.
<https://www.cccco.edu/-/media/CCCCO-Website/Files/DII/guidelines-for-measuring-disproportionate-impact-in-equity-plans-tfa-ada.pdf>.")
    (license license:gpl3)))

(define-public r-disimformixed
  (package
    (name "r-disimformixed")
    (version "0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DisimForMixed" version))
       (sha256
        (base32 "00mknsalikangr17946877m5fy2jgkgasgl6ng4f2nr44f0q9l6q"))))
    (properties `((upstream-name . "DisimForMixed")))
    (build-system r-build-system)
    (propagated-inputs (list r-dplyr r-cluster))
    (home-page "https://cran.r-project.org/package=DisimForMixed")
    (synopsis
     "Calculate Dissimilarity Matrix for Dataset with Mixed Attributes")
    (description
     "Implement the methods proposed by Ahmad & Dey (2007)
<doi:10.1016/j.datak.2007.03.016> in calculating the dissimilarity matrix at the
presence of mixed attributes.  This Package includes functions to discretize
quantitative variables, calculate conditional probability for each pair of
attribute values, distance between every pair of attribute values, significance
of attributes, calculate dissimilarity between each pair of objects.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-dishet
  (package
    (name "r-dishet")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DisHet" version))
       (sha256
        (base32 "056jcs1qpiyadnmlzd0cj4kp0qzkichxi0pdnxypyq1fsqnpvan3"))))
    (properties `((upstream-name . "DisHet")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrixstats r-gtools))
    (home-page "https://cran.r-project.org/package=DisHet")
    (synopsis
     "Estimate the Gene Expression Levels and Component Proportions of the Normal, Stroma (Immune) and Tumor Components of Bulk Tumor Samples")
    (description
     "Model cell type heterogeneity of bulk renal cell carcinoma.  The observed gene
expression in bulk tumor sample is modeled by a log-normal distribution with the
location parameter structured as a linear combination of the component-specific
gene expressions.")
    (license license:gpl2)))

(define-public r-diseasystore
  (package
    (name "r-diseasystore")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diseasystore" version))
       (sha256
        (base32 "1024r1p4wawcg1346vk91xk7x5hxasliiyjp2y0nk085s4lb7s96"))))
    (properties `((upstream-name . "diseasystore")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-tidyselect
                             r-tidyr
                             r-stringr
                             r-scdb
                             r-rlang
                             r-readr
                             r-r6
                             r-purrr
                             r-lubridate
                             r-jsonlite
                             r-isoweek
                             r-glue
                             r-dplyr
                             r-dbplyr
                             r-dbi
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ssi-dk/diseasystore")
    (synopsis "Feature Stores for the 'diseasy' Framework")
    (description
     "Simple feature stores and tools for creating personalised feature stores.
diseasystore powers feature stores which can automatically link and aggregate
features to a given stratification level.  These feature stores are
automatically time-versioned (powered by the SCDB package) and allows you to
easily and dynamically compute features as part of your continuous integration.")
    (license license:gpl3+)))

(define-public r-diseasemapping
  (package
    (name "r-diseasemapping")
    (version "2.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diseasemapping" version))
       (sha256
        (base32 "1qjzyicz9wg63vqkkxpiqj991sirkpgax6cl9b6hr939rf2axs8j"))))
    (properties `((upstream-name . "diseasemapping")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=diseasemapping")
    (synopsis "Modelling Spatial Variation in Disease Risk for Areal Data")
    (description
     "Formatting of population and case data, calculation of Standardized Incidence
Ratios, and fitting the BYM model using INLA'.  For details see Brown (2015)
<doi:10.18637/jss.v063.i12>.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-disdat
  (package
    (name "r-disdat")
    (version "1.0-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disdat" version))
       (sha256
        (base32 "1m22pichm603gn9h94vx0kmds28krlp9ax1yrsfwx12rqchcdhk7"))))
    (properties `((upstream-name . "disdat")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=disdat")
    (synopsis "Data for Comparing Species Distribution Modeling Methods")
    (description
     "Easy access to species distribution data for 6 regions in the world, for a total
of 226 anonymised species.  These data are described and made available by Elith
et al (2020) <doi:10.17161/bi.v15i2.13384> to compare species distribution
modelling methods.")
    (license license:gpl3+)))

(define-public r-discursive
  (package
    (name "r-discursive")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "discursive" version))
       (sha256
        (base32 "14wn01p6vx1y1aprhz4r8y9dmvfxslif37nx854xnx6ncnihag57"))))
    (properties `((upstream-name . "discursive")))
    (build-system r-build-system)
    (propagated-inputs (list r-tm r-stringr r-stm r-snowballc))
    (home-page "https://cran.r-project.org/package=discursive")
    (synopsis
     "Measuring Discursive Sophistication in Open-Ended Survey Responses")
    (description
     "This package provides a simple approach to measure political sophistication
based on open-ended survey responses.  Discursive sophistication captures the
complexity of individual attitude expression by quantifying its relative size,
range, and constraint.  For more information on the measurement approach see:
Kraft, Patrick W. 2023. \"Women Also Know Stuff: Challenging the Gender Gap in
Political Sophistication.\" American Political Science Review (forthcoming).")
    (license license:gpl3+)))

(define-public r-discsurv
  (package
    (name "r-discsurv")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "discSurv" version))
       (sha256
        (base32 "0k585cyz02vqk4w7w20rhn6g9rspmmlbdpv7k837021iyhwwb838"))))
    (properties `((upstream-name . "discSurv")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam
                             r-treeclust
                             r-rpart
                             r-rdpack
                             r-ranger
                             r-mvtnorm
                             r-mvnfast
                             r-mgcv
                             r-geepack
                             r-functional
                             r-data-table))
    (home-page "https://cran.r-project.org/package=discSurv")
    (synopsis "Discrete Time Survival Analysis")
    (description
     "This package provides data transformations, estimation utilities, predictive
evaluation measures and simulation functions for discrete time survival
analysis.")
    (license license:gpl3)))

(define-public r-discrtr
  (package
    (name "r-discrtr")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "discrtr" version))
       (sha256
        (base32 "03xafiy7fjxsincbwbz1y0xv372yd7cs8sbmqvv2s3glx6jdxk07"))))
    (properties `((upstream-name . "discrtr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmdformats r-magrittr))
    (home-page "https://github.com/paezha/discrtr")
    (synopsis
     "Companion Package for the Book \"Discrete Choice Analysis with 'R'\"")
    (description
     "Templates and data files to support \"Discrete Choice Analysis with R\", PÃ¡ez, A.
and Boisjoly, G. (2023) <doi:10.1007/978-3-031-20719-8>.")
    (license license:expat)))

(define-public r-discrim
  (package
    (name "r-discrim")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "discrim" version))
       (sha256
        (base32 "098021yq1bdqd0hnpv3lh4w7zna2v0kn4pbsffgbkigg0qi8cgm0"))))
    (properties `((upstream-name . "discrim")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr r-tibble r-rlang r-parsnip r-dials))
    (home-page "https://github.com/tidymodels/discrim")
    (synopsis "Model Wrappers for Discriminant Analysis")
    (description
     "Bindings for additional classification models for use with the parsnip package.
Models include flavors of discriminant analysis, such as linear (Fisher (1936)
<doi:10.1111/j.1469-1809.1936.tb02137.x>), regularized (Friedman (1989)
<doi:10.1080/01621459.1989.10478752>), and flexible (Hastie, Tibshirani, and
Buja (1994) <doi:10.1080/01621459.1994.10476866>), as well as naive Bayes
classifiers (Hand and Yu (2007) <doi:10.1111/j.1751-5823.2001.tb00465.x>).")
    (license license:expat)))

(define-public r-discretization
  (package
    (name "r-discretization")
    (version "1.0-1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "discretization" version))
       (sha256
        (base32 "0jkxi0rirzi3dc3886b97sqwmkrkp25mq6avzp58iqy1w58likpk"))))
    (properties `((upstream-name . "discretization")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=discretization")
    (synopsis "Data Preprocessing, Discretization for Classification")
    (description
     "This package provides a collection of supervised discretization algorithms.  It
can also be grouped in terms of top-down or bottom-up, implementing the
discretization algorithms.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-discreteweibull
  (package
    (name "r-discreteweibull")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiscreteWeibull" version))
       (sha256
        (base32 "1rg3ax6jryagf5d3h8m44x9wyhr2qff3srfa9zrk6i64p1ahk9lr"))))
    (properties `((upstream-name . "DiscreteWeibull")))
    (build-system r-build-system)
    (propagated-inputs (list r-rsolnp))
    (home-page "https://cran.r-project.org/package=DiscreteWeibull")
    (synopsis "Discrete Weibull Distributions (Type 1 and 3)")
    (description
     "Probability mass function, distribution function, quantile function, random
generation and parameter estimation for the type I and III discrete Weibull
distributions.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-discretetests
  (package
    (name "r-discretetests")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiscreteTests" version))
       (sha256
        (base32 "18257srwfz99531wks60isi1dg95yv1xvpb4hhxh9qw9wijw08sp"))))
    (properties `((upstream-name . "DiscreteTests")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6 r-lifecycle r-checkmate))
    (home-page "https://github.com/DISOhda/DiscreteTests")
    (synopsis
     "Vectorised Computation of P-Values and Their Supports for Several Discrete Statistical Tests")
    (description
     "This package provides vectorised functions for computing p-values of various
common discrete statistical tests, as described e.g. in Agresti (2002)
<doi:10.1002/0471249688>, including their distributions.  Exact and approximate
computation methods are provided.  For exact p-values, several procedures of
determining two-sided p-values are included, which are outlined in more detail
in Hirji (2006) <doi:10.1201/9781420036190>.")
    (license license:gpl3)))

(define-public r-discreteqvalue
  (package
    (name "r-discreteqvalue")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiscreteQvalue" version))
       (sha256
        (base32 "1xl6m3sf02v4y26375jn846ixzcxpqim1r6d4j56y8b5c243jg4h"))))
    (properties `((upstream-name . "DiscreteQvalue")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DiscreteQvalue")
    (synopsis "Improved q-Values for Discrete Uniform and Homogeneous Tests")
    (description
     "We consider a multiple testing procedure used in many modern applications which
is the q-value method proposed by Storey and Tibshirani (2003),
<doi:10.1073/pnas.1530509100>.  The q-value method is based on the false
discovery rate (FDR), hence versions of the q-value method can be defined
depending on which estimator of the proportion of true null hypotheses, p0, is
plugged in the FDR estimator.  We implement the q-value method based on two
classical pi0 estimators, and furthermore, we propose and implement three
versions of the q-value method for homogeneous discrete uniform P-values based
on pi0 estimators which take into account the discrete distribution of the
P-values.")
    (license license:gpl2)))

(define-public r-discretelaplace
  (package
    (name "r-discretelaplace")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiscreteLaplace" version))
       (sha256
        (base32 "17w4vjvsm7jacvwckjczyah3hglq044r3m6vqdcrg8haz884rav2"))))
    (properties `((upstream-name . "DiscreteLaplace")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DiscreteLaplace")
    (synopsis "Discrete Laplace Distributions")
    (description
     "Probability mass function, distribution function, quantile function, random
generation and estimation for the skew discrete Laplace distributions.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-discreteinverseweibull
  (package
    (name "r-discreteinverseweibull")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiscreteInverseWeibull" version))
       (sha256
        (base32 "0vjsvl4m4zccfgizv7mzidbbpzqcm101x448vllcdcrn2xlnkmnq"))))
    (properties `((upstream-name . "DiscreteInverseWeibull")))
    (build-system r-build-system)
    (propagated-inputs (list r-rsolnp))
    (home-page "https://cran.r-project.org/package=DiscreteInverseWeibull")
    (synopsis "Discrete Inverse Weibull Distribution")
    (description
     "Probability mass function, distribution function, quantile function, random
generation and parameter estimation for the discrete inverse Weibull
distribution.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-discretefit
  (package
    (name "r-discretefit")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "discretefit" version))
       (sha256
        (base32 "0xyv3lff6xmz9q1k2lprll68fw9ckqhgl1z87pd9rm0ldy969m9p"))))
    (properties `((upstream-name . "discretefit")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/josh-mc/discretefit")
    (synopsis "Simulated Goodness-of-Fit Tests for Discrete Distributions")
    (description
     "This package implements fast Monte Carlo simulations for goodness-of-fit (GOF)
tests for discrete distributions.  This includes tests based on the Chi-squared
statistic, the log-likelihood-ratio (G^2) statistic, the Freeman-Tukey
(Hellinger-distance) statistic, the Kolmogorov-Smirnov statistic, the Cramer-von
Mises statistic as described in Choulakian, Lockhart and Stephens (1994)
<doi:10.2307/3315828>, and the root-mean-square statistic, see Perkins, Tygert,
and Ward (2011) <doi:10.1016/j.amc.2011.03.124>.")
    (license license:expat)))

(define-public r-discretefdr
  (package
    (name "r-discretefdr")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiscreteFDR" version))
       (sha256
        (base32 "02yj9pfxh1f4fgij4gq29aijd42im9b6npyhw4jirdpl7zkh0j8i"))))
    (properties `((upstream-name . "DiscreteFDR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo
                             r-rcpp
                             r-lifecycle
                             r-discretetests
                             r-discretedatasets
                             r-checkmate))
    (native-inputs (list r-r-rsp r-knitr))
    (home-page "https://github.com/DISOhda/DiscreteFDR")
    (synopsis
     "FDR Based Multiple Testing Procedures with Adaptation for Discrete Tests")
    (description
     "Implementations of the multiple testing procedures for discrete tests described
in the paper DÃ¶hler, Durand and Roquain (2018) \"New FDR bounds for discrete and
heterogeneous tests\" <doi:10.1214/18-EJS1441>.  The main procedures of the paper
(HSU and HSD), their adaptive counterparts (AHSU and AHSD), and the HBR variant
are available and are coded to take as input the results of a test procedure
from package @code{DiscreteTests}', or a set of observed p-values and their
discrete support under their nulls.  A shortcut function to obtain such p-values
and supports is also provided, along with a wrapper allowing to apply discrete
procedures directly to data.")
    (license license:gpl3)))

(define-public r-discretedists
  (package
    (name "r-discretedists")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiscreteDists" version))
       (sha256
        (base32 "1cag5z4ag1n21ya2fiwrxvflnn4fnqgqfqxgg48r68jvmzdglhbn"))))
    (properties `((upstream-name . "DiscreteDists")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-rcpp r-pracma r-gamlss-dist r-gamlss))
    (home-page "https://github.com/fhernanb/DiscreteDists")
    (synopsis "Discrete Statistical Distributions")
    (description
     "Implementation of new discrete statistical distributions.  Each distribution
includes the traditional functions as well as an additional function called the
family function, which can be used to estimate parameters within the gamlss
framework.")
    (license license:expat)))

(define-public r-discretedatasets
  (package
    (name "r-discretedatasets")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiscreteDatasets" version))
       (sha256
        (base32 "0jpjky99cfb7h3i244n16llmgkrkbavbmyhz181fxiaiwzs7z66c"))))
    (properties `((upstream-name . "DiscreteDatasets")))
    (build-system r-build-system)
    (propagated-inputs (list r-checkmate))
    (home-page "https://github.com/DISOhda/DiscreteDatasets")
    (synopsis "Example Data Sets for Use with Discrete Statistical Tests")
    (description
     "This package provides several data sets for use with discrete statistical tests
and discrete multiple testing procedures.  Some of them are also available as a
four-column version, so that each row represents a 2x2 table.")
    (license license:gpl3)))

(define-public r-discoverableresearch
  (package
    (name "r-discoverableresearch")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "discoverableresearch" version))
       (sha256
        (base32 "0gw9fpmsqj1cj2qr7hqr86j28kjn3qfykdkkxrazj3dnv981xhhy"))))
    (properties `((upstream-name . "discoverableresearch")))
    (build-system r-build-system)
    (propagated-inputs (list r-tm
                             r-synthesisr
                             r-stringi
                             r-stringdist
                             r-stopwords
                             r-readr
                             r-ngram
                             r-magrittr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=discoverableresearch")
    (synopsis
     "Checks Title, Abstract and Keywords to Optimise Discoverability")
    (description
     "This package provides a suite of tools are provided here to support authors in
making their research more discoverable.  check_keywords() - this function
checks the keywords to assess whether they are already represented in the title
and abstract.  check_fields() - this function compares terminology used across
the title, abstract and keywords to assess where terminological diversity (i.e.
the use of synonyms) could increase the likelihood of the record being
identified in a search.  The function looks for terms in the title and abstract
that also exist in other fields and highlights these as needing attention.
suggest_keywords() - this function takes a full text document and produces a
list of unigrams, bigrams and trigrams (1-, 2- or 2-word phrases) present in the
full text after removing stop words (words with a low utility in natural
language processing) that do not occur in the title or abstract that may be
suitable candidates for keywords.  suggest_title() - this function takes a full
text document and produces a list of the most frequently used unigrams, bigrams
and trigrams after removing stop words that do not occur in the abstract or
keywords that may be suitable candidates for title words.  check_title() - this
function carries out a number of sub tasks: 1) it compares the length (number of
words) of the title with the mean length of titles in major bibliographic
databases to assess whether the title is likely to be too short; 2) it assesses
the proportion of stop words in the title to highlight titles with low utility
in search engines that strip out stop words; 3) it compares the title with a
given sample of record titles from an .ris import and calculates a similarity
score based on phrase overlap.  This highlights the level of uniqueness of the
title.  This version of the package also contains functions currently in a
non-CRAN package called litsearchr <https://github.com/elizagrames/litsearchr>.")
    (license license:gpl3)))

(define-public r-discover
  (package
    (name "r-discover")
    (version "3.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "discoveR" version))
       (sha256
        (base32 "1smy2bzzqc4nvrd4qj2sq4d1f0pvbm4nixxh8xpy22lwwa8pkd24"))))
    (properties `((upstream-name . "discoveR")))
    (build-system r-build-system)
    (propagated-inputs (list r-shinyjs
                             r-shinydashboardplus
                             r-shinydashboard
                             r-shinycustomloader
                             r-shinyace
                             r-shiny
                             r-rlang
                             r-plotly
                             r-loader
                             r-htmlwidgets
                             r-htmltools
                             r-golem
                             r-ggplot2
                             r-ggdendro
                             r-factominer
                             r-echarts4r
                             r-dt
                             r-config
                             r-colourpicker
                             r-cluster))
    (home-page "https://www.promidat.com")
    (synopsis "Exploratory Data Analysis System")
    (description
     "This package performs an exploratory data analysis through a shiny interface.
It includes basic methods such as the mean, median, mode, normality test, among
others.  It also includes clustering techniques such as Principal Components
Analysis, Hierarchical Clustering and the K-Means Method.")
    (license license:gpl2+)))

(define-public r-discoursegt
  (package
    (name "r-discoursegt")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "discourseGT" version))
       (sha256
        (base32 "00s7bcwc5mdra5wwf3wac6s0bj2n6ryqfx7bv2zji6fp0h4ya4wc"))))
    (properties `((upstream-name . "discourseGT")))
    (build-system r-build-system)
    (propagated-inputs (list r-network
                             r-igraph
                             r-ggrepel
                             r-ggplot2
                             r-ggally
                             r-dplyr))
    (native-inputs (list r-r-rsp r-knitr))
    (home-page "https://cran.r-project.org/package=discourseGT")
    (synopsis
     "Analyze Group Patterns using Graph Theory in Educational Settings")
    (description
     "Analyzes group patterns using discourse analysis data with graph theory
mathematics.  Takes the order of which individuals talk and converts it to a
network edge and weight list.  Returns the density, centrality, centralization,
and subgroup information for each group.  Based on the analytical framework laid
out in Chai et al. (2019) <doi:10.1187/cbe.18-11-0222>.")
    (license license:expat)))

(define-public r-discos
  (package
    (name "r-discos")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiSCos" version))
       (sha256
        (base32 "0xwbiaqmlp7bpnkagadc87ay7shp9gls7d6vhi7ksws9r03134sm"))))
    (properties `((upstream-name . "DiSCos")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack
                             r-pracma
                             r-mass
                             r-ggplot2
                             r-extremestat
                             r-evmix
                             r-data-table
                             r-cvxr))
    (native-inputs (list r-knitr))
    (home-page "http://www.davidvandijcke.com/DiSCos/")
    (synopsis "Distributional Synthetic Controls Estimation")
    (description
     "The method of synthetic controls is a widely-adopted tool for evaluating causal
effects of policy changes in settings with observational data.  In many settings
where it is applicable, researchers want to identify causal effects of policy
changes on a treated unit at an aggregate level while having access to data at a
finer granularity.  This package implements a simple extension of the synthetic
controls estimator, developed in Gunsilius (2023) <doi:10.3982/ECTA18260>, that
takes advantage of this additional structure and provides nonparametric
estimates of the heterogeneity within the aggregate unit.  The idea is to
replicate the quantile function associated with the treated unit by a weighted
average of quantile functions of the control units.  The package contains tools
for aggregating and plotting the resulting distributional estimates, as well as
for carrying out inference on them.")
    (license license:expat)))

(define-public r-discord
  (package
    (name "r-discord")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "discord" version))
       (sha256
        (base32 "0is9gwj09zj25hklsxgi3k7ypq2qp2yx0vir6wgpnd30wa11zs5h"))))
    (properties `((upstream-name . "discord")))
    (build-system r-build-system)
    (home-page "https://github.com/R-Computing-Lab/discord")
    (synopsis "Functions for Discordant Kinship Modeling")
    (description
     "This package provides functions for discordant kinship modeling (and other
sibling-based quasi-experimental designs).  Currently, the package contains data
restructuring functions and functions for generating biometrically informed data
for kin pairs.")
    (license license:gpl3)))

(define-public r-discnorm
  (package
    (name "r-discnorm")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "discnorm" version))
       (sha256
        (base32 "05pzrrv2pwd3m15f8qxy0m2gsam3qw71bvapf061rbw1lzmr62b6"))))
    (properties `((upstream-name . "discnorm")))
    (build-system r-build-system)
    (propagated-inputs (list r-sirt
                             r-pbivnorm
                             r-mnormt
                             r-mass
                             r-lavaan
                             r-gofkernel
                             r-cubature
                             r-copula
                             r-arules))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=discnorm")
    (synopsis "Test for Discretized Normality in Ordinal Data")
    (description
     "Tests whether multivariate ordinal data may stem from discretizing a
multivariate normal distribution.  The test is described by Foldnes and
GrÃ¸nneberg (2019) <doi:10.1080/10705511.2019.1673168>.  In addition, an
adjusted polychoric correlation estimator is provided that takes marginal
knowledge into account, as described by GrÃ¸nneberg and Foldnes (2022)
<doi:10.1037/met0000495>.")
    (license license:gpl2+)))

(define-public r-disclosur
  (package
    (name "r-disclosur")
    (version "0.6.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disclosuR" version))
       (sha256
        (base32 "0s1j8j2jyvdr15wysi9y7yin5rz06hgd5rlqxpxz5zc8nyvar69r"))))
    (properties `((upstream-name . "disclosuR")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-tm
                             r-syuzhet
                             r-stringr
                             r-stringi
                             r-snowballc
                             r-sentimentanalysis
                             r-rlang
                             r-qdap
                             r-pdftools
                             r-lubridate
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=disclosuR")
    (synopsis "Text Conversion from Nexis Uni PDFs to R Data Frames")
    (description
     "Transform newswire and earnings call transcripts as PDF obtained from Nexis Uni
to R data frames.  Various newswires and @code{FairDisclosure} earnings call
formats are supported.  Further, users can apply several pre-defined
dictionaries on the data based on Graffin et al.
(2016)<doi:10.5465/amj.2013.0288> and Gamache et al.
(2015)<doi:10.5465/amj.2013.0377>.")
    (license license:gpl3)))

(define-public r-disclapmix2
  (package
    (name "r-disclapmix2")
    (version "0.6.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disclapmix2" version))
       (sha256
        (base32 "0lqg4wvx7jf4an2x3lq9486m5741djkw8q506vbn8xlh4gxwmp3s"))))
    (properties `((upstream-name . "disclapmix2")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-cluster))
    (home-page "https://cran.r-project.org/package=disclapmix2")
    (synopsis
     "Mixtures of Discrete Laplace Distributions using Numerical Optimisation")
    (description
     "Fit a mixture of Discrete Laplace distributions using plain numerical
optimisation.  This package has similar applications as the disclapmix package
that uses an EM algorithm.")
    (license license:gpl2+)))

(define-public r-disclapmix
  (package
    (name "r-disclapmix")
    (version "1.7.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disclapmix" version))
       (sha256
        (base32 "1rc5kv4abx1hxgkp3vb3f247nv887vrh9l2y189blq0p6k258575"))))
    (properties `((upstream-name . "disclapmix")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppprogress r-rcpp r-mass r-disclap r-cluster))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=disclapmix")
    (synopsis "Discrete Laplace Mixture Inference using the EM Algorithm")
    (description
     "Make inference in a mixture of discrete Laplace distributions using the EM
algorithm.  This can e.g. be used for modelling the distribution of Y
chromosomal haplotypes as described in [1, 2] (refer to the URL section).")
    (license (list license:gpl2
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-disclap
  (package
    (name "r-disclap")
    (version "1.5.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disclap" version))
       (sha256
        (base32 "0qsycr04xz1h90jyzxwagfkc4rkc8mb9srasvhrp7grynjxlbb9f"))))
    (properties `((upstream-name . "disclap")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=disclap")
    (synopsis "Discrete Laplace Exponential Family")
    (description
     "The discrete Laplace exponential family for use in fitting generalized linear
models.")
    (license license:gpl2)))

(define-public r-discharge
  (package
    (name "r-discharge")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "discharge" version))
       (sha256
        (base32 "1hwsdrbajmpfdc9arb1pjhx2w45dy3zrba9ibcrnpyqhhr4i1c5m"))))
    (properties `((upstream-name . "discharge")))
    (build-system r-build-system)
    (propagated-inputs (list r-lmom r-ggplot2 r-circstats r-checkmate r-boot))
    (home-page "https://cran.r-project.org/package=discharge")
    (synopsis "Fourier Analysis of Discharge Data")
    (description
     "Computes discrete fast Fourier transform of river discharge data and the derived
metrics.  The methods are described in J. L. Sabo, D. M. Post (2008)
<doi:10.1890/06-1340.1> and J. L. Sabo, A. Ruhi, G. W. Holtgrieve, V. Elliott,
M. E. Arias, P. B. Ngor, T. A. RÃ¤sÃ¤nsen, S. Nam (2017)
<doi:10.1126/science.aao1053>.")
    (license license:gpl3)))

(define-public r-discfrail
  (package
    (name "r-discfrail")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "discfrail" version))
       (sha256
        (base32 "1ll8c0fwwmz2yw8w582422r8bk9lr1570d7m7w2n1flrnqpqmk8j"))))
    (properties `((upstream-name . "discfrail")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-numderiv r-matrix))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/fgaspe04/discfrail")
    (synopsis
     "Cox Models for Time-to-Event Data with Nonparametric Discrete Group-Specific Frailties")
    (description
     "This package provides functions for fitting Cox proportional hazards models for
grouped time-to-event data, where the shared group-specific frailties have a
discrete nonparametric distribution.  The methods proposed in the package is
described by Gasperoni, F., Ieva, F., Paganoni, A. M., Jackson, C. H., Sharples,
L. (2018) <doi:10.1093/biostatistics/kxy071>.  There are also functions for
simulating from these models, with a nonparametric or a parametric baseline
hazard function.")
    (license license:gpl3)))

(define-public r-discfa
  (package
    (name "r-discfa")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "discFA" version))
       (sha256
        (base32 "0z455pymg48j5z8g4z6bpv8qrrwxj6gfw2p2135dpvl37jpgha42"))))
    (properties `((upstream-name . "discFA")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam))
    (home-page "https://cran.r-project.org/package=discFA")
    (synopsis "Discrete Factor Analysis")
    (description
     "Discrete factor analysis for dependent Poisson and negative binomial models with
truncation, zero inflation, and zero inflated truncation.")
    (license license:gpl3)))

(define-public r-discbio
  (package
    (name "r-discbio")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIscBIO" version))
       (sha256
        (base32 "0zr1lpfqn8q3xhh27aa59j5xq70fxhzkwqaqfi34zfsiqzb7cy6a"))))
    (properties `((upstream-name . "DIscBIO")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr
                             r-vegan
                             r-tsne
                             r-statmod
                             r-singlecellexperiment
                             r-rweka
                             r-rpart-plot
                             r-rpart
                             r-rcolorbrewer
                             r-png
                             r-org-hs-eg-db
                             r-netindices
                             r-mclust
                             r-impute
                             r-igraph
                             r-httr
                             r-ggplot2
                             r-fpc
                             r-cluster
                             r-annotationdbi))
    (home-page "https://github.com/ocbe-uio/DIscBIO")
    (synopsis
     "User-Friendly Pipeline for Biomarker Discovery in Single-Cell Transcriptomics")
    (description
     "An open, multi-algorithmic pipeline for easy, fast and efficient analysis of
cellular sub-populations and the molecular signatures that characterize them.
The pipeline consists of four successive steps: data pre-processing, cellular
clustering with pseudo-temporal ordering, defining differential expressed genes
and biomarker identification.  More details on Ghannoum et.  al. (2021)
<doi:10.3390/ijms22031399>.  This package implements extensions of the work
published by Ghannoum et.  al. (2019) <doi:10.1101/700989>.")
    (license license:expat)))

(define-public r-discauc
  (package
    (name "r-discauc")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "discAUC" version))
       (sha256
        (base32 "1b0pk75jk7z9hcrv3pnci4709cvc2givwdbisd6yhanlg9vsz545"))))
    (properties `((upstream-name . "discAUC")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-rlang r-glue r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jefriedel/discAUC")
    (synopsis "Linear and Non-Linear AUC for Discounting Data")
    (description
     "Area under the curve (AUC; Myerson et al., 2001) <doi:10.1901/jeab.2001.76-235>
is a popular measure used in discounting research.  Although the calculation of
AUC is standardized, there are differences in AUC based on some assumptions.
For example, Myerson et al. (2001) <doi:10.1901/jeab.2001.76-235> assumed that
(with delay discounting data) a researcher would impute an indifference point at
zero delay equal to the value of the larger, later outcome.  However, this
practice is not clearly followed.  This imputed zero-delay indifference point
plays an important role in log and ordinal versions of AUC. Ordinal and log
versions of AUC are described by Borges et al. (2016)<doi:10.1002/jeab.219>.
The package can calculate all three versions of AUC [and includes a new version:
IHS(AUC)], impute indifference points when x = 0, calculate ordinal AUC in the
case of Halton sampling of x-values, and account for probability discounting
AUC.")
    (license license:gpl3)))

(define-public r-disbayes
  (package
    (name "r-disbayes")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disbayes" version))
       (sha256
        (base32 "0dzgs048pwpl59fpnvqdra001xkwllxpkaxanwdbmzc8l1xmrwb2"))))
    (properties `((upstream-name . "disbayes")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stanheaders
                             r-shelf
                             r-rstan
                             r-rcppparallel
                             r-rcppeigen
                             r-rcpp
                             r-mgcv
                             r-matrixstats
                             r-magrittr
                             r-loo
                             r-ggplot2
                             r-generics
                             r-dplyr
                             r-bh))
    (native-inputs (list r-knitr))
    (home-page "https://chjackson.github.io/disbayes/")
    (synopsis "Bayesian Multi-State Modelling of Chronic Disease Burden Data")
    (description
     "Estimation of incidence and case fatality for a chronic disease, given partial
information, using a multi-state model.  Given data on age-specific mortality
and either incidence or prevalence, Bayesian inference is used to estimate the
posterior distributions of incidence, case fatality, and functions of these such
as prevalence.  The methods are described in Jackson et al. (2023)
<doi:10.1093/jrsssa/qnac015>.")
    (license license:gpl3)))

(define-public r-disastr-api
  (package
    (name "r-disastr-api")
    (version "1.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disastr.api" version))
       (sha256
        (base32 "08yf0i94lrs25ffy9g6md8mzxcq9s3ywcw0ryvfddi25ddym6jxy"))))
    (properties `((upstream-name . "disastr.api")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr))
    (home-page "https://cran.r-project.org/package=disastr.api")
    (synopsis "Wrapper for the UN OCHA ReliefWeb Disaster Events API")
    (description
     "Access and manage the application programming interface (API) of the United
Nations Office for the Coordination of Humanitarian Affairs (OCHA)
@code{ReliefWeb} disaster events at <https://reliefweb.int/disasters>.  The
package requires a minimal number of dependencies.  It offers functionality to
retrieve a user-defined sample of disaster events from @code{ReliefWeb},
providing an easy alternative to scraping the @code{ReliefWeb} website.  It
enables a seamless integration of regular data updates into the research work
flow.")
    (license license:gpl3)))

(define-public r-disaggregation
  (package
    (name "r-disaggregation")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disaggregation" version))
       (sha256
        (base32 "02sn3byrw2smflimycdlax8yd0wf42qlmyjlknc74v1zc69xaw1h"))))
    (properties `((upstream-name . "disaggregation")))
    (build-system r-build-system)
    (propagated-inputs (list r-tmb
                             r-tidyterra
                             r-terra
                             r-splancs
                             r-sparsemvn
                             r-sf
                             r-rspde
                             r-rcppeigen
                             r-matrix
                             r-ggplot2
                             r-fmesher
                             r-dplyr
                             r-cowplot))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=disaggregation")
    (synopsis "Disaggregation Modelling")
    (description
     "Fits disaggregation regression models using TMB ('Template Model Builder').
When the response data are aggregated to polygon level but the predictor
variables are at a higher resolution, these models can be useful.  Regression
models with spatial random fields.  The package is described in detail in Nandi
et al. (2023) <doi:10.18637/jss.v106.i11>.")
    (license license:expat)))

(define-public r-disaggregatets
  (package
    (name "r-disaggregatets")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DisaggregateTS" version))
       (sha256
        (base32 "17d9mvznxysyybmnl5yz0sx15dxxry4vxpafp35s3sdlarg5jv39"))))
    (properties `((upstream-name . "DisaggregateTS")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-withr r-rdpack r-matrix r-lars))
    (home-page "https://cran.r-project.org/package=DisaggregateTS")
    (synopsis "High-Dimensional Temporal Disaggregation")
    (description
     "First - Generates (potentially high-dimensional) high-frequency and
low-frequency series for simulation studies in temporal disaggregation; Second -
a toolkit utilizing temporal disaggregation and benchmarking techniques with a
low-dimensional matrix of indicator series previously proposed in Dagum and
Cholette (2006, ISBN:978-0-387-35439-2) ; and Third - novel techniques proposed
by Mosley, Gibberd and Eckley (2021) <@code{arXiv:2108.05783>} for
disaggregating low-frequency series in the presence of high-dimensional
indicator matrices.")
    (license license:gpl3+)))

(define-public r-disaggr
  (package
    (name "r-disaggr")
    (version "1.0.5.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "disaggR" version))
       (sha256
        (base32 "1i2in27gygmh1l05371hzbf8zssgsjl6jyljsr964gk02l0ghkpn"))))
    (properties `((upstream-name . "disaggR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer))
    (native-inputs (list r-knitr))
    (home-page "https://inseefr.github.io/disaggR/")
    (synopsis "Two-Steps Benchmarks for Time Series Disaggregation")
    (description
     "The @code{twoStepsBenchmark}() and @code{threeRuleSmooth}() functions allow you
to disaggregate a low-frequency time series with higher frequency time series,
using the French National Accounts methodology.  The aggregated sum of the
resulting time series is strictly equal to the low-frequency time series within
the benchmarking window.  Typically, the low-frequency time series is an annual
one, unknown for the last year, and the high frequency one is either quarterly
or monthly.  See \"Methodology of quarterly national accounts\", Insee MÃ©thodes
NÂ°126, by Insee (2012, ISBN:978-2-11-068613-8,
<https://www.insee.fr/en/information/2579410>).")
    (license license:expat)))

(define-public r-dirttee
  (package
    (name "r-dirttee")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dirttee" version))
       (sha256
        (base32 "1kmchjvm5x3gsvq2dqxr4di2l607j1ivsm75zwggaiwi8yjz9s4c"))))
    (properties `((upstream-name . "dirttee")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-rlang
                             r-provenance
                             r-nloptr
                             r-mgcv
                             r-matrix
                             r-mass
                             r-formula-tools
                             r-expectreg))
    (home-page "https://cran.r-project.org/package=dirttee")
    (synopsis "Distributional Regression for Time to Event Data")
    (description
     "Semiparametric distributional regression methods (expectile, quantile and mode
regression) for time-to-event variables with right-censoring; uses inverse
probability of censoring weights or accelerated failure time models with
auxiliary likelihoods.  Expectile regression using inverse probability of
censoring weights has been introduced in Seipp et al. (2021) ``Weighted
Expectile Regression for Right-Censored Data <doi:10.1002/sim.9137>, mode
regression for time-to-event variables has been introduced in Seipp et al.
(2022) ``Flexible Semiparametric Mode Regression for Time-to-Event Data
<doi:10.1177/09622802221122406>.")
    (license license:gpl2+)))

(define-public r-dirstats
  (package
    (name "r-dirstats")
    (version "0.1.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DirStats" version))
       (sha256
        (base32 "1l4sxg5vlgnx30rcpwj9iw9kzl79cbwmarbip2n7bp7fpb8wsl3i"))))
    (properties `((upstream-name . "DirStats")))
    (build-system r-build-system)
    (propagated-inputs (list r-rotasym r-movmf))
    (native-inputs (list gfortran))
    (home-page "https://github.com/egarpor/DirStats")
    (synopsis "Nonparametric Methods for Directional Data")
    (description
     "Nonparametric kernel density estimation, bandwidth selection, and other
utilities for analyzing directional data.  Implements the estimator in Bai, Rao
and Zhao (1987) <doi:10.1016/0047-259X(88)90113-3>, the cross-validation
bandwidth selectors in Hall, Watson and Cabrera (1987)
<doi:10.1093/biomet/74.4.751> and the plug-in bandwidth selectors in
GarcÃ­a-PortuguÃ©s (2013) <doi:10.1214/13-ejs821>.")
    (license license:gpl3)))

(define-public r-dirmcmc
  (package
    (name "r-dirmcmc")
    (version "1.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dirmcmc" version))
       (sha256
        (base32 "117p3jvinmha7a2phcpzq38ig05kcranp15xbxqvv0cgh3c95fjr"))))
    (properties `((upstream-name . "dirmcmc")))
    (build-system r-build-system)
    (propagated-inputs (list r-mcmcse))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dirmcmc")
    (synopsis "Directional Metropolis Hastings Algorithm")
    (description
     "Implementation of Directional Metropolis Hastings Algorithm for MCMC.")
    (license license:gpl3)))

(define-public r-dirichletprocess
  (package
    (name "r-dirichletprocess")
    (version "0.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dirichletprocess" version))
       (sha256
        (base32 "1b500cm5ljpvpa0axqnylcvk8x3vmva1jy179k97ggps58lmspcj"))))
    (properties `((upstream-name . "dirichletprocess")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-gtools r-ggplot2))
    (home-page "https://github.com/dm13450/dirichletprocess")
    (synopsis "Build Dirichlet Process Objects for Bayesian Modelling")
    (description
     "Perform nonparametric Bayesian analysis using Dirichlet processes without the
need to program the inference algorithms.  Utilise included pre-built models or
specify custom models and allow the dirichletprocess package to handle the
Markov chain Monte Carlo sampling.  Our Dirichlet process objects can act as
building blocks for a variety of statistical models including and not limited
to: density estimation, clustering and prior distributions in hierarchical
models.  See Teh, Y. W. (2011)
<https://www.stats.ox.ac.uk/~teh/research/npbayes/Teh2010a.pdf>, among many
other sources.")
    (license license:gpl3)))

(define-public r-directstandardisation
  (package
    (name "r-directstandardisation")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DirectStandardisation" version))
       (sha256
        (base32 "1qlfvzlig3a2v78fiq6sbbpxklmjczikxdw57m6mqngzrl9vdl2g"))))
    (properties `((upstream-name . "DirectStandardisation")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DirectStandardisation")
    (synopsis "Adjusted Means and Proportions by Direct Standardisation")
    (description
     "Calculate adjusted means and proportions of a variable by groups defined by
another variable by direct standardisation, standardised to the structure of the
dataset.")
    (license license:gpl2)))

(define-public r-directpa
  (package
    (name "r-directpa")
    (version "1.5.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "directPA" version))
       (sha256
        (base32 "0q6g18rwz5bfg73f144lzfp0apc4jf2gibh8h3vci0fnmwfvs7gz"))))
    (properties `((upstream-name . "directPA")))
    (build-system r-build-system)
    (propagated-inputs (list r-plotly r-calibrate))
    (home-page "https://cran.r-project.org/package=directPA")
    (synopsis "Direction Analysis for Pathways and Kinases")
    (description
     "Direction analysis is a set of tools designed to identify combinatorial effects
of multiple treatments/conditions on pathways and kinases profiled by
microarray, RNA-seq, proteomics, or phosphoproteomics data.  See Yang P et al
(2014) <doi:10.1093/bioinformatics/btt616>; and Yang P et al. (2016)
<doi:10.1002/pmic.201600068>.")
    (license license:gpl3)))

(define-public r-directotree
  (package
    (name "r-directotree")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "directotree" version))
       (sha256
        (base32 "1yv703mb3fnvjxr2rrxvb8x869hbbjx4l94qbbsmy0ssknayq60y"))))
    (properties `((upstream-name . "directotree")))
    (build-system r-build-system)
    (propagated-inputs (list r-data-tree r-collapsibletree))
    (home-page "https://cran.r-project.org/package=directotree")
    (synopsis "Creates an Interactive Tree Structure of a Directory")
    (description
     "Represents the content of a directory as an interactive collapsible tree.
Offers the possibility to assign a text (e.g., a Readme.txt') to each folder
(represented as a clickable node), so that when the user hovers the pointer over
a node, the corresponding text is displayed as a tooltip.")
    (license license:gpl3+)))

(define-public r-directional
  (package
    (name "r-directional")
    (version "6.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Directional" version))
       (sha256
        (base32 "0ncr8ihzmmk3yw5393mlj3k536nqx1wm2vl045m4drjp1845dqdy"))))
    (properties `((upstream-name . "Directional")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf
                             r-rnaturalearth
                             r-rnanoflann
                             r-rgl
                             r-rfast2
                             r-rfast
                             r-magrittr
                             r-ggplot2
                             r-foreach
                             r-doparallel
                             r-bigstatsr))
    (home-page "https://cran.r-project.org/package=Directional")
    (synopsis "Collection of Functions for Directional Data Analysis")
    (description
     "This package provides a collection of functions for directional data (including
massive data, with millions of observations) analysis.  Hypothesis testing,
discriminant and regression analysis, MLE of distributions and more are
included.  The standard textbook for such data is the \"Directional Statistics\"
by Mardia, K. V. and Jupp, P. E. (2000).  Other references include a) Phillip J.
Paine, Simon P. Preston Michail Tsagris and Andrew T. A. Wood (2018). \"An
elliptically symmetric angular Gaussian distribution\".  Statistics and Computing
28(3): 689-697. <doi:10.1007/s11222-017-9756-4>.  b) Tsagris M. and Alenazi A.
(2019). \"Comparison of discriminant analysis methods on the sphere\".
Communications in Statistics: Case Studies, Data Analysis and Applications
5(4):467--491. <doi:10.1080/23737484.2019.1684854>.  c) P. J. Paine, S. P.
Preston, M. Tsagris and Andrew T. A. Wood (2020). \"Spherical regression models
with general covariates and anisotropic errors\".  Statistics and Computing
30(1): 153--165. <doi:10.1007/s11222-019-09872-2>.  d) Tsagris M. and Alenazi A.
(2024). \"An investigation of hypothesis testing procedures for circular and
spherical mean vectors\".  Communications in Statistics-Simulation and
Computation, 53(3): 1387--1408. <doi:10.1080/03610918.2022.2045499>.  e) Tsagris
M. and Alzeley O. (2023). \"Circular and spherical projected Cauchy
distributions: A Novel Framework for Circular and Directional Data Modeling\".
<doi:10.48550/@code{arXiv.2302.02468>}.  f) Zehao Yu and Xianzheng Huang (2024).
 A new parameterization for elliptically symmetric angular Gaussian
distributions of arbitrary dimension.  Electronic Journal of Statistics, 18(1):
301--334. <doi:10.1214/23-EJS2210>.  g) Tsagris M. (2024). \"Directional data
analysis using the spherical Cauchy and the Poisson-kernel based distribution\".
<doi:10.48550/@code{arXiv.2409.03292>}.")
    (license license:gpl2+)))

(define-public r-directeffects
  (package
    (name "r-directeffects")
    (version "0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DirectEffects" version))
       (sha256
        (base32 "181m5xhlgrpmj4c9zdr70sn8gwxlpd54cc5yjngyx5j0l9mfi5a3"))))
    (properties `((upstream-name . "DirectEffects")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-matching
                             r-glue
                             r-generics
                             r-formula
                             r-broom))
    (native-inputs (list r-knitr))
    (home-page "https://mattblackwell.github.io/DirectEffects/")
    (synopsis
     "Estimating Controlled Direct Effects for Explaining Causal Findings")
    (description
     "This package provides a set of functions to estimate the controlled direct
effect of treatment fixing a potential mediator to a specific value.  Implements
the sequential g-estimation estimator described in Vansteelandt (2009)
<doi:10.1097/EDE.0b013e3181b6f4c9> and Acharya, Blackwell, and Sen (2016)
<doi:10.1017/S0003055416000216> and the telescope matching estimator described
in Blackwell and Strezhnev (2020) <doi:10.1111/rssa.12759>.")
    (license license:gpl2+)))

(define-public r-directedclustering
  (package
    (name "r-directedclustering")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DirectedClustering" version))
       (sha256
        (base32 "0ac5dn0mi8j6jvl7zsv9k9mbanfs2h65haqy2lyqzh5s6vw61i2y"))))
    (properties `((upstream-name . "DirectedClustering")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DirectedClustering")
    (synopsis "Directed Weighted Clustering Coefficient")
    (description
     "Allows the computation of clustering coefficients for directed and weighted
networks by using different approaches.  It allows to compute clustering
coefficients that are not present in igraph package.  A description of
clustering coefficients can be found in \"Directed clustering in weighted
networks: a new perspective\", Clemente, G.P., Grassi, R. (2017),
<doi:10.1016/j.chaos.2017.12.007>.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-direct
  (package
    (name "r-direct")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIRECT" version))
       (sha256
        (base32 "0868918aa0nxhgmczpbpf9i06x9ik18vff51cdb4i9q405mal6sj"))))
    (properties `((upstream-name . "DIRECT")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DIRECT")
    (synopsis
     "Bayesian Clustering of Multivariate Data Under the Dirichlet-Process Prior")
    (description
     "This package provides a Bayesian clustering method for replicated time series or
replicated measurements from multiple experimental conditions, e.g., time-course
gene expression data.  It estimates the number of clusters directly from the
data using a Dirichlet-process prior.  See Fu, A. Q., Russell, S., Bray, S. and
Tavare, S. (2013) Bayesian clustering of replicated time-course gene expression
data with weak signals.  The Annals of Applied Statistics.  7(3) 1334-1361.
<doi:10.1214/13-AOAS650>.")
    (license license:gpl2+)))

(define-public r-dire
  (package
    (name "r-dire")
    (version "2.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Dire" version))
       (sha256
        (base32 "140qqpp0vhqw0vmzff58sx51nj21x61z063j4j23nrdrl3ylamcv"))))
    (properties `((upstream-name . "Dire")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo
                             r-rcpp
                             r-matrix
                             r-mass
                             r-lbfgs
                             r-iterators
                             r-haven
                             r-foreach))
    (native-inputs (list r-knitr))
    (home-page "https://american-institutes-for-research.github.io/Dire/")
    (synopsis "Linear Regressions with a Latent Outcome Variable")
    (description
     "Fit latent variable linear models, estimating score distributions for groups of
people, following Cohen and Jiang (1999) <doi:10.2307/2669917>.  In this model,
a latent distribution is conditional on students item response, item
characteristics, and conditioning variables the user includes.  This latent
trait is then integrated out.  This software is intended to fit the same models
as the existing software AM <https://am.air.org/>.  As of version 2, also allows
the user to draw plausible values.")
    (license license:gpl2)))

(define-public r-dipw
  (package
    (name "r-dipw")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dipw" version))
       (sha256
        (base32 "0nxjwiffi1ivafzha3c35kjk36ai7na0nbfl6x3gpsi2km7b84nd"))))
    (properties `((upstream-name . "dipw")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmosek r-matrix r-glmnet))
    (home-page "https://cran.r-project.org/package=dipw")
    (synopsis "Debiased Inverse Propensity Score Weighting")
    (description
     "Estimation of the average treatment effect when controlling for high-dimensional
confounders using debiased inverse propensity score weighting (DIPW).  DIPW
relies on the propensity score following a sparse logistic regression model, but
the regression curves are not required to be estimable.  Despite this, our
package also allows the users to estimate the regression curves and take the
estimated curves as input to our methods.  Details of the methodology can be
found in Yuhao Wang and Rajen D. Shah (2020) \"Debiased Inverse Propensity Score
Weighting for Estimation of Average Treatment Effects with High-Dimensional
Confounders\" <@code{arXiv:2011.08661>}.  The package relies on the optimisation
software MOSEK <https://www.mosek.com/> which must be installed separately; see
the documentation for Rmosek'.")
    (license license:gpl3)))

(define-public r-dipsaus
  (package
    (name "r-dipsaus")
    (version "0.2.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dipsaus" version))
       (sha256
        (base32 "12bhxys313iqrfkd0cpr2ibv94v14vjj3sxkhvhxqhclf1d19qc6"))))
    (properties `((upstream-name . "dipsaus")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-shiny
                             r-rstudioapi
                             r-rlang
                             r-rcpp
                             r-r6
                             r-progressr
                             r-jsonlite
                             r-future-apply
                             r-future
                             r-fastmap
                             r-digest
                             r-cli
                             r-base64enc))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/dipterix/dipsaus")
    (synopsis "Dipping Sauce for Data Analysis and Visualizations")
    (description
     "Works as an \"add-on\" to packages like shiny', future', as well as rlang', and
provides utility functions.  Just like dipping sauce adding flavors to potato
chips or pita bread, dipsaus for data analysis and visualizations adds handy
functions and enhancements to popular packages.  The goal is to provide simple
solutions that are frequently asked for online, such as how to synchronize shiny
inputs without freezing the app, or how to get memory size on Linux or
@code{MacOS} system.  The enhancements roughly fall into these four categories:
1.  shiny input widgets; 2.  high-performance computing using the future
package; 3.  modify R calls and convert among numbers, strings, and other
objects.  4.  utility functions to get system information such like CPU
chip-set, memory limit, etc.")
    (license license:gpl3)))

(define-public r-dips
  (package
    (name "r-dips")
    (version "0.6.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiPs" version))
       (sha256
        (base32 "148lbw5f62sm93n5bgn6rswqi3g7j6prdrscz56xalj65d3z1dz5"))))
    (properties `((upstream-name . "DiPs")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlemon r-plyr r-mvnfast))
    (home-page "https://cran.r-project.org/package=DiPs")
    (synopsis
     "Directional Penalties for Optimal Matching in Observational Studies")
    (description
     "Improves the balance of optimal matching with near-fine balance by giving
penalties on the unbalanced covariates with the unbalanced directions.  Many
directional penalties can also be viewed as Lagrange multipliers, pushing a
matched sample in the direction of satisfying a linear constraint that would not
be satisfied without penalization.  Yu and Rosenbaum (2019)
<doi:10.1111/biom.13098>.")
    (license license:expat)))

(define-public r-dipm
  (package
    (name "r-dipm")
    (version "1.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dipm" version))
       (sha256
        (base32 "1hzcwjnjrhd1s31w8pnyhpfz519jvj820jyq1rdkq8qllny5jbrk"))))
    (properties `((upstream-name . "dipm")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-partykit r-ggplot2))
    (home-page "https://cran.r-project.org/package=dipm")
    (synopsis "Depth Importance in Precision Medicine (DIPM) Method")
    (description
     "An implementation by Chen, Li, and Zhang (2022) <doi: 10.1093/bioadv/vbac041> of
the Depth Importance in Precision Medicine (DIPM) method in Chen and Zhang
(2022) <doi:10.1093/biostatistics/kxaa021> and Chen and Zhang (2020)
<doi:10.1007/978-3-030-46161-4_16>.  The DIPM method is a classification tree
that searches for subgroups with especially poor or strong performance in a
given treatment group.")
    (license license:gpl2+)))

(define-public r-diphiseq
  (package
    (name "r-diphiseq")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiPhiSeq" version))
       (sha256
        (base32 "11l2inf99vxz9k292307j8c2b25kc1066svy3vxrfl72rrm4fqa7"))))
    (properties `((upstream-name . "DiPhiSeq")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DiPhiSeq")
    (synopsis
     "Robust Tests for Differential Dispersion and Differential Expression in RNA-Sequencing Data")
    (description
     "This package implements the algorithm described in Jun Li and Alicia T. Lamere,
\"@code{DiPhiSeq}: Robust comparison of expression levels on RNA-Seq data with
large sample sizes\" (Unpublished).  Detects not only genes that show different
average expressions (\"differential expression\", DE), but also genes that show
different diversities of expressions in different groups (\"differentially
dispersed\", DD).  DD genes can be important clinical markers. @code{DiPhiSeq}
uses a redescending penalty on the quasi-likelihood function, and thus has
superior robustness against outliers and other noise.  Updates from version
0.1.0: (1) Added the option of using adaptive initial value for phi. (2) Added a
function for estimating the proportion of outliers in the data. (3) Modified the
input parameter names for clarity, and modified the output format for the main
function.")
    (license license:gpl3)))

(define-public r-dipalm
  (package
    (name "r-dipalm")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiPALM" version))
       (sha256
        (base32 "0y6nzf7lkf0znp88r7k0myf5k1c7cqcc2gh5kgzj5q8savhr90ax"))))
    (properties `((upstream-name . "DiPALM")))
    (build-system r-build-system)
    (propagated-inputs (list r-wgcna r-limma r-ggplot2))
    (home-page "https://cran.r-project.org/package=DiPALM")
    (synopsis "Differential Pattern Analysis via Linear Modeling")
    (description
     "Individual gene expression patterns are encoded into a series of eigenvector
patterns ('WGCNA package).  Using the framework of linear model-based
differential expression comparisons ('limma package), time-course expression
patterns for genes in different conditions are compared and analyzed for
significant pattern changes.  For reference, see: Greenham K, Sartor RC, Zorich
S, Lou P, Mockler TC and @code{McClung} CR. @code{eLife}.  2020 Sep 30;9(4).
<doi:10.7554/@code{eLife.58993>}.")
    (license license:gpl2+)))

(define-public r-dint
  (package
    (name "r-dint")
    (version "2.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dint" version))
       (sha256
        (base32 "1hkbvf4aidjqmcq79bh2k0lg6ayrrhq60zl1vv93zc6a792i55ka"))))
    (properties `((upstream-name . "dint")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/s-fleck/dint")
    (synopsis "Toolkit for Year-Quarter, Year-Month and Year-Isoweek Dates")
    (description
     "S3 classes and methods to create and work with year-quarter, year-month and
year-isoweek vectors.  Basic arithmetic operations (such as adding and
subtracting) are supported, as well as formatting and converting to and from
standard R date types.")
    (license license:expat)))

(define-public r-diner
  (package
    (name "r-diner")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dineR" version))
       (sha256
        (base32 "1nnfg4kylb8ivwij1qdn9qv5jciinl4jk4gghfw97jphp4da91pw"))))
    (properties `((upstream-name . "dineR")))
    (build-system r-build-system)
    (propagated-inputs (list r-progress r-matrix r-mass))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/RicSalgado/dineR")
    (synopsis "Differential Network Estimation in R")
    (description
     "An efficient and convenient set of functions to perform differential network
estimation through the use of alternating direction method of multipliers
optimization with a variety of loss functions.")
    (license license:expat)))

(define-public r-dineq
  (package
    (name "r-dineq")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dineq" version))
       (sha256
        (base32 "1xrhrdc970f7hm9xng9z7xmshnmmz89cn3gmnyabzprx44ccr9sl"))))
    (properties `((upstream-name . "dineq")))
    (build-system r-build-system)
    (propagated-inputs (list r-hmisc r-boot))
    (home-page "https://cran.r-project.org/package=dineq")
    (synopsis "Decomposition of (Income) Inequality")
    (description
     "Decomposition of (income) inequality by population sub groups.  For a
decomposition on a single variable the mean log deviation can be used (see
Mookherjee Shorrocks (1982) <DOI:10.2307/2232673>).  For a decomposition on
multiple variables a regression based technique can be used (see Fields (2003)
<DOI:10.1016/s0147-9121(03)22001-x>).  Recentered influence function regression
for marginal effects of the (income or wealth) distribution (see Firpo et al.
(2009) <DOI:10.3982/ECTA6822>).  Some extensions to inequality functions to
handle weights and/or missings.")
    (license license:gpl3)))

(define-public r-dinamic-duo
  (package
    (name "r-dinamic-duo")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiNAMIC.Duo" version))
       (sha256
        (base32 "06cgc0cfdkg5g9ybxb7nnz50vngyh2sssj3bmzsw7rmrbjvfsg8p"))))
    (properties `((upstream-name . "DiNAMIC.Duo")))
    (build-system r-build-system)
    (inputs (list python))
    (propagated-inputs (list r-plyr r-dinamic r-biomart))
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=DiNAMIC.Duo")
    (synopsis "Finding Recurrent DNA Copy Number Alterations and Differences")
    (description
     "In tumor tissue, underlying genomic instability can lead to DNA copy number
alterations, e.g., copy number gains or losses.  Sporadic copy number
alterations occur randomly throughout the genome, whereas recurrent alterations
are observed in the same genomic region across multiple independent samples,
perhaps because they provide a selective growth advantage.  Here we use cyclic
shift permutations to identify recurrent copy number alterations in a single
cohort or recurrent copy number differences in two cohorts based on a common set
of genomic markers.  Additional functionality is provided to perform downstream
analyses, including the creation of summary files and graphics.
@code{DiNAMIC.Duo} builds upon the original @code{DiNAMIC} package of Walter et
al. (2011) <doi:10.1093/bioinformatics/btq717> and leverages the theory
developed in Walter et al. (2015) <doi:10.1093/biomet/asv046>.  An article
describing @code{DiNAMIC.Duo} by Walter et al. (2022) can be found at <doi:
10.1093/bioinformatics/btac542>.")
    (license license:gpl3)))

(define-public r-dinamic
  (package
    (name "r-dinamic")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dinamic" version))
       (sha256
        (base32 "01w8fzjpvz4mwhnqhjjixy7q60hdlpqcm33i98qnighkry024ysm"))))
    (properties `((upstream-name . "dinamic")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dinamic")
    (synopsis
     "Method to Analyze Recurrent DNA Copy Number Aberrations in Tumors")
    (description
     "In tumor tissue, underlying genomic instability can lead to DNA copy number
alterations, e.g., copy number gains or losses.  Sporadic copy number
alterations occur randomly throughout the genome, whereas recurrent alterations
are observed in the same genomic region across multiple independent samples,
perhaps because they provide a selective growth advantage.  This package
implements the @code{DiNAMIC} procedure for assessing the statistical
significance of recurrent DNA copy number aberrations (Bioinformatics (2011)
27(5) 678 - 685).")
    (license license:gpl3)))

(define-public r-dina
  (package
    (name "r-dina")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dina" version))
       (sha256
        (base32 "1sq7998xc5qhvd8clc8r32ch7axinh2a2dc7i1w2p148wv130yhd"))))
    (properties `((upstream-name . "dina")))
    (build-system r-build-system)
    (propagated-inputs (list r-simcdm r-rgen r-rcpparmadillo r-rcpp))
    (home-page "https://github.com/tmsalab/dina")
    (synopsis "Bayesian Estimation of DINA Model")
    (description
     "Estimate the Deterministic Input, Noisy \"And\" Gate (DINA) cognitive diagnostic
model parameters using the Gibbs sampler described by Culpepper (2015)
<doi:10.3102/1076998615595403>.")
    (license license:gpl2+)))

(define-public r-dimora
  (package
    (name "r-dimora")
    (version "0.3.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIMORA" version))
       (sha256
        (base32 "1qdi3nvr4p31kdfqs43xlfcryni182imp67bf03dma3pfnqxgwqj"))))
    (properties `((upstream-name . "DIMORA")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2 r-numderiv r-minpack-lm r-forecast
                             r-desolve))
    (home-page "https://cran.r-project.org/package=DIMORA")
    (synopsis "Diffusion Models R Analysis")
    (description
     "The implemented methods are: Standard Bass model, Generalized Bass model (with
rectangular shock, exponential shock, and mixed shock.  You can choose to add
from 1 to 3 shocks), Guseo-Guidolin model and Variable Potential Market model,
and UCRCD model.  The Bass model consists of a simple differential equation that
describes the process of how new products get adopted in a population, the
Generalized Bass model is a generalization of the Bass model in which there is a
\"carrier\" function x(t) that allows to change the speed of time sliding.  In
some real processes the reachable potential of the resource available in a
temporal instant may appear to be not constant over time, because of this we use
Variable Potential Market model, in which the Guseo-Guidolin has a particular
specification for the market function.  The UCRCD model (Unbalanced Competition
and Regime Change Diachronic) is a diffusion model used to capture the dynamics
of the competitive or collaborative transition.")
    (license license:gpl3+)))

(define-public r-dimodelsvis
  (package
    (name "r-dimodelsvis")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DImodelsVis" version))
       (sha256
        (base32 "1j224j3xj1scf1smy2zk0dwv3calkx3jzpn989w9hjck96x657n5"))))
    (properties `((upstream-name . "DImodelsVis")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-scales
                             r-rlang
                             r-plotwidgets
                             r-pieglyph
                             r-metr
                             r-insight
                             r-glue
                             r-ggtext
                             r-ggplot2
                             r-ggfortify
                             r-forcats
                             r-dplyr
                             r-dimodels
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://rishvish.github.io/DImodelsVis/")
    (synopsis
     "Visualising and Interpreting Statistical Models Fit to Compositional Data")
    (description
     "Statistical models fit to compositional data are often difficult to interpret
due to the sum to 1 constraint on data variables.  D@code{ImodelsVis} provides
novel visualisations tools to aid with the interpretation of models fit to
compositional data.  All visualisations in the package are created using the
ggplot2 plotting framework and can be extended like every other ggplot object.")
    (license license:gpl3+)))

(define-public r-dimodelsmulti
  (package
    (name "r-dimodelsmulti")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DImodelsMulti" version))
       (sha256
        (base32 "1av5kfvshy05xqipp4qa5fhj4yd55wfpznx91l2fgdklxbnjr0v4"))))
    (properties `((upstream-name . "DImodelsMulti")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2
                             r-plyr
                             r-nlme
                             r-matrix
                             r-knitr
                             r-dplyr
                             r-dimodels))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://dimodels.com")
    (synopsis
     "Fit Multivariate Diversity-Interactions Models with Repeated Measures")
    (description
     "An add-on package to DImodels for the fitting of biodiversity and ecosystem
function relationship study data with multiple ecosystem function responses
and/or time points.  This package uses the multivariate and repeated measures
Diversity-Interactions (DI) methods developed by Kirwan et al. (2009)
<doi:10.1890/08-1684.1>, Finn et al. (2013) <doi:10.1111/1365-2664.12041>, and
Dooley et al. (2015) <doi:10.1111/ele.12504>.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-dimodels
  (package
    (name "r-dimodels")
    (version "1.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DImodels" version))
       (sha256
        (base32 "1ykdjqbli32awx6fwyff0l522dclhfyjp83svsjrfnm0517rlg4w"))))
    (properties `((upstream-name . "DImodels")))
    (build-system r-build-system)
    (propagated-inputs (list r-rootsolve r-multcomp r-hnp r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DImodels")
    (synopsis "Diversity-Interactions (DI) Models")
    (description
     "The DImodels package is suitable for analysing data from biodiversity and
ecosystem function studies using the Diversity-Interactions (DI) modelling
approach introduced by Kirwan et al. (2009) <doi:10.1890/08-1684.1>.  Suitable
data will contain proportions for each species and a community-level response
variable, and may also include additional factors, such as blocks or treatments.
 The package can perform data manipulation tasks, such as computing pairwise
interactions (the DI_data() function), can perform an automated model selection
process (the @code{autoDI}() function) and has the flexibility to fit a wide
range of user-defined DI models (the DI() function).")
    (license license:gpl2+)))

(define-public r-dimensionsr
  (package
    (name "r-dimensionsr")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dimensionsR" version))
       (sha256
        (base32 "1bic5ynqapz4mh3bcv58r00ip5s04mc8n58yhlkbrnbcqyqaca4f"))))
    (properties `((upstream-name . "dimensionsR")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/massimoaria/dimensionsR")
    (synopsis
     "Gathering Bibliographic Records from 'Digital Science Dimensions' Using 'DSL' API")
    (description
     "This package provides a set of tools to extract bibliographic content from
Digital Science Dimensions using DSL API
<https://www.dimensions.ai/dimensions-apis/>.")
    (license license:gpl3)))

(define-public r-dimensio
  (package
    (name "r-dimensio")
    (version "0.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dimensio" version))
       (sha256
        (base32 "1vdmd2lzmj246jaamkxda2w899yxrzhbj7mk01rzd8zysqjdkbj9"))))
    (properties `((upstream-name . "dimensio")))
    (build-system r-build-system)
    (propagated-inputs (list r-khroma r-arkhe))
    (native-inputs (list r-knitr))
    (home-page "https://packages.tesselle.org/dimensio/")
    (synopsis "Multivariate Data Analysis")
    (description
     "Simple Principal Components Analysis (PCA) and (Multiple) Correspondence
Analysis (CA) based on the Singular Value Decomposition (SVD).  This package
provides S4 classes and methods to compute, extract, summarize and visualize
results of multivariate data analysis.  It also includes methods for partial
bootstrap validation described in Greenacre (1984, ISBN: 978-0-12-299050-2) and
Lebart et al. (2006, ISBN: 978-2-10-049616-7).")
    (license license:gpl3+)))

(define-public r-dime
  (package
    (name "r-dime")
    (version "1.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIME" version))
       (sha256
        (base32 "1kbs5s3pgjlqiikcd54v9ym9yw40q6x1bgl7k0570l7i3mvcfvsj"))))
    (properties `((upstream-name . "DIME")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DIME")
    (synopsis "Differential Identification using Mixture Ensemble")
    (description
     "This package provides a robust identification of differential binding sites
method for analyzing @code{ChIP-seq} (Chromatin Immunoprecipitation Sequencing)
comparing two samples that considers an ensemble of finite mixture models
combined with a local false discovery rate (fdr) allowing for flexible modeling
of data.  Methods for Differential Identification using Mixture Ensemble (DIME)
is described in: Taslim et al., (2011) <doi:10.1093/bioinformatics/btr165>.")
    (license license:gpl2+)))

(define-public r-dilp
  (package
    (name "r-dilp")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dilp" version))
       (sha256
        (base32 "0pvd7xsg9g772n6m8h88rigkmnivmqrqj33ar1y2iq2z3k4r93jz"))))
    (properties `((upstream-name . "dilp")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-tidyr
                             r-stringr
                             r-rlang
                             r-magrittr
                             r-ggrepel
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mjbutrim/dilp")
    (synopsis
     "Reconstruct Paleoclimate and Paleoecology with Leaf Physiognomy")
    (description
     "Use leaf physiognomic methods to reconstruct mean annual temperature (MAT), mean
annual precipitation (MAP), and leaf dry mass per area (Ma), along with other
useful quantitative leaf traits.  Methods in this package described in Lowe et
al. (in review).")
    (license license:gpl3+)))

(define-public r-digss
  (package
    (name "r-digss")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIGSS" version))
       (sha256
        (base32 "1bbwkq40gdan1zwq3cwn96k0k045x67l11rhm3q4dppw50736fpk"))))
    (properties `((upstream-name . "DIGSS")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/markhubbe/DIGSS")
    (synopsis
     "Determination of Intervals Using Georeferenced Survey Simulation")
    (description
     "Simulation tool to estimate the rate of success that surveys possessing
user-specific characteristics have in identifying archaeological sites (or any
groups of clouds of objects), given specific parameters of survey area, survey
methods, and site properties.  The survey approach used is largely based on the
work of Kintigh (1988) <doi:10.2307/281113>.")
    (license license:expat)))

(define-public r-digittests
  (package
    (name "r-digittests")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "digitTests" version))
       (sha256
        (base32 "0giz0zr8rcvfv36qmqy6fpamjcansrq4bs3znnq0g97iprj0x3i5"))))
    (properties `((upstream-name . "digitTests")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://koenderks.github.io/digitTests/")
    (synopsis "Tests for Detecting Irregular Digit Patterns")
    (description
     "This package provides statistical tests and support functions for detecting
irregular digit patterns in numerical data.  The package includes tools for
extracting digits at various locations in a number, tests for repeated values,
and (Bayesian) tests of digit distributions.")
    (license license:gpl3+)))

(define-public r-digitize
  (package
    (name "r-digitize")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "digitize" version))
       (sha256
        (base32 "1qw4x4z9vrs79sd9b2daw668nc6nvjl4qhayfqmd87yxa2ydv6x0"))))
    (properties `((upstream-name . "digitize")))
    (build-system r-build-system)
    (propagated-inputs (list r-readbitmap))
    (home-page "https://github.com/tpoisot/digitize/")
    (synopsis "Use Data from Published Plots in R")
    (description
     "Import data from a digital image; it requires user input for calibration and to
locate the data points.  The end result is similar to @code{DataThief} and other
other programs that digitize published plots or graphs.")
    (license license:gpl2+)))

(define-public r-digitalpcr
  (package
    (name "r-digitalpcr")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "digitalPCR" version))
       (sha256
        (base32 "0hwqq84yr1hnvf4bygc5425887dhqjjjyy1ils71iavcal04s8pb"))))
    (properties `((upstream-name . "digitalPCR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=digitalPCR")
    (synopsis "Estimate Copy Number for Digital PCR")
    (description
     "The assay sensitivity is the minimum number of copies that the digital PCR assay
can detect.  Users provide serial dilution results in the format of counts of
positive and total reaction wells.  The output is the estimated assay
sensitivity and the copy number per well in the initial dilute.")
    (license license:gpl2)))

(define-public r-digirhythm
  (package
    (name "r-digirhythm")
    (version "2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "digiRhythm" version))
       (sha256
        (base32 "1z8arjp4pk8iq7jwigyh7bxfd33dhdxc9blmy1j8kssml152ilhn"))))
    (properties `((upstream-name . "digiRhythm")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-xts
                             r-tidyr
                             r-stringr
                             r-readr
                             r-pracma
                             r-magrittr
                             r-lubridate
                             r-ggplot2
                             r-dplyr
                             r-crayon))
    (native-inputs (list r-knitr))
    (home-page "https://nasserdr.github.io/digiRhythm/")
    (synopsis "Analyzing Animal's Rhythmicity")
    (description
     "Analyze and visualize the rhythmic behavior of animals using the degree of
functional coupling (See Scheibe (1999) <doi:10.1076/brhm.30.2.216.1420>),
compute and visualize harmonic power, actograms, average activity and diurnality
index.")
    (license license:gpl3)))

(define-public r-diftree
  (package
    (name "r-diftree")
    (version "3.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIFtree" version))
       (sha256
        (base32 "1ps3nb1a5dgxs187bcjsys4fpi0z4z6d84qlxg8rf1rvcfgg21r5"))))
    (properties `((upstream-name . "DIFtree")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam r-plotrix r-penalized r-gridbase))
    (home-page "https://cran.r-project.org/package=DIFtree")
    (synopsis
     "Item Focussed Trees for the Identification of Items in Differential Item Functioning")
    (description
     "Item focussed recursive partitioning for simultaneous selection of items and
variables that induce Differential Item Functioning (DIF) in dichotomous or
polytomous items.")
    (license license:gpl2)))

(define-public r-difshiny
  (package
    (name "r-difshiny")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIFshiny" version))
       (sha256
        (base32 "0lb98dj2kidfv8zqs1rdkj7b6gf6i4d2s904bwsbyg7w03jxm86f"))))
    (properties `((upstream-name . "DIFshiny")))
    (build-system r-build-system)
    (propagated-inputs (list r-shinydashboard r-shiny r-readxl r-difr))
    (home-page "https://cran.r-project.org/package=DIFshiny")
    (synopsis "Differential Item Functioning via Shiny Application")
    (description
     "Differential Item Functioning (DIF) Analysis with shiny application interfaces.
You can run the functions in this package without any arguments and perform your
DIF analysis using user-friendly interfaces.")
    (license license:gpl2)))

(define-public r-difr
  (package
    (name "r-difr")
    (version "5.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "difR" version))
       (sha256
        (base32 "1cd5kaal5mjrbj1l9ki2wbqasdxphgc2yhaf4xwgbh1nr2zkhr02"))))
    (properties `((upstream-name . "difR")))
    (build-system r-build-system)
    (propagated-inputs (list r-mirt r-ltm r-lme4 r-deltaplotr))
    (home-page "https://cran.r-project.org/package=difR")
    (synopsis
     "Collection of Methods to Detect Dichotomous Differential Item Functioning (DIF)")
    (description
     "This package provides a collection of standard methods to detect differential
item functioning among dichotomously scored items.  Methods for uniform and
non-uniform DIF, based on test-score or IRT methods, for comparing two or more
than two groups of respondents, are available (Magis, Beland, Tuerlinckx and De
Boeck,A General Framework and an R Package for the Detection of Dichotomous
Differential Item Functioning, Behavior Research Methods, 42, 2010, 847-862
<doi:10.3758/BRM.42.3.847>).")
    (license license:gpl2+)))

(define-public r-difplus
  (package
    (name "r-difplus")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIFplus" version))
       (sha256
        (base32 "1k03lr437gx5y762z3h40hz9kcl4m8xgrndxvbyvsgmn2h6pbwsd"))))
    (properties `((upstream-name . "DIFplus")))
    (build-system r-build-system)
    (propagated-inputs (list r-testdataimputation r-plyr))
    (home-page "https://cran.r-project.org/package=DIFplus")
    (synopsis
     "Multilevel Mantel-Haenszel Statistics for Differential Item Functioning Detection")
    (description
     "Clustered or multilevel data structures are common in the assessment of
differential item functioning (DIF), particularly in the context of large-scale
assessment programs.  This package allows users to implement extensions of the
Mantel-Haenszel DIF detection procedures in the presence of multilevel data
based on the work of Begg (1999) <doi:10.1111/j.0006-341X.1999.00302.x>, Begg &
Paykin (2001) <doi:10.1080/00949650108812115>, and French & Finch (2013)
<doi:10.1177/0013164412472341>.")
    (license license:gpl2+)))

(define-public r-difnlr
  (package
    (name "r-difnlr")
    (version "1.4.2-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "difNLR" version))
       (sha256
        (base32 "1wrvsjbvvqwpv7cwc445n7l4ly8gvj8hyd66k02ib8r5854zn192"))))
    (properties `((upstream-name . "difNLR")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam
                             r-plyr
                             r-nnet
                             r-msm
                             r-ggplot2
                             r-calculus))
    (home-page "https://cran.r-project.org/package=difNLR")
    (synopsis "DIF and DDF Detection by Non-Linear Regression Models")
    (description
     "Detection of differential item functioning (DIF) among dichotomously scored
items and differential distractor functioning (DDF) among unscored items with
non-linear regression procedures based on generalized logistic regression models
(Hladka & Martinkova, 2020, <doi:10.32614/RJ-2020-014>).")
    (license license:gpl3)))

(define-public r-difm
  (package
    (name "r-difm")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIFM" version))
       (sha256
        (base32 "126yn0kj6znpigxg7hsmpn67149mgl1nzv6zp772cwd8pdwpyklw"))))
    (properties `((upstream-name . "DIFM")))
    (build-system r-build-system)
    (propagated-inputs (list r-spdep
                             r-sp
                             r-rcpparmadillo
                             r-rcpp
                             r-matrix
                             r-laplacesdemon
                             r-gridextra))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DIFM")
    (synopsis "Dynamic ICAR Spatiotemporal Factor Models")
    (description
     "Bayesian factor models are effective tools for dimension reduction.  This is
especially applicable to multivariate large-scale datasets.  It allows
researchers to understand the latent factors of the data which are the linear or
non-linear combination of the variables.  Dynamic Intrinsic Conditional
Autocorrelative Priors (ICAR) Spatiotemporal Factor Models DIFM package provides
function to run Markov Chain Monte Carlo (MCMC), evaluation methods and visual
plots from Shin and Ferreira (2023)<doi:10.1016/j.spasta.2023.100763>.  Our
method is a class of Bayesian factor model which can account for spatial and
temporal correlations.  By incorporating these correlations, the model can
capture specific behaviors and provide predictions.")
    (license license:gpl2+)))

(define-public r-diflasso
  (package
    (name "r-diflasso")
    (version "1.0-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIFlasso" version))
       (sha256
        (base32 "13ls5018l790cdr26431li4gi9zw03ilypszfqglg4hj485h7dyw"))))
    (properties `((upstream-name . "DIFlasso")))
    (build-system r-build-system)
    (propagated-inputs (list r-penalized r-misctools r-grplasso))
    (home-page "https://cran.r-project.org/package=DIFlasso")
    (synopsis
     "Penalty Approach to Differential Item Functioning in Rasch Models")
    (description
     "This package performs DIFlasso as proposed by Tutz and Schauberger (2015)
<doi:10.1007/s11336-013-9377-6>, a method to detect DIF (Differential Item
Functioning) in Rasch Models.  It can handle settings with many variables and
also metric variables.")
    (license license:gpl2)))

(define-public r-diffxtables
  (package
    (name "r-diffxtables")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiffXTables" version))
       (sha256
        (base32 "0a0q1fz80jlcrk4rw70yjb8djxgsm5axih45vi4dqpg6n8xlrzw2"))))
    (properties `((upstream-name . "DiffXTables")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-pander))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DiffXTables")
    (synopsis "Pattern Analysis Across Contingency Tables")
    (description
     "Statistical hypothesis testing of pattern heterogeneity via differences in
underlying distributions across multiple contingency tables.  Five tests are
included: the comparative chi-squared test (Song et al.  2014)
<doi:10.1093/nar/gku086> (Zhang et al.  2015) <doi:10.1093/nar/gkv358>, the
Sharma-Song test (Sharma et al.  2021) <doi:10.1093/bioinformatics/btab240>, the
heterogeneity test, the marginal-change test (Sharma et al.  2020)
<doi:10.1145/3388440.3412485>, and the strength test (Sharma et al.  2020)
<doi:10.1145/3388440.3412485>.  Under the null hypothesis that row and column
variables are statistically independent and joint distributions are equal, their
test statistics all follow an asymptotically chi-squared distribution.  A
comprehensive type analysis categorizes the relation among the contingency
tables into type null, 0, 1, and 2 (Sharma et al.  2020)
<doi:10.1145/3388440.3412485>.  They can identify heterogeneous patterns that
differ in either the first order (marginal) or the second order (differential
departure from independence).  Second-order differences reveal more fundamental
changes than first-order differences across heterogeneous patterns.")
    (license license:lgpl3+)))

(define-public r-diffviewer
  (package
    (name "r-diffviewer")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diffviewer" version))
       (sha256
        (base32 "1rwcqmc9h7ggxfkc57wklz5vqqanlr0mff7f2613gkh9pci5nadg"))))
    (properties `((upstream-name . "diffviewer")))
    (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-htmlwidgets))
    (native-inputs (list esbuild))
    (home-page "https://diffviewer.r-lib.org")
    (synopsis "HTML Widget to Show File Differences")
    (description
     "This package provides a HTML widget that shows differences between files (text,
images, and data frames).")
    (license license:expat)))

(define-public r-diffval
  (package
    (name "r-diffval")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diffval" version))
       (sha256
        (base32 "1qhbby9zfckkkxbpvbnym3i1pfapgrjf0m61fly9v7k50j07d4cd"))))
    (properties `((upstream-name . "diffval")))
    (build-system r-build-system)
    (home-page "https://gitlab.com/point-veg/diffval")
    (synopsis "Vegetation Patterns")
    (description
     "Find, visualize and explore patterns of differential taxa in vegetation data
(namely in a phytosociological table), using the Differential Value
(@code{DiffVal}).  Patterns are searched through mathematical optimization
algorithms.  Ultimately, Total Differential Value (TDV) optimization aims at
obtaining classifications of vegetation data based on differential taxa, as in
the traditional geobotanical approach.  The Gurobi optimizer, as well as the R
package gurobi', can be installed from
<https://www.gurobi.com/products/gurobi-optimizer/>.  The useful vignette Gurobi
Installation Guide, from package prioritizr', can be found here:
<https://prioritizr.net/articles/gurobi_installation_guide.html>.")
    (license license:gpl3+)))

(define-public r-diffusion
  (package
    (name "r-diffusion")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diffusion" version))
       (sha256
        (base32 "1bgswz2ichzgdb3ckw0sgxkqv3pf1lpzkjb3ly389ln03q0iwnwq"))))
    (properties `((upstream-name . "diffusion")))
    (build-system r-build-system)
    (propagated-inputs (list r-systemfit r-optimx r-nloptr))
    (home-page "https://github.com/mamut86/diffusion")
    (synopsis "Forecast the Diffusion of New Products")
    (description
     "Various diffusion models to forecast new product growth.  Currently the package
contains Bass, Gompertz, Gamma/Shifted Gompertz and Weibull curves.  See Meade
and Islam (2006) <doi:10.1016/j.ijforecast.2006.01.005>.")
    (license license:lgpl2.1)))

(define-public r-diffudist
  (package
    (name "r-diffudist")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diffudist" version))
       (sha256
        (base32 "0s8k949l7fvdy0c1zlrk4zr5dnxksq67spwg8mpdsyc2xchh7b5c"))))
    (properties `((upstream-name . "diffudist")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis
                             r-rlang
                             r-reshape2
                             r-rcppeigen
                             r-rcpp
                             r-rcolorbrewer
                             r-matrix
                             r-igraph
                             r-ggplot2
                             r-ggdendro
                             r-expm))
    (native-inputs (list r-knitr))
    (home-page "https://gbertagnolli.github.io/diffudist/")
    (synopsis "Diffusion Distance for Complex Networks")
    (description
     "Enables the evaluation of diffusion distances for complex single-layer networks.
 Given a network one can define different types of Laplacian (or transition)
matrices corresponding to different continuous-time random walks dynamics on the
network.  This package enables the evaluation of Laplacians, stochastic
matrices, and the corresponding diffusion distance matrices.  The metric
structure induced by the network-driven process is richer and more robust than
the one given by shortest-paths and allows to study the geometry induced by
different types of diffusion-like communication mechanisms taking place on
complex networks.  For more details see: De Domenico, M. (2017)
<doi:10.1103/physrevlett.118.168301> and Bertagnolli, G. and De Domenico, M.
(2021) <doi:10.1103/@code{PhysRevE.103.042301>}.")
    (license license:gpl2+)))

(define-public r-diffr
  (package
    (name "r-diffr")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diffr" version))
       (sha256
        (base32 "0ydwnpyzirynffsnvip667y0jqzy7yfqlfpqhb38xvmd9rmwfbp8"))))
    (properties `((upstream-name . "diffr")))
    (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-htmlwidgets))
    (native-inputs (list esbuild))
    (home-page "https://cran.r-project.org/package=diffr")
    (synopsis "Display Differences Between Two Files using Codediff Library")
    (description
     "An R interface to the codediff @code{JavaScript} library (a copy of which is
included in the package, see <https://github.com/danvk/codediff.js> for
information).  Allows for visualization of the difference between 2 files,
usually text files or R scripts, in a browser.")
    (license license:gpl2)))

(define-public r-diffpriv
  (package
    (name "r-diffpriv")
    (version "0.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diffpriv" version))
       (sha256
        (base32 "12q2v93369bshid83rsy1csbr9ay6rfpd8zdxm12zi7py3f9sjs8"))))
    (properties `((upstream-name . "diffpriv")))
    (build-system r-build-system)
    (propagated-inputs (list r-gsl))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/brubinstein/diffpriv")
    (synopsis "Easy Differential Privacy")
    (description
     "An implementation of major general-purpose mechanisms for privatizing
statistics, models, and machine learners, within the framework of differential
privacy of Dwork et al. (2006) <doi:10.1007/11681878_14>.  Example mechanisms
include the Laplace mechanism for releasing numeric aggregates, and the
exponential mechanism for releasing set elements.  A sensitivity sampler
(Rubinstein & Alda, 2017) <@code{arXiv:1706.02562>} permits sampling target
non-private function sensitivity; combined with the generic mechanisms, it
permits turn-key privatization of arbitrary programs.")
    (license license:expat)))

(define-public r-diffnet
  (package
    (name "r-diffnet")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiffNet" version))
       (sha256
        (base32 "1hil8p896vckgwmlr8vqkrwswclwh1hs8gxvk648gpahi1na1ssc"))))
    (properties `((upstream-name . "DiffNet")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-igraph r-assertthat))
    (home-page "https://cran.r-project.org/package=DiffNet")
    (synopsis
     "Identifying Significant Node Scores using Network Diffusion Algorithm")
    (description
     "Designed for network analysis, leveraging the personalized @code{PageRank}
algorithm to calculate node scores in a given graph.  This innovative approach
allows users to uncover the importance of nodes based on a customized
perspective, making it particularly useful in fields like bioinformatics, social
network analysis, and more.")
    (license license:gpl3+)))

(define-public r-diffmatchpatch
  (package
    (name "r-diffmatchpatch")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diffmatchpatch" version))
       (sha256
        (base32 "064p2xzv0x890pw24lm9fmafp0x93f3yv77ms2zabzlclfylzzb7"))))
    (properties `((upstream-name . "diffmatchpatch")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-cli))
    (home-page "https://github.com/rundel/diffmatchpatch")
    (synopsis "String Diff, Match, and Patch Utilities")
    (description
     "This package provides a wrapper for Google's diff-match-patch library.  It
provides basic tools for computing diffs, finding fuzzy matches, and
constructing / applying patches to strings.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-diffirt
  (package
    (name "r-diffirt")
    (version "1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diffIRT" version))
       (sha256
        (base32 "0kip6wz9l9q80qsqwf32pwz7d9vqin6dgfwf0nxlrlzf8xjsxgim"))))
    (properties `((upstream-name . "diffIRT")))
    (build-system r-build-system)
    (propagated-inputs (list r-statmod))
    (home-page "https://cran.r-project.org/package=diffIRT")
    (synopsis "Diffusion IRT Models for Response and Response Time Data")
    (description
     "Package to fit diffusion-based IRT models to response and response time data.
Models are fit using marginal maximum likelihood.  Parameter restrictions (fixed
value and equality constraints) are possible.  In addition, factor scores
(person drift rate and person boundary separation) can be estimated.  Model fit
assessment tools are also available.  The traditional diffusion model can be
estimated as well.")
    (license license:gpl2)))

(define-public r-differentes
  (package
    (name "r-differentes")
    (version "0.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diffeRenTES" version))
       (sha256
        (base32 "1904zg9ynf873cqkww2ii4k60cr1bi9km67dxvgsc2bd8dxkm9ks"))))
    (properties `((upstream-name . "diffeRenTES")))
    (build-system r-build-system)
    (propagated-inputs (list r-igraph r-dot r-boolnet))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=diffeRenTES")
    (synopsis "Computation of TES-Based Cell Differentiation Trees")
    (description
     "Computes the ATM (Attractor Transition Matrix) structure and the tree-like
structure describing the cell differentiation process (based on the Threshold
Ergodic Set concept introduced by Serra and Villani), starting from the Boolean
networks with synchronous updating scheme of the @code{BoolNet} R package.  TESs
(Threshold Ergodic Sets) are the mathematical abstractions that represent the
different cell types arising during ontogenesis.  TESs and the powerful model of
biological differentiation based on Boolean networks to which it belongs have
been firstly described in \"A Dynamical Model of Genetic Networks for Cell
Differentiation\" Villani M, Barbieri A, Serra R (2011) A Dynamical Model of
Genetic Networks for Cell Differentiation.  PLOS ONE 6(3): e17703.")
    (license license:gpl3)))

(define-public r-differ
  (package
    (name "r-differ")
    (version "0.0-8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diffeR" version))
       (sha256
        (base32 "0l2pm4kh6yq3h3v27a5r28c0724g89pglaxd14f14cdxk51hznqx"))))
    (properties `((upstream-name . "diffeR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-terra
                             r-rlang
                             r-raster
                             r-ggplot2))
    (home-page "https://github.com/amsantac/diffeR")
    (synopsis
     "Metrics of Difference for Comparing Pairs of Maps or Pairs of Variables")
    (description
     "Metrics of difference for comparing pairs of variables or pairs of maps
representing real or categorical variables at original and multiple resolutions.")
    (license license:gpl2+)))

(define-public r-diffeqr
  (package
    (name "r-diffeqr")
    (version "2.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diffeqr" version))
       (sha256
        (base32 "116j5iivp1rp0aql74mbvbp9j9q86rh49iamfbi46jx0yfh87256"))))
    (properties `((upstream-name . "diffeqr")))
    (build-system r-build-system)
    (inputs (list julia))
    (propagated-inputs (list r-juliacall))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/SciML/diffeqr")
    (synopsis "Solving Differential Equations (ODEs, SDEs, DDEs, DAEs)")
    (description
     "An interface to @code{DifferentialEquations.jl} <https://diffeq.sciml.ai/dev/>
from the R programming language.  It has unique high performance methods for
solving ordinary differential equations (ODE), stochastic differential equations
(SDE), delay differential equations (DDE), differential-algebraic equations
(DAE), and more.  Much of the functionality, including features like adaptive
time stepping in SDEs, are unique and allow for multiple orders of magnitude
speedup over more common methods.  Supports GPUs, with support for CUDA
(NVIDIA), AMD GPUs, Intel @code{oneAPI} GPUs, and Apple's Metal (M-series chip
GPUs).  diffeqr attaches an R interface onto the package, allowing seamless use
of this tooling by R users.  For more information, see Rackauckas and Nie (2017)
<doi:10.5334/jors.151>.")
    (license license:expat)))

(define-public r-diffenrich
  (package
    (name "r-diffenrich")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diffEnrich" version))
       (sha256
        (base32 "0fa0v24ir8an82mx38489zavqfya3130q9z52dmm62lnf7pvkvzl"))))
    (properties `((upstream-name . "diffEnrich")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-rlang
                             r-reshape2
                             r-here
                             r-ggplot2
                             r-ggnewscale
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/SabaLab/diffEnrich")
    (synopsis
     "Given a List of Gene Symbols, Performs Differential Enrichment Analysis")
    (description
     "Compare functional enrichment between two experimentally-derived groups of genes
or proteins (Peterson, DR., et al.(2018)) <doi: 10.1371/journal.pone.0198139>.
Given a list of gene symbols, @code{diffEnrich} will perform differential
enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG)
REST API. This package provides a number of functions that are intended to be
used in a pipeline.  Briefly, the user provides a KEGG formatted species id for
either human, mouse or rat, and the package will download and clean species
specific ENTREZ gene IDs and map them to their respective KEGG pathways by
accessing KEGG's REST API. KEGG's API is used to guarantee the most up-to-date
pathway data from KEGG. Next, the user will identify significantly enriched
pathways from two gene sets, and finally, the user will identify pathways that
are differentially enriched between the two gene sets.  In addition to the
analysis pipeline, this package also provides a plotting function.")
    (license license:gpl2)))

(define-public r-diffee
  (package
    (name "r-diffee")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diffee" version))
       (sha256
        (base32 "01lb1prz70mxgymhhsvx48kbfy69xyyaabsmfhf28af9wfb89662"))))
    (properties `((upstream-name . "diffee")))
    (build-system r-build-system)
    (propagated-inputs (list r-pcapp r-igraph))
    (home-page "https://github.com/QData/DIFFEE")
    (synopsis
     "Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure")
    (description
     "This is an R implementation of Fast and Scalable Learning of Sparse Changes in
High-Dimensional Gaussian Graphical Model Structure (DIFFEE).  The DIFFEE
algorithm can be used to fast estimate the differential network between two
related datasets.  For instance, it can identify differential gene network from
datasets of case and control.  By performing data-driven network inference from
two high-dimensional data sets, this tool can help users effectively translate
two aggregated data blocks into knowledge of the changes among entities between
two Gaussian Graphical Model.  Please run demo(@code{diffeeDemo}) to learn the
basic functions provided by this package.  For further details, please read the
original paper: Beilun Wang, Arshdeep Sekhon, Yanjun Qi (2018)
<@code{arXiv:1710.11223>}.")
    (license license:gpl2)))

(define-public r-diffdfs
  (package
    (name "r-diffdfs")
    (version "0.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diffdfs" version))
       (sha256
        (base32 "1b61wx9fy7a4rb6jh1cvayf1w1far74pgcliqyk9pzn06nlqylfj"))))
    (properties `((upstream-name . "diffdfs")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-janitor r-dplyr r-arrow))
    (home-page "https://cran.r-project.org/package=diffdfs")
    (synopsis "Compute the Difference Between Data Frames")
    (description
     "Shows you which rows have changed between two data frames with the same column
structure.  Useful for diffing slowly mutating data.")
    (license license:expat)))

(define-public r-diffdf
  (package
    (name "r-diffdf")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diffdf" version))
       (sha256
        (base32 "0i9wq31cshxcmg61p610s2r4phi43bxmffbzh74yp9y4f1difil0"))))
    (properties `((upstream-name . "diffdf")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://gowerc.github.io/diffdf/")
    (synopsis "Dataframe Difference Tool")
    (description
     "This package provides functions for comparing two data.frames against each
other.  The core functionality is to provide a detailed breakdown of any
differences between two data.frames as well as providing utility functions to
help narrow down the source of problems and differences.")
    (license license:expat)))

(define-public r-diffcorr
  (package
    (name "r-diffcorr")
    (version "0.4.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiffCorr" version))
       (sha256
        (base32 "05rvyfgr9f5x0dcgwcsvnpcmgmg5hcsgyxspjzxkmbyfk8wzwaf7"))))
    (properties `((upstream-name . "DiffCorr")))
    (build-system r-build-system)
    (propagated-inputs (list r-pcamethods r-multtest r-igraph r-fdrtool))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DiffCorr")
    (synopsis
     "Analyzing and Visualizing Differential Correlation Networks in Biological Data")
    (description
     "This package provides a method for identifying pattern changes between 2
experimental conditions in correlation networks (e.g., gene co-expression
networks), which builds on a commonly used association measure, such as
Pearson's correlation coefficient.  This package includes functions to calculate
correlation matrices for high-dimensional dataset and to test differential
correlation, which means the changes in the correlation relationship among
variables (e.g., genes and metabolites) between 2 experimental conditions.")
    (license (license:fsdg-compatible "GPL (> 3)"))))

(define-public r-diffcor
  (package
    (name "r-diffcor")
    (version "0.8.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diffcor" version))
       (sha256
        (base32 "1dg0qdhnf33mn3853c23jlbd4d10aa7qhmqhpffhz91fcy3rivkn"))))
    (properties `((upstream-name . "diffcor")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=diffcor")
    (synopsis "Fisher's z-Tests Concerning Differences Between Correlations")
    (description
     "Computations of Fisher's z-tests concerning different kinds of correlation
differences.  The diffpwr family entails approaches to estimating statistical
power via Monte Carlo simulations.  Important to note, the Pearson correlation
coefficient is sensitive to linear association, but also to a host of
statistical issues such as univariate and bivariate outliers, range
restrictions, and heteroscedasticity (e.g., Duncan & Layard, 1973
<doi:10.1093/BIOMET/60.3.551>; Wilcox, 2013 <doi:10.1016/C2010-0-67044-1>).
Thus, every power analysis requires that specific statistical prerequisites are
fulfilled and can be invalid if the prerequisites do not hold.  To this end, the
bootcor family provides bootstrapping confidence intervals for the incorporated
correlation difference tests.")
    (license license:gpl2+)))

(define-public r-difconet
  (package
    (name "r-difconet")
    (version "1.0-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "difconet" version))
       (sha256
        (base32 "0cjadi4mnpfmy18vyp0dw55mnhs0zddf51w59gvq6gszk145z3bq"))))
    (properties `((upstream-name . "difconet")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-mvtnorm r-gplots r-data-table))
    (home-page "http://bioinformatica.mty.itesm.mx/difconet")
    (synopsis "Differential Coexpressed Networks")
    (description
     "Estimation of DIFferential COexpressed NETworks using diverse and user metrics.
This package is basically used for three functions related to the estimation of
differential coexpression.  First, to estimate differential coexpression where
the coexpression is estimated, by default, by Spearman correlation.  For this, a
metric to compare two correlation distributions is needed.  The package includes
6 metrics.  Some of them needs a threshold.  A new metric can also be specified
as a user function with specific parameters (see difconet.run).  The
significance is be estimated by permutations.  Second, to generate datasets with
controlled differential correlation data.  This is done by either adding noise,
or adding specific correlation structure.  Third, to show the results of
differential correlation analyses.  Please see
<http://bioinformatica.mty.itesm.mx/difconet> for further information.")
    (license license:gpl2+)))

(define-public r-difboost
  (package
    (name "r-difboost")
    (version "0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIFboost" version))
       (sha256
        (base32 "07x31ccy2l0drv1356g1v4jw71i7zqb3d0v856gsd3kpqhclpvx0"))))
    (properties `((upstream-name . "DIFboost")))
    (build-system r-build-system)
    (propagated-inputs (list r-stabs r-penalized r-mboost))
    (home-page "https://cran.r-project.org/package=DIFboost")
    (synopsis
     "Detection of Differential Item Functioning (DIF) in Rasch Models by Boosting Techniques")
    (description
     "This package performs detection of Differential Item Functioning using the
method DIFboost as proposed by Schauberger and Tutz (2016)
<doi:10.1111/bmsp.12060>.")
    (license license:gpl2)))

(define-public r-diezeit
  (package
    (name "r-diezeit")
    (version "0.1-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diezeit" version))
       (sha256
        (base32 "0rq1k08byvqn99wpql7drnrcxlzcqrcxixh7bczbc8dv1hhsgk9i"))))
    (properties `((upstream-name . "diezeit")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr r-brew))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=diezeit")
    (synopsis "R Interface to the ZEIT ONLINE Content API")
    (description
     "This package provides a wrapper for the ZEIT ONLINE Content API, available at
<http://developer.zeit.de>.  diezeit gives access to articles and corresponding
metadata from the ZEIT archive and from ZEIT ONLINE. A personal API key is
required for usage.")
    (license license:expat)))

(define-public r-dietr
  (package
    (name "r-dietr")
    (version "1.1.5-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dietr" version))
       (sha256
        (base32 "10b290iccx5wa3krjssy29j4p2wz0qkks0a8ih4mhxnry554xjb7"))))
    (properties `((upstream-name . "dietr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfishbase))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/sborstein/dietr")
    (synopsis "Diet Estimated Trophic Levels")
    (description
     "Estimates fractional trophic level from quantitative and qualitative diet data
and calculates electivity indices in R. Borstein (2020)
<doi:10.1007/s10750-020-04417-5>.")
    (license license:gpl2+)))

(define-public r-diemr
  (package
    (name "r-diemr")
    (version "1.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diemr" version))
       (sha256
        (base32 "1rrqqj8ks4n457nammnkrvwzic69m6a2d52ac4x29kx9bgp4qwqa"))))
    (properties `((upstream-name . "diemr")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-vcfr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=diemr")
    (synopsis "Diagnostic Index Expectation Maximisation in R")
    (description
     "Likelihood-based genome polarisation finds which alleles of genomic markers
belong to which side of the barrier.  Co-estimates which individuals belong to
either side of the barrier and barrier strength.  Uses expectation maximisation
in likelihood framework.  The method is described in Baird et al. (2023)
<doi:10.1111/2041-210X.14010>.")
    (license license:gpl3+)))

(define-public r-didroorfm
  (package
    (name "r-didroorfm")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "didrooRFM" version))
       (sha256
        (base32 "12clfnbm56jwldw0afb0nb0argnd97mx7369jiywhxy0p4xqibqq"))))
    (properties `((upstream-name . "didrooRFM")))
    (build-system r-build-system)
    (propagated-inputs (list r-dplyr))
    (home-page "https://cran.r-project.org/package=didrooRFM")
    (synopsis
     "Compute Recency Frequency Monetary Scores for your Customer Data")
    (description
     "This hosts the @code{findRFM} function which generates RFM scores on a 1-5 point
scale for customer transaction data.  The function consumes a data frame with
Transaction Number, Customer ID, Date of Purchase (in date format) and Amount of
Purchase as the attributes.  The function returns a data frame with RFM data for
the sales information.")
    (license license:gpl2)))

(define-public r-didmultiplegtdyn
  (package
    (name "r-didmultiplegtdyn")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIDmultiplegtDYN" version))
       (sha256
        (base32 "0mcvac2p0sd0prxaj1ajigil4k9k9bm3y68lxxbrmhjrcn8n5n18"))))
    (properties `((upstream-name . "DIDmultiplegtDYN")))
    (build-system r-build-system)
    (propagated-inputs (list r-xlsx
                             r-sandwich
                             r-rnames
                             r-plm
                             r-matlib
                             r-lmtest
                             r-haven
                             r-ggplot2
                             r-dplyr
                             r-data-table
                             r-cowplot
                             r-car))
    (home-page "https://cran.r-project.org/package=DIDmultiplegtDYN")
    (synopsis
     "Estimation in Difference-in-Difference Designs with Multiple Groups and Periods")
    (description
     "Estimation of event-study Difference-in-Difference (DID) estimators in designs
with multiple groups and periods, and with a potentially non-binary treatment
that may increase or decrease multiple times.")
    (license license:expat)))

(define-public r-didmultiplegt
  (package
    (name "r-didmultiplegt")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIDmultiplegt" version))
       (sha256
        (base32 "14fa7zmhyz815z6h1ycvhcvq072g09jfjkcpyllxim4dl5430hdc"))))
    (properties `((upstream-name . "DIDmultiplegt")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-sampling
                             r-plotrix
                             r-magrittr
                             r-fixest
                             r-dplyr
                             r-didmultiplegtdyn
                             r-didhad))
    (home-page "https://cran.r-project.org/package=DIDmultiplegt")
    (synopsis "Estimators DID with Multiple Groups and Periods")
    (description
     "Estimators of Difference-in-Differences based on de Chaisemartin and
D'Haultfoeuille.")
    (license license:expat)))

(define-public r-didimputation
  (package
    (name "r-didimputation")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "didimputation" version))
       (sha256
        (base32 "122z473jkf5jb66s2g7vdqi0q56v8chz2dpl61qkcgqhv4hbh1q3"))))
    (properties `((upstream-name . "didimputation")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-rcpparmadillo
                             r-rcpp
                             r-purrr
                             r-matrix
                             r-magrittr
                             r-glue
                             r-fixest
                             r-dplyr
                             r-data-table
                             r-broom))
    (home-page "https://cran.r-project.org/package=didimputation")
    (synopsis "Imputation Estimator from Borusyak, Jaravel, and Spiess (2021)")
    (description
     "Estimates Two-way Fixed Effects difference-in-differences/event-study models
using the imputation-based approach proposed by Borusyak, Jaravel, and Spiess
(2021).")
    (license license:expat)))

(define-public r-didhad
  (package
    (name "r-didhad")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIDHAD" version))
       (sha256
        (base32 "1cmzsa1yn19gw5mc5lyrsnf1ghil7a3mgh2a1ana6rfzb5bpq4fq"))))
    (properties `((upstream-name . "DIDHAD")))
    (build-system r-build-system)
    (propagated-inputs (list r-yatchewtest
                             r-rnames
                             r-rlang
                             r-plm
                             r-nprobust
                             r-mass
                             r-haven
                             r-ggplot2
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=DIDHAD")
    (synopsis
     "Difference-in-Differences in Heterogeneous Adoption Designs with Quasi Stayers")
    (description
     "Estimation of Difference-in-Differences (@code{DiD}) estimators from de
Chaisemartin and D'Haultfoeuille (2024) <doi:10.2139/ssrn.4284811> in
Heterogeneous Adoption Designs with no stayers but with quasi stayers.")
    (license license:expat)))

(define-public r-didforbigdata
  (package
    (name "r-didforbigdata")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiDforBigData" version))
       (sha256
        (base32 "0f90wr7jrgsplja3n4f246avpxp3ysm03qi3nc6bfn0s1d969q91"))))
    (properties `((upstream-name . "DiDforBigData")))
    (build-system r-build-system)
    (propagated-inputs (list r-sandwich r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://setzler.github.io/DiDforBigData/")
    (synopsis
     "Big Data Implementation of Difference-in-Differences Estimation with Staggered Treatment")
    (description
     "This package provides a big-data-friendly and memory-efficient
difference-in-differences estimator for staggered (and non-staggered) treatment
contexts.")
    (license license:expat)))

(define-public r-diderot
  (package
    (name "r-diderot")
    (version "0.13")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Diderot" version))
       (sha256
        (base32 "04d1drxn99r0fqq3zym7yyip9c8rfqhghq20q4zyb42l3hfgv9ai"))))
    (properties `((upstream-name . "Diderot")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi
                             r-splitstackshape
                             r-rcurl
                             r-igraph
                             r-foreach
                             r-doparallel
                             r-data-table))
    (home-page "https://cran.r-project.org/package=Diderot")
    (synopsis "Bibliographic Network Analysis")
    (description
     "Enables the user to build a citation network/graph from bibliographic data and,
based on modularity and heterocitation metrics, assess the degree of
awareness/cross-fertilization between two corpora/communities.  This toolset is
optimized for Scopus data.")
    (license license:gpl2+)))

(define-public r-didec
  (package
    (name "r-didec")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "didec" version))
       (sha256
        (base32 "0x1ib0jnp1y7d5rpkf1m485bzyamfzx2i64my5ldwvr738sl2bdk"))))
    (properties `((upstream-name . "didec")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-phylogram
                             r-gtools
                             r-ggplot2
                             r-foci
                             r-factoextra
                             r-dendextend
                             r-cowplot
                             r-copbasic))
    (home-page "https://cran.r-project.org/package=didec")
    (synopsis "Directed Dependence Coefficient")
    (description
     "Directed Dependence Coefficient (didec) is a measure of directed dependence.
Multivariate Feature Ordering by Conditional Independence (MFOCI) is a variable
selection algorithm based on didec.  Hierarchical Variable Clustering
(@code{VarClustPartition}) is a variable clustering method based on didec.  For
more information, see the paper by Ansari and Fuchs (2024,
<doi:10.48550/@code{arXiv.2212.01621>}), and the paper by Fuchs and Wang (2024,
<doi:10.1016/j.ijar.2024.109185>).")
    (license license:expat)))

(define-public r-didacticboost
  (package
    (name "r-didacticboost")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DidacticBoost" version))
       (sha256
        (base32 "0z1h61n6nfjvb64fgkzi1sq7ag747crhh593hxkx0cpza29778rz"))))
    (properties `((upstream-name . "DidacticBoost")))
    (build-system r-build-system)
    (propagated-inputs (list r-rpart))
    (home-page "https://github.com/dashaub/DidacticBoost")
    (synopsis "Simple Implementation and Demonstration of Gradient Boosting")
    (description
     "This package provides a basic, clear implementation of tree-based gradient
boosting designed to illustrate the core operation of boosting models.  Tuning
parameters (such as stochastic subsampling, modified learning rate, or
regularization) are not implemented.  The only adjustable parameter is the
number of training rounds.  If you are looking for a high performance boosting
implementation with tuning parameters, consider the xgboost package.")
    (license license:gpl3)))

(define-public r-did2s
  (package
    (name "r-did2s")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "did2s" version))
       (sha256
        (base32 "0iyz6z4w2im22rvbpabql2w1cncv0pnrh0hp7agf0pazcpzk2jh6"))))
    (properties `((upstream-name . "did2s")))
    (build-system r-build-system)
    (propagated-inputs (list r-staggered
                             r-sparsem
                             r-rlang
                             r-matrixextra
                             r-matrix
                             r-ggplot2
                             r-fixest
                             r-didimputation
                             r-did
                             r-data-table
                             r-broom
                             r-boot))
    (native-inputs (list r-knitr))
    (home-page "https://kylebutts.github.io/did2s/")
    (synopsis "Two-Stage Difference-in-Differences Following Gardner (2021)")
    (description
     "Estimates Two-way Fixed Effects difference-in-differences/event-study models
using the approach proposed by Gardner (2021)
<doi:10.48550/@code{arXiv.2207.05943>}.  To avoid the problems caused by OLS
estimation of the Two-way Fixed Effects model, this function first estimates the
fixed effects and covariates using untreated observations and then in a second
stage, estimates the treatment effects.")
    (license license:expat)))

(define-public r-did
  (package
    (name "r-did")
    (version "2.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "did" version))
       (sha256
        (base32 "07r4m326n2gmgmf5ym5y72xg1xin771172rcpk0xkz6v344lwf9j"))))
    (properties `((upstream-name . "did")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-pbapply
                             r-matrix
                             r-ggpubr
                             r-ggplot2
                             r-generics
                             r-drdid
                             r-bmisc))
    (native-inputs (list r-knitr))
    (home-page "https://bcallaway11.github.io/did/")
    (synopsis "Treatment Effects with Multiple Periods and Groups")
    (description
     "The standard Difference-in-Differences (DID) setup involves two periods and two
groups -- a treated group and untreated group.  Many applications of DID methods
involve more than two periods and have individuals that are treated at different
points in time.  This package contains tools for computing average treatment
effect parameters in Difference in Differences setups with more than two periods
and with variation in treatment timing using the methods developed in Callaway
and Sant'Anna (2021) <doi:10.1016/j.jeconom.2020.12.001>.  The main parameters
are group-time average treatment effects which are the average treatment effect
for a particular group at a a particular time.  These can be aggregated into a
fewer number of treatment effect parameters, and the package deals with the
cases where there is selective treatment timing, dynamic treatment effects,
calendar time effects, or combinations of these.  There are also functions for
testing the Difference in Differences assumption, and plotting group-time
average treatment effects.")
    (license license:gpl2)))

(define-public r-dictionary
  (package
    (name "r-dictionary")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dictionaRy" version))
       (sha256
        (base32 "0j25wn2ghy59y1v02493d4knab06wxrzz8m9g6zxlkqzw1dqgc4f"))))
    (properties `((upstream-name . "dictionaRy")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-jsonlite))
    (home-page "https://github.com/stevecondylios/dictionaRy")
    (synopsis "Retrieve the Dictionary Definitions of English Words")
    (description
     "An R interface to the Free Dictionary API <https://dictionaryapi.dev/>,
<https://github.com/@code{meetDeveloper/freeDictionaryAPI>}.  Retrieve
dictionary definitions for English words, as well as additional information
including phonetics, part of speech, origins, audio pronunciation, example
usage, synonyms and antonyms, returned in tidy format for ease of use.")
    (license license:expat)))

(define-public r-dictionar6
  (package
    (name "r-dictionar6")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dictionar6" version))
       (sha256
        (base32 "1rg958py4pqghkid3830hla7vibvwsjhk75x55lxry5d8dp04m9f"))))
    (properties `((upstream-name . "dictionar6")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6 r-ooplah))
    (home-page "https://xoopR.github.io/dictionar6/")
    (synopsis "R6 Dictionary Interface")
    (description
     "Efficient object-oriented R6 dictionary capable of holding objects of any class,
including R6.  Typed and untyped dictionaries are provided as well as the usual
dictionary methods that are available in other OOP languages, for example
listing keys, items, values, and methods to get/set these.")
    (license license:expat)))

(define-public r-dict
  (package
    (name "r-dict")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Dict" version))
       (sha256
        (base32 "1v8yp03gajg9i82qyfww14jx93l4jbfq8mh6jqyf6calgrsj06jc"))))
    (properties `((upstream-name . "Dict")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-r6 r-purrr r-magrittr r-dplyr))
    (home-page "https://github.com/five-dots/Dict")
    (synopsis "R6 Based Key-Value Dictionary Implementation")
    (description
     "This package provides a key-value dictionary data structure based on R6 class
which is designed to be similar usages with other languages dictionary (e.g.
Python') with reference semantics and extendabilities by R6.")
    (license license:expat)))

(define-public r-diconvex
  (package
    (name "r-diconvex")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DIconvex" version))
       (sha256
        (base32 "0bnrq9nmryshir6ll43nz20aaqmmw0zjvfml72cpwbvrma8a3qmz"))))
    (properties `((upstream-name . "DIconvex")))
    (build-system r-build-system)
    (propagated-inputs (list r-lpsolveapi))
    (home-page "https://cran.r-project.org/package=DIconvex")
    (synopsis "Finding Patterns of Monotonicity and Convexity in Data")
    (description
     "Given an initial set of points, this package minimizes the number of elements to
discard from this set such that there exists at least one monotonic and convex
mapping within pre-specified upper and lower bounds.")
    (license license:gpl2)))

(define-public r-dicomread
  (package
    (name "r-dicomread")
    (version "0.0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DICOMread" version))
       (sha256
        (base32 "1wrgx5b9w476g8s3jmccc027xdqbmcmnlhwf02g6j213rgy87p73"))))
    (properties `((upstream-name . "DICOMread")))
    (build-system r-build-system)
    (propagated-inputs (list r-matlabr))
    (home-page "https://cran.r-project.org/package=DICOMread")
    (synopsis "Reading and Saving DICOM Image Files")
    (description
     "This function provides an interface between Matlab and R in facilitating fast
processing for reading and saving DICOM images.")
    (license license:gpl3)))

(define-public r-diceview
  (package
    (name "r-diceview")
    (version "2.2-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiceView" version))
       (sha256
        (base32 "1a7jlj7nmj41zfmpb54iwi8c9g44d376cc353ybr8dq8vkyq0vss"))))
    (properties `((upstream-name . "DiceView")))
    (build-system r-build-system)
    (propagated-inputs (list r-scatterplot3d r-r-cache r-geometry r-foreach
                             r-dicedesign))
    (home-page "https://github.com/IRSN/DiceView")
    (synopsis
     "Methods for Visualization of Computer Experiments Design and Surrogate")
    (description
     "View 2D/3D sections, contour plots, mesh of excursion sets for computer
experiments designs, surrogates or test functions.")
    (license license:gpl3)))

(define-public r-dicer
  (package
    (name "r-dicer")
    (version "2.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diceR" version))
       (sha256
        (base32 "1pfb1wxwh9li3z06hrx1zy5vwqmlmq4rjqjh1pi8i6jkbshf702m"))))
    (properties `((upstream-name . "diceR")))
    (build-system r-build-system)
    (propagated-inputs (list r-yardstick
                             r-tidyr
                             r-stringr
                             r-rcpp
                             r-rankaggreg
                             r-purrr
                             r-nmf
                             r-mclust
                             r-magrittr
                             r-klar
                             r-infotheo
                             r-ggplot2
                             r-dplyr
                             r-clvalid
                             r-clv
                             r-clustersim
                             r-clue
                             r-class
                             r-assertthat
                             r-abind))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/AlineTalhouk/diceR/")
    (synopsis "Diverse Cluster Ensemble in R")
    (description
     "This package performs cluster analysis using an ensemble clustering framework,
Chiu & Talhouk (2018) <doi:10.1186/s12859-017-1996-y>.  Results from a diverse
set of algorithms are pooled together using methods such as majority voting,
K-Modes, @code{LinkCluE}, and CSPA. There are options to compare cluster
assignments across algorithms using internal and external indices,
visualizations such as heatmaps, and significance testing for the existence of
clusters.")
    (license license:expat)))

(define-public r-diceplot
  (package
    (name "r-diceplot")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diceplot" version))
       (sha256
        (base32 "1jynszk534xsinc0sv4217s7i75804wp4nf3ry91374p1qz1zjc7"))))
    (properties `((upstream-name . "diceplot")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-rlang
                             r-ggplot2
                             r-dplyr
                             r-data-table
                             r-cowplot))
    (home-page "https://cran.r-project.org/package=diceplot")
    (synopsis "High Dimensional Categorical Data Visualization")
    (description
     "Easy visualization for datasets with more than two categorical variables and
additional continuous variables.  diceplot is particularly useful for exploring
complex categorical data in the context of pathway analysis across multiple
conditions.  For a detailed documentation please visit
<https://dice-and-domino-plot.readthedocs.io/en/latest/>.")
    (license license:gpl2+)))

(define-public r-diceoptim
  (package
    (name "r-diceoptim")
    (version "2.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiceOptim" version))
       (sha256
        (base32 "0qqvj97lzir6sgvshg13lr3c9yw1qybqh4m34kj37fk8gaab1py7"))))
    (properties `((upstream-name . "DiceOptim")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgenoud
                             r-randtoolbox
                             r-pbivnorm
                             r-mnormt
                             r-dicekriging
                             r-dicedesign))
    (home-page "http://dice.emse.fr/")
    (synopsis "Kriging-Based Optimization for Computer Experiments")
    (description
     "Efficient Global Optimization (EGO) algorithm as described in \"Roustant et al.
(2012)\" <doi:10.18637/jss.v051.i01> and adaptations for problems with noise
(\"Picheny and Ginsbourger, 2012\") <doi:10.1016/j.csda.2013.03.018>, parallel
infill, and problems with constraints.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-dicem
  (package
    (name "r-dicem")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DICEM" version))
       (sha256
        (base32 "099z5ns939az3nkajw179cc02ldagpwyvb9bhbvkvaxz5cpfn3j0"))))
    (properties `((upstream-name . "DICEM")))
    (build-system r-build-system)
    (propagated-inputs (list r-xgboost
                             r-vader
                             r-stringr
                             r-quanteda
                             r-politeness
                             r-matrix
                             r-doc2concrete))
    (home-page "https://cran.r-project.org/package=DICEM")
    (synopsis "Directness and Intensity of Conflict Expression")
    (description
     "This package provides a Natural Language Processing Model trained to detect
directness and intensity during conflict.  See <https://www.mikeyeomans.info>.")
    (license license:expat)))

(define-public r-diceeval
  (package
    (name "r-diceeval")
    (version "1.6.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiceEval" version))
       (sha256
        (base32 "02ba7cxp9hv983d3br4a1y3ss6krjax72vrpkp5qqy0v9fyshm23"))))
    (properties `((upstream-name . "DiceEval")))
    (build-system r-build-system)
    (propagated-inputs (list r-dicekriging))
    (home-page "https://cran.r-project.org/package=DiceEval")
    (synopsis "Construction and Evaluation of Metamodels")
    (description
     "Estimation, validation and prediction of models of different types : linear
models, additive models, MARS,@code{PolyMARS} and Kriging.")
    (license license:gpl3)))

(define-public r-dice
  (package
    (name "r-dice")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dice" version))
       (sha256
        (base32 "0gic7lqnsdmwv3dbzwwmcwdfyfqlq8kpr2pciqphd1j2ligzwl3s"))))
    (properties `((upstream-name . "dice")))
    (build-system r-build-system)
    (propagated-inputs (list r-gtools))
    (home-page "https://cran.r-project.org/package=dice")
    (synopsis "Calculate probabilities of various dice-rolling events")
    (description
     "This package provides utilities to calculate the probabilities of various
dice-rolling events, such as the probability of rolling a four-sided die six
times and getting a 4, a 3, and either a 1 or 2 among the six rolls (in any
order); the probability of rolling two six-sided dice three times and getting a
10 on the first roll, followed by a 4 on the second roll, followed by anything
but a 7 on the third roll; or the probabilities of each possible sum of rolling
five six-sided dice, dropping the lowest two rolls, and summing the remaining
dice.")
    (license license:gpl2+)))

(define-public r-dibble
  (package
    (name "r-dibble")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dibble" version))
       (sha256
        (base32 "1s845ii2hd0d2aam3wp3rb7r7i60plzqdmgdgix1pwbam02cfymn"))))
    (properties `((upstream-name . "dibble")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-tidyselect
                             r-tidyr
                             r-tibble
                             r-rlang
                             r-purrr
                             r-pillar
                             r-memoise
                             r-dplyr))
    (home-page "https://github.com/UchidaMizuki/dibble")
    (synopsis "Dimensional Data Frames")
    (description
     "This package provides a dibble that implements data cubes (derived from
dimensional tibble'), and allows broadcasting by dimensional names.")
    (license license:expat)))

(define-public r-diathor
  (package
    (name "r-diathor")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diathor" version))
       (sha256
        (base32 "12m174r2z2vwxqwpayd8fz5hgrgx87bzfklpsksfm4zma64xwmxb"))))
    (properties `((upstream-name . "diathor")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-stringdist
                             r-purrr
                             r-ggplot2
                             r-data-table))
    (home-page "https://cran.r-project.org/package=diathor")
    (synopsis "Calculate Ecological Information and Diatom Based Indices")
    (description
     "Calculate multiple biotic indices using diatoms from environmental samples.
Diatom species are identified by their species names through a heuristic search,
and ecological data is retrieved from multiple sources.  The package includes
the calculation of chloroplast diversity indices, size classes, ecological
guilds, and various biotic indices.  It outputs both a dataframe with all the
results and plots of the obtained data in a specified output folder.  Sample
data is sourced from Nicolosi Gelis, Cochero, & GÃ³mez (2020,
<doi:10.1016/j.ecolind.2019.105951>).  The package utilizes the Diat.Barcode
database for morphological and ecological information by Rimet & Couchez (2012,
<doi:10.1051/kmae/2012018>), along with the combined classification of guilds
and size classes from B-Beres et al. (2017,
<doi:10.1016/j.ecolind.2017.07.007>).  Currently supported diatom-based biotic
indices include DES index (Descy, 1979); EPID index (Dell'Uomo, 1996); IDAP
index (Prygiel & Coste, 1993); ID-CH index (HÃ¼rlimann & Niederhauser, 2007);
IDP index (GÃ³mez & Licursi, 2001); ILM index (Leclercq & Maquet, 1987); IPS
index (Coste, 1982); LOBO index (Lobo, Callegaro, & Bender, 2002); SLA index
(Sladecek, 1986); TDI index (Kelly & Whitton, 1995); SPEAR(herbicide) index
(Wood et al., 2019); PBIDW index (Castro-Roa & Pinilla-Agudelo, 2014); DISP
index (Stenger-KovÃ¡csa et al., 2018).")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-diaplt
  (package
    (name "r-diaplt")
    (version "1.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diaplt" version))
       (sha256
        (base32 "103hq13ql8xs1zb90is2r1lanj5vpvz9rk315zvbd8am00fshc9n"))))
    (properties `((upstream-name . "diaplt")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=diaplt")
    (synopsis "Beads Summary Plot of Ranges")
    (description
     "Visualize one-factor data frame.  Beads plot consists of diamonds of each factor
of each data series.  A diamond indicates average and range.  Look over a data
frame with many numeric columns and a factor column.")
    (license license:expat)))

(define-public r-dialrjars
  (package
    (name "r-dialrjars")
    (version "8.13.36")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dialrjars" version))
       (sha256
        (base32 "1r02wimq3bnb28dz65jm0kmkkkd02k0a4d50cjn5n54ck8lf9hsc"))))
    (properties `((upstream-name . "dialrjars")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (propagated-inputs (list r-rjava))
    (home-page "https://github.com/socialresearchcentre/dialrjars")
    (synopsis "Required 'libphonenumber' jars for the 'dialr' Package")
    (description
     "Collects libphonenumber jars required for the dialr package.")
    (license license:gpl3+)))

(define-public r-dialr
  (package
    (name "r-dialr")
    (version "0.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dialr" version))
       (sha256
        (base32 "16lpb93shwr0gw7pk3q629kgsvh9csgxyy344m9za7qx9m2vjnnb"))))
    (properties `((upstream-name . "dialr")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (propagated-inputs (list r-rjava r-dialrjars))
    (native-inputs (list r-knitr))
    (home-page "https://socialresearchcentre.github.io/dialr/")
    (synopsis "Parse, Format, and Validate International Phone Numbers")
    (description
     "Parse, format, and validate international phone numbers using Google's
libphonenumber java library, <https://github.com/google/libphonenumber>.")
    (license license:gpl3+)))

(define-public r-diallelanalysisr
  (package
    (name "r-diallelanalysisr")
    (version "0.6.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiallelAnalysisR" version))
       (sha256
        (base32 "042i84pxm3gy59r94m0pk7gb04kxl9l8w43b9h7g70dyxi6hf89x"))))
    (properties `((upstream-name . "DiallelAnalysisR")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2))
    (home-page "https://cran.r-project.org/package=DiallelAnalysisR")
    (synopsis "Diallel Analysis with R")
    (description
     "This package performs Diallel Analysis with R using Griffing's and Hayman's
approaches.  Four different Methods (1: Method-I (Parents + F1's + reciprocals);
2: Method-II (Parents and one set of F1's); 3: Method-III (One set of F1's and
reciprocals); 4: Method-IV (One set of F1's only)) and two Models (1: Fixed
Effects Model; 2: Random Effects Model) can be applied using Griffing's
approach.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-diagrammersvg
  (package
    (name "r-diagrammersvg")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiagrammeRsvg" version))
       (sha256
        (base32 "0j2cm1mx3zrb2k3pcrb96z2z3kws61gyyjsjjv5rqcb5lzdgi65k"))))
    (properties `((upstream-name . "DiagrammeRsvg")))
    (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-v8))
    (native-inputs (list esbuild))
    (home-page "https://github.com/rich-iannone/DiagrammeRsvg")
    (synopsis "Export DiagrammeR Graphviz Graphs as SVG")
    (description
     "Allows for export of @code{DiagrammeR} Graphviz objects to SVG.")
    (license license:expat)))

(define-public r-diagrammer
  (package
    (name "r-diagrammer")
    (version "1.0.11")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DiagrammeR" version))
       (sha256
        (base32 "1py4yii88lsyj8y71d2v0rb9lk5hvhfh0q8n2q4288wqw7bf6wz8"))))
    (properties `((upstream-name . "DiagrammeR")))
    (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-visnetwork
                             r-viridislite
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-scales
                             r-rstudioapi
                             r-rlang
                             r-readr
                             r-rcolorbrewer
                             r-purrr
                             r-magrittr
                             r-igraph
                             r-htmlwidgets
                             r-htmltools
                             r-glue
                             r-dplyr
                             r-cli))
    (native-inputs (list esbuild))
    (home-page "https://rich-iannone.github.io/DiagrammeR/")
    (synopsis "Graph/Network Visualization")
    (description
     "Build graph/network structures using functions for stepwise addition and
deletion of nodes and edges.  Work with data available in tables for bulk
addition of nodes, edges, and associated metadata.  Use graph selections and
traversals to apply changes to specific nodes or edges.  A wide selection of
graph algorithms allow for the analysis of graphs.  Visualize the graphs and
take advantage of any aesthetic properties assigned to nodes and edges.")
    (license license:expat)))

(define-public r-diagonals
  (package
    (name "r-diagonals")
    (version "6.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diagonals" version))
       (sha256
        (base32 "1c5pf23bcq47m9n2s5m5bkcksnifz9g06xc9149163i8mqhzia7l"))))
    (properties `((upstream-name . "diagonals")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://qua.st/diagonals")
    (synopsis "Block Diagonal Extraction or Replacement")
    (description
     "Several tools for handling block-matrix diagonals and similar constructs are
implemented.  Block-diagonal matrices can be extracted or removed using two
small functions implemented here.  In addition, non-square matrices are
supported.  Block diagonal matrices occur when two dimensions of a data set are
combined along one edge of a matrix.  For example, trade-flow data in the
decompr and gvc packages have each country-industry combination occur along both
edges of the matrix.")
    (license license:gpl3)))

(define-public r-diagmeta
  (package
    (name "r-diagmeta")
    (version "0.5-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diagmeta" version))
       (sha256
        (base32 "1wilkpwb8vzjx8zpgq0zmvfcd35dij4jxk5gn0x1xyhlfvj9nxrj"))))
    (properties `((upstream-name . "diagmeta")))
    (build-system r-build-system)
    (propagated-inputs (list r-meta r-lme4))
    (home-page "https://github.com/guido-s/diagmeta")
    (synopsis
     "Meta-Analysis of Diagnostic Accuracy Studies with Several Cutpoints")
    (description
     "This package provides methods by Steinhauser et al. (2016)
<DOI:10.1186/s12874-016-0196-1> for meta-analysis of diagnostic accuracy studies
with several cutpoints.")
    (license license:gpl2+)))

(define-public r-diagl1
  (package
    (name "r-diagl1")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diagL1" version))
       (sha256
        (base32 "1rl51a5gjzf41la0rbigz4n8brn1prji6hp862hlxwscdni9w2f9"))))
    (properties `((upstream-name . "diagL1")))
    (build-system r-build-system)
    (propagated-inputs (list r-quantreg
                             r-matrixmodels
                             r-matrix
                             r-mass
                             r-lawstat
                             r-greekletters
                             r-foreach
                             r-doparallel
                             r-cubature
                             r-conquer))
    (home-page "https://cran.r-project.org/package=diagL1")
    (synopsis
     "Routines for Fit, Inference and Diagnostics in Linear L1 and LAD Models")
    (description
     "Diagnostics for linear L1 regression (also known as LAD - Least Absolute
Deviations), including: estimation, confidence intervals, tests of hypotheses,
measures of leverage, methods of diagnostics for L1 regression, special
diagnostics graphs and measures of leverage.  The algorithms are based in
Dielman (2005) <doi:10.1080/0094965042000223680>, Elian et al. (2000)
<doi:10.1080/03610920008832518> and Dodge (1997) <doi:10.1006/jmva.1997.1666>.
This package builds on the quantreg package, which is a well-established package
for tuning quantile regression models.  There are also tests to verify if the
errors have a Laplace distribution based on the work of Puig and Stephens (2000)
<doi:10.2307/1270952>.")
    (license license:gpl2+)))

(define-public r-diagis
  (package
    (name "r-diagis")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "diagis" version))
       (sha256
        (base32 "1gl720d1rrmqingsskkc86kl3n10c7cwvmx19yyxiprwzfkrjh95"))))
    (properties `((upstream-name . "diagis")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-gridextra r-ggplot2
                             r-coda))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/helske/diagis/")
    (synopsis
     "Diagnostic Plot and Multivariate Summary Statistics of Weighted Samples from Importance Sampling")
    (description
     "Fast functions for effective sample size, weighted multivariate mean, variance,
and quantile computation, and weight diagnostic plot for generic importance
sampling type or other probability weighted samples.")
    (license license:gpl2+)))

(define-public r-di
  (package
    (name "r-di")
    (version "1.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "di" version))
       (sha256
        (base32 "1w2gjhyi410z98d8wnhbd69jxm69nz4pmnr4fb09i70a90f53s25"))))
    (properties `((upstream-name . "di")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=di")
    (synopsis "Deficit Index (DI)")
    (description
     "This package provides a set of utilities for calculating the Deficit (frailty)
Index (DI) in gerontological studies.  The deficit index was first proposed by
Arnold Mitnitski and Kenneth Rockwood and represents a proxy measure of aging
and also can be served as a sensitive predictor of survival.  For more
information, see (i)\"Accumulation of Deficits as a Proxy Measure of Aging\" by
Arnold B. Mitnitski et al. (2001), The Scientific World Journal 1,
<DOI:10.1100/tsw.2001.58>; (ii) \"Frailty, fitness and late-life mortality in
relation to chronological and biological age\" by Arnold B Mitnitski et al.
(2001), BMC Geriatrics2002 2(1), <DOI:10.1186/1471-2318-2-1>.")
    (license license:gpl3)))

(define-public r-dhsic
  (package
    (name "r-dhsic")
    (version "2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dHSIC" version))
       (sha256
        (base32 "1c1xz1f1fp937w4rlylvqv3ii0p9dafvmn4fqq8rzxhcg5rn9j4l"))))
    (properties `((upstream-name . "dHSIC")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://cran.r-project.org/package=dHSIC")
    (synopsis
     "Independence Testing via Hilbert Schmidt Independence Criterion")
    (description
     "This package contains an implementation of the d-variable Hilbert Schmidt
independence criterion and several hypothesis tests based on it, as described in
Pfister et al. (2017) <doi:10.1111/rssb.12235>.")
    (license license:gpl3)))

(define-public r-dhsage
  (package
    (name "r-dhsage")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dhsage" version))
       (sha256
        (base32 "1p239fsay49rvakxgkgnghra7p4nzyvfird8mc4i4lz4w133x1jd"))))
    (properties `((upstream-name . "dhsage")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dhsage")
    (synopsis
     "Reproductive Age Female Data of Various Demographic Health Surveys")
    (description
     "We provide 70 data sets of females of reproductive age from 19 Asian countries,
ranging in age from 15 to 49.  The data sets are extracted from demographic and
health surveys that were conducted over an extended period of time.  Moreover,
the functions also provide Whippleâs index as well as age reporting quality
such as very rough, rough, approximate, accurate, and highly accurate.")
    (license license:gpl2+)))

(define-public r-dhs-rates
  (package
    (name "r-dhs-rates")
    (version "0.9.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DHS.rates" version))
       (sha256
        (base32 "1j4jgwi5skjr4h8gyphkfjxhx80f0x6bhqb81711bhq5zp3bl59l"))))
    (properties `((upstream-name . "DHS.rates")))
    (build-system r-build-system)
    (propagated-inputs (list r-survey
                             r-rlang
                             r-reshape
                             r-matrixstats
                             r-haven
                             r-dplyr
                             r-crayon))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DHS.rates")
    (synopsis "Calculates Demographic Indicators")
    (description
     "Calculates key indicators such as fertility rates (Total Fertility Rate (TFR),
General Fertility Rate (GFR), and Age Specific Fertility Rate (ASFR)) using
Demographic and Health Survey (DHS) women/individual data, childhood mortality
probabilities and rates such as Neonatal Mortality Rate (NNMR), Post-neonatal
Mortality Rate (PNNMR), Infant Mortality Rate (IMR), Child Mortality Rate (CMR),
and Under-five Mortality Rate (U5MR), and adult mortality indicators such as the
Age Specific Mortality Rate (ASMR), Age Adjusted Mortality Rate (AAMR), Age
Specific Maternal Mortality Rate (ASMMR), Age Adjusted Maternal Mortality Rate
(AAMMR), Age Specific Pregnancy Related Mortality Rate (ASPRMR), Age Adjusted
Pregnancy Related Mortality Rate (AAPRMR), Maternal Mortality Ratio (MMR) and
Pregnancy Related Mortality Ratio (PRMR).  In addition to the indicators, the
DHS.rates package estimates sampling errors indicators such as Standard Error
(SE), Design Effect (DEFT), Relative Standard Error (RSE) and Confidence
Interval (CI).  The package is developed according to the DHS methodology of
calculating the fertility indicators and the childhood mortality rates outlined
in the \"Guide to DHS Statistics\" (Croft, Trevor N., Aileen M. J. Marshall,
Courtney K. Allen, et al.  2018,
<https://dhsprogram.com/Data/Guide-to-DHS-Statistics/index.cfm>) and the DHS
methodology of estimating the sampling errors indicators outlined in the \"DHS
Sampling and Household Listing Manual\" (ICF International 2012,
<https://dhsprogram.com/pubs/pdf/DHSM4/DHS6_Sampling_Manual_Sept2012_DHSM4.pdf>).")
    (license license:gpl2)))

(define-public r-dhh
  (package
    (name "r-dhh")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dhh" version))
       (sha256
        (base32 "00kg2x1was85aq2vr15bak8y5p4mymbs8pbriijlbw64401djmb0"))))
    (properties `((upstream-name . "dhh")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dhh")
    (synopsis "Heavy-Headed Distribution")
    (description
     "The density, cumulative distribution, quantiles, and i.i.d random variables of a
heavy-headed distribution.  For more information, please see the vignette.")
    (license license:gpl2+)))

(define-public r-dhglm
  (package
    (name "r-dhglm")
    (version "2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dhglm" version))
       (sha256
        (base32 "1918wkylldcdxjggly3a4yh4cv2nkig5bjfx0j79av633hahlg92"))))
    (properties `((upstream-name . "dhglm")))
    (build-system r-build-system)
    (propagated-inputs (list r-sandwich r-matrix r-mass r-car r-boot))
    (home-page "https://cran.r-project.org/package=dhglm")
    (synopsis "Double Hierarchical Generalized Linear Models")
    (description
     "This package implements double hierarchical generalized linear models in which
the mean, dispersion parameters for variance of random effects, and residual
variance (overdispersion) can be further modeled as random-effect models.")
    (license (license:fsdg-compatible "Unlimited"))))

(define-public r-dhga
  (package
    (name "r-dhga")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dhga" version))
       (sha256
        (base32 "1n48irj53g3kn451ak5ly50wxdn7qmzi2kib8clsvcx2n7mvpgcm"))))
    (properties `((upstream-name . "dhga")))
    (build-system r-build-system)
    (propagated-inputs (list r-venndiagram))
    (home-page "https://cran.r-project.org/package=dhga")
    (synopsis "Differential Hub Gene Analysis")
    (description
     "Identification of hub genes in a gene co-expression network from gene expression
data.  The differential network analysis for two contrasting conditions leads to
the identification of various types of hubs like Housekeeping, Unique to stress
(Disease) and Unique to control (Normal) hub genes.")
    (license license:gpl2+)))

(define-public r-dhbins
  (package
    (name "r-dhbins")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DHBins" version))
       (sha256
        (base32 "1g69acac7pxw8x0d9czyds7xljhbv9d686c99a3y8b4vh7dnx62s"))))
    (properties `((upstream-name . "DHBins")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2))
    (home-page "https://cran.r-project.org/package=DHBins")
    (synopsis "Hexmaps for NZ District Health Boards")
    (description
     "Draws stylized choropleth maps -- hexagonal maps and triangular multiclass hex
maps -- for New Zealand District Health Boards and Regional Council areas.
These allow faceted, coloured displays of quantitative information for
comparison across District Health Boards or Regional Councils.  The preprint
Lumley (2019) <@code{arXiv:1912.04435>} is based on the methods in this package.")
    (license license:gpl3)))

(define-public r-dharma
  (package
    (name "r-dharma")
    (version "0.4.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DHARMa" version))
       (sha256
        (base32 "0mfywr4pshnd13xs2zdhd8xvbc43qxaj075jhy8lrlg1agmc6gya"))))
    (properties `((upstream-name . "DHARMa")))
    (build-system r-build-system)
    (propagated-inputs (list r-qgam
                             r-matrix
                             r-lmtest
                             r-lme4
                             r-gap
                             r-ape))
    (native-inputs (list r-knitr))
    (home-page "http://florianhartig.github.io/DHARMa/")
    (synopsis
     "Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models")
    (description
     "The DHARMa package uses a simulation-based approach to create readily
interpretable scaled (quantile) residuals for fitted (generalized) linear mixed
models.  Currently supported are linear and generalized linear (mixed) models
from lme4 (classes @code{lmerMod}', @code{glmerMod}'), @code{glmmTMB}',
GLMMadaptive', and @code{spaMM}'; phylogenetic linear models from phylolm
(classes phylolm and phyloglm'); generalized additive models ('gam from mgcv');
glm (including negbin from MASS', but excluding quasi-distributions) and lm
model classes.  Moreover, externally created simulations, e.g. posterior
predictive simulations from Bayesian software such as JAGS', STAN', or BUGS can
be processed as well.  The resulting residuals are standardized to values
between 0 and 1 and can be interpreted as intuitively as residuals from a linear
regression.  The package also provides a number of plot and test functions for
typical model misspecification problems, such as over/underdispersion,
zero-inflation, and residual spatial, phylogenetic and temporal autocorrelation.")
    (license license:gpl3+)))

(define-public r-dgumbel
  (package
    (name "r-dgumbel")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dgumbel" version))
       (sha256
        (base32 "1qlc81rh6fcrai9ls27j83bjac26qhpfnchf9pdjz86dyclfjx43"))))
    (properties `((upstream-name . "dgumbel")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppeigen r-rcpp))
    (home-page "https://github.com/blunde1/dgumbel")
    (synopsis "The Gumbel Distribution Functions and Gradients")
    (description
     "Gumbel distribution functions (De Haan L. (2007) <doi:10.1007/0-387-34471-3>)
implemented with the techniques of automatic differentiation (Griewank A. (2008)
<isbn:978-0-89871-659-7>).  With this tool, a user should be able to quickly
model extreme events for which the Gumbel distribution is the domain of
attraction.  The package makes available the density function, the distribution
function the quantile function and a random generating function.  In addition,
it supports gradient functions.  The package combines Adept (C++ templated
automatic differentiation) (Hogan R. (2017) <doi:10.5281/zenodo.1004730>) and
Eigen (templated matrix-vector library) for fast computations of both objective
functions and exact gradients.  It relies on @code{RcppEigen} for easy access to
Eigen and bindings to R.")
    (license license:gpl2+)))

(define-public r-dgpsi
  (package
    (name "r-dgpsi")
    (version "2.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dgpsi" version))
       (sha256
        (base32 "004d15bql0by1j4gacrjfbnk95wyzd1m54gdh23y7n664xdn3fql"))))
    (properties `((upstream-name . "dgpsi")))
    (build-system r-build-system)
    (propagated-inputs (list r-uuid
                             r-reticulate
                             r-reshape2
                             r-patchwork
                             r-lhs
                             r-ggplot2
                             r-ggforce
                             r-dplyr
                             r-clhs
                             r-bitops
                             r-benchmarkme))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mingdeyu/dgpsi-R")
    (synopsis
     "Interface to 'dgpsi' for Deep and Linked Gaussian Process Emulations")
    (description
     "Interface to the python package dgpsi for Gaussian process, deep Gaussian
process, and linked deep Gaussian process emulations of computer models and
networks using stochastic imputation (SI).  The implementations follow Ming &
Guillas (2021) <doi:10.1137/20M1323771> and Ming, Williamson, & Guillas (2023)
<doi:10.1080/00401706.2022.2124311> and Ming & Williamson (2023)
<@code{arXiv:2306.01212>}.  To get started with the package, see
<https://mingdeyu.github.io/dgpsi-R/>.")
    (license license:expat)))

(define-public r-dgp4lcf
  (package
    (name "r-dgp4lcf")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DGP4LCF" version))
       (sha256
        (base32 "1v8wh52wcxs4adp1h9xplj5vych867scjrw32pqdczmiawi3q9d5"))))
    (properties `((upstream-name . "DGP4LCF")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo
                             r-rcpp
                             r-pheatmap
                             r-mvtnorm
                             r-gpfda
                             r-factor-switching
                             r-corrplot
                             r-combinat
                             r-coda))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DGP4LCF")
    (synopsis
     "Dependent Gaussian Processes for Longitudinal Correlated Factors")
    (description
     "Functionalities for analyzing high-dimensional and longitudinal biomarker data
to facilitate precision medicine, using a joint model of Bayesian sparse factor
analysis and dependent Gaussian processes.  This paper illustrates the method in
detail: J Cai, RJB Goudie, C Starr, BDM Tom (2023)
<doi:10.48550/@code{arXiv.2307.02781>}.")
    (license license:expat)))

(define-public r-dgof
  (package
    (name "r-dgof")
    (version "1.5.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dgof" version))
       (sha256
        (base32 "0530k0isqq26xal2smp1kf6fi7vs1r6g4bbhdnzpiwlij8a7c8zs"))))
    (properties `((upstream-name . "dgof")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dgof")
    (synopsis "Discrete Goodness-of-Fit Tests")
    (description
     "This package provides a revision to the stats::ks.test() function and the
associated ks.test.Rd help page.  With one minor exception, it does not change
the existing behavior of ks.test(), and it adds features necessary for doing
one-sample tests with hypothesized discrete distributions.  The package also
contains cvm.test(), for doing one-sample Cramer-von Mises goodness-of-fit
tests.")
    (license license:gpl2+)))

(define-public r-dgm
  (package
    (name "r-dgm")
    (version "1.7.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DGM" version))
       (sha256
        (base32 "1f59spd4bwx4d1gbjaizjxccaslw1fvf8pxa9nrxi07j6kq9mg0h"))))
    (properties `((upstream-name . "DGM")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2
                             r-rcpparmadillo
                             r-rcpp
                             r-ggplot2
                             r-data-table
                             r-coin))
    (home-page "https://github.com/schw4b/DGM")
    (synopsis "Dynamic Graphical Models")
    (description
     "Dynamic graphical models for multivariate time series data to estimate directed
dynamic networks in functional magnetic resonance imaging (@code{fMRI}), see
Schwab et al. (2017) <doi:10.1016/j.neuroimage.2018.03.074>.")
    (license license:gpl3)))

(define-public r-dglmextpois
  (package
    (name "r-dglmextpois")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DGLMExtPois" version))
       (sha256
        (base32 "0bbf7cyrnn1ghvhbnv54pv6325l8v8fy1bayl4b6qgs84xd959p4"))))
    (properties `((upstream-name . "DGLMExtPois")))
    (build-system r-build-system)
    (propagated-inputs (list r-nloptr r-compoissonreg))
    (home-page "https://github.com/franciscomartinezdelrio/DGLMExtPois")
    (synopsis "Double Generalized Linear Models Extending Poisson Regression")
    (description
     "Model estimation, dispersion testing and diagnosis of hyper-Poisson
Saez-Castillo, A.J. and Conde-Sanchez, A. (2013)
<doi:10.1016/j.csda.2012.12.009> and Conway-Maxwell-Poisson Huang, A. (2017)
regression models.")
    (license license:gpl2)))

(define-public r-dglm
  (package
    (name "r-dglm")
    (version "1.8.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dglm" version))
       (sha256
        (base32 "1xgvfdlsgi14mv02k71dg0g21yhzzzpaf0dlaq26w6565046m6iy"))))
    (properties `((upstream-name . "dglm")))
    (build-system r-build-system)
    (propagated-inputs (list r-statmod))
    (home-page "https://cran.r-project.org/package=dglm")
    (synopsis "Double Generalized Linear Models")
    (description
     "Model fitting and evaluation tools for double generalized linear models (DGLMs).
 This class of models uses one generalized linear model (GLM) to fit the
specified response and a second GLM to fit the deviance of the first model.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-dglars
  (package
    (name "r-dglars")
    (version "2.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dglars" version))
       (sha256
        (base32 "0nr18ry5jzjm77xc3z85szx6sij7a4faa1c47bkswsjiijpljjx2"))))
    (properties `((upstream-name . "dglars")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix))
    (native-inputs (list gfortran))
    (home-page "https://www.jstatsoft.org/v59/i08/.")
    (synopsis "Differential Geometric Least Angle Regression")
    (description
     "Differential geometric least angle regression method for fitting sparse
generalized linear models.  In this version of the package, the user can fit
models specifying Gaussian, Poisson, Binomial, Gamma and Inverse Gaussian
family.  Furthermore, several link functions can be used to model the
relationship between the conditional expected value of the response variable and
the linear predictor.  The solution curve can be computed using an efficient
predictor-corrector or a cyclic coordinate descent algorithm, as described in
the paper linked to via the URL below.")
    (license license:gpl2+)))

(define-public r-dggridr
  (package
    (name "r-dggridr")
    (version "3.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dggridR" version))
       (sha256
        (base32 "1vwmf5m1k40kk68vil280gnzh028y04wi5q3xjacyhaw8di0w9d5"))))
    (properties `((upstream-name . "dggridR")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf r-s2 r-rcpp r-collapse))
    (native-inputs (list r-r-rsp r-knitr))
    (home-page "https://github.com/r-barnes/dggridR/")
    (synopsis "Discrete Global Grids")
    (description
     "Spatial analyses involving binning require that every bin have the same area,
but this is impossible using a rectangular grid laid over the Earth or over any
projection of the Earth.  Discrete global grids use hexagons, triangles, and
diamonds to overcome this issue, overlaying the Earth with equally-sized bins.
This package provides utilities for working with discrete global grids, along
with utilities to aid in plotting such data.")
    (license license:agpl3+)))

(define-public r-dgeobj-utils
  (package
    (name "r-dgeobj-utils")
    (version "1.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DGEobj.utils" version))
       (sha256
        (base32 "01pbyz62vayism9bk6scx97yxwfmsss2af39grq46rilrcgrck3k"))))
    (properties `((upstream-name . "DGEobj.utils")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-dplyr r-dgeobj r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DGEobj.utils")
    (synopsis "Differential Gene Expression (DGE) Analysis Utility Toolkit")
    (description
     "This package provides a function toolkit to facilitate reproducible RNA-Seq
Differential Gene Expression (DGE) analysis (Law (2015)
<doi:10.12688/f1000research.9005.3>).  The tools include both analysis work-flow
and utility functions: mapping/unit conversion, count normalization, accounting
for unknown covariates, and more.  This is a complement/cohort to the DGEobj
package that provides a flexible container to manage and annotate Differential
Gene Expression analysis results.")
    (license license:gpl3)))

(define-public r-dgeobj
  (package
    (name "r-dgeobj")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DGEobj" version))
       (sha256
        (base32 "00ndl6ckbr3f6pg9mgcygv1pq7j8gc7g8f54lirm624hiswsppn3"))))
    (properties `((upstream-name . "DGEobj")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-magrittr r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DGEobj")
    (synopsis
     "Differential Gene Expression (DGE) Analysis Results Data Object")
    (description
     "This package provides a flexible container to manage and annotate Differential
Gene Expression (DGE) analysis results (Smythe et.  al (2015)
<doi:10.1093/nar/gkv007>).  The DGEobj has data slots for row (gene), col
(samples), assays (matrix n-rows by m-samples dimensions) and metadata (not
keyed to row, col, or assays).  A set of accessory functions to deposit, query
and retrieve subsets of a data workflow has been provided.  Attributes are used
to capture metadata such as species and gene model, including reproducibility
information such that a 3rd party can access a DGEobj history to see how each
data object was created or modified.  Since the DGEobj is customizable and
extensible it is not limited to RNA-seq analysis types of workflows -- it can
accommodate nearly any data analysis workflow that starts from a matrix of
assays (rows) by samples (columns).")
    (license license:gpl3)))

(define-public r-dgear
  (package
    (name "r-dgear")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DGEAR" version))
       (sha256
        (base32 "0knai1098ayp2z1s2x4zkk5npmakw30qk8qdp4hsmvwh21rijnzw"))))
    (properties `((upstream-name . "DGEAR")))
    (build-system r-build-system)
    (propagated-inputs (list r-desctools))
    (home-page "https://cran.r-project.org/package=DGEAR")
    (synopsis "Differential Gene Expression Analysis with R")
    (description
     "Analyses gene expression data derived from experiments to detect differentially
expressed genes by employing the concept of majority voting with five different
statistical models.  It includes functions for differential expression analysis,
significance testing, etc.  It simplifies the process of uncovering meaningful
patterns and trends within gene expression data, aiding researchers in
downstream analysis.  Boyer, R.S., Moore, J.S. (1991)
<doi:10.1007/978-94-011-3488-0_5>.")
    (license license:expat)))

(define-public r-dgaselid
  (package
    (name "r-dgaselid")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dGAselID" version))
       (sha256
        (base32 "0da7fi872i3ycb3j5v4isr4x2z39a68w4mdq859zslmqhiqd43b6"))))
    (properties `((upstream-name . "dGAselID")))
    (build-system r-build-system)
    (propagated-inputs (list r-mlinterfaces r-genefilter r-biobase r-all))
    (home-page "https://cran.r-project.org/package=dGAselID")
    (synopsis
     "Genetic Algorithm with Incomplete Dominance for Feature Selection")
    (description
     "Feature selection from high dimensional data using a diploid genetic algorithm
with Incomplete Dominance for genotype to phenotype mapping and Random
Assortment of chromosomes approach to recombination.")
    (license license:expat)))

(define-public r-dga
  (package
    (name "r-dga")
    (version "2.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dga" version))
       (sha256
        (base32 "1q860hzxrbkpmnphdysx4wk1b46wjll8sw7xjsy1lxcaz9hwcnjk"))))
    (properties `((upstream-name . "dga")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-chron))
    (home-page "https://cran.r-project.org/package=dga")
    (synopsis "Capture-Recapture Estimation using Bayesian Model Averaging")
    (description
     "This package performs Bayesian model averaging for capture-recapture.  This
includes code to stratify records, check the strata for suitable overlap to be
used for capture-recapture, and some functions to plot the estimated population
size.")
    (license license:gpl2+)))

(define-public r-dfvad
  (package
    (name "r-dfvad")
    (version "0.3.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfvad" version))
       (sha256
        (base32 "1g232y0zmgpgx6phfsx67548dvqiwa4bc8q9cvpgmkdfaskczcfx"))))
    (properties `((upstream-name . "dfvad")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/shipei-zeng/dfvad")
    (synopsis "Diewert and Fox's Method of Value Added Growth Decomposition")
    (description
     "Decomposing value added growth into explanatory factors.  A cost constrained
value added function is defined to specify the production frontier.  Industry
estimates can also be aggregated using a weighted average approach.  Details
about the methodology and data can be found in Diewert and Fox (2018)
<doi:10.1093/oxfordhb/9780190226718.013.19> and Zeng, Parsons, Diewert and Fox
(2018)
<https://www.business.unsw.edu.au/research-site/centreforappliedeconomicresearch-site/Documents/emg2018-6_SZeng_EMG-Slides.pdf>.")
    (license license:gpl2)))

(define-public r-dfsaneacc
  (package
    (name "r-dfsaneacc")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfsaneacc" version))
       (sha256
        (base32 "1sicnpir73vvg470q1mcfd1p06vgfr6z3kfb5mnipr5z72c9gd4w"))))
    (properties `((upstream-name . "dfsaneacc")))
    (build-system r-build-system)
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=dfsaneacc")
    (synopsis
     "Accelerated Derivative-Free Method for Large-Scale Nonlinear Systems of Equations")
    (description
     "Secant acceleration applied to derivative-free Spectral Residual Methods for
solving large-scale nonlinear systems of equations.  The main reference follows:
E. G. Birgin and J. M. Martinez (2022) <doi:10.1137/20M1388024>.")
    (license license:gpl3)))

(define-public r-dfrr
  (package
    (name "r-dfrr")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfrr" version))
       (sha256
        (base32 "0kgsi2jysv0hpdvmv1fng41ar7p3pgzgf1vv0dcm954jdrl2dz6d"))))
    (properties `((upstream-name . "dfrr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tmvtnorm r-plotly r-mass r-ggplot2 r-fda))
    (home-page "https://github.com/asgari-fatemeh/dfrr")
    (synopsis "Dichotomized Functional Response Regression")
    (description
     "Implementing Function-on-Scalar Regression model in which the response function
is dichotomized and observed sparsely.  This package provides smooth estimations
of functional regression coefficients and principal components for the
dichotomized functional response regression (dfrr) model.")
    (license license:gpl3)))

(define-public r-dfr
  (package
    (name "r-dfr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfr" version))
       (sha256
        (base32 "1n8k7v2hwcva8pjx3bxld87iy6crf0ca03d0pay1xcryf6knk3zp"))))
    (properties `((upstream-name . "dfr")))
    (build-system r-build-system)
    (propagated-inputs (list r-sgs r-matrix r-faux r-caret))
    (home-page "https://github.com/ff1201/dfr")
    (synopsis "Dual Feature Reduction for SGL")
    (description
     "Implementation of the Dual Feature Reduction (DFR) approach for the Sparse Group
Lasso (SGL) and the Adaptive Sparse Group Lasso (@code{aSGL}) (Feser and
Evangelou (2024) <doi:10.48550/@code{arXiv.2405.17094>}).  The DFR approach is a
feature reduction approach that applies strong screening to reduce the feature
space before optimisation, leading to speed-up improvements for fitting SGL
(Simon et al. (2013) <doi:10.1080/10618600.2012.681250>) and @code{aSGL}
(Mendez-Civieta et al. (2020) <doi:10.1007/s11634-020-00413-8> and Poignard
(2020) <doi:10.1007/s10463-018-0692-7>) models.  DFR is implemented using the
Adaptive Three Operator Splitting (ATOS) (Pedregosa and Gidel (2018)
<doi:10.48550/@code{arXiv.1804.02339>}) algorithm, with linear and logistic SGL
models supported, both of which can be fit using k-fold cross-validation.  Dense
and sparse input matrices are supported.")
    (license license:gpl3+)))

(define-public r-dfphase1
  (package
    (name "r-dfphase1")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfphase1" version))
       (sha256
        (base32 "0a9cxdc81rib84sgg5mpf28nhcv1g83kvnr7rin3djyv60ccrq8x"))))
    (properties `((upstream-name . "dfphase1")))
    (build-system r-build-system)
    (propagated-inputs (list r-robustbase r-rcpp r-lattice))
    (home-page "https://cran.r-project.org/package=dfphase1")
    (synopsis
     "Phase I Control Charts (with Emphasis on Distribution-Free Methods)")
    (description
     "Statistical methods for retrospectively detecting changes in location and/or
dispersion of univariate and multivariate variables.  Data values are assumed to
be independent, can be individual (one observation at each instant of time) or
subgrouped (more than one observation at each instant of time).  Control limits
are computed, often using a permutation approach, so that a prescribed false
alarm probability is guaranteed without making any parametric assumptions on the
stable (in-control) distribution.  See G. Capizzi and G. Masarotto (2018)
<doi:10.1007/978-3-319-75295-2_1> for an introduction to the package.")
    (license license:lgpl2.0+)))

(define-public r-dfped
  (package
    (name "r-dfped")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfped" version))
       (sha256
        (base32 "11ffsah14igba276m9d3cla0kgb3isizm5d7j1iqcd0wq23il7hq"))))
    (properties `((upstream-name . "dfped")))
    (build-system r-build-system)
    (propagated-inputs (list r-rstan r-ggplot2))
    (home-page "http://github.com/artemis-toumazi/dfped")
    (synopsis
     "Extrapolation and Bridging of Adult Information in Early Phase Dose-Finding Paediatrics Studies")
    (description
     "This package provides a unified method for designing and analysing dose-finding
trials in paediatrics, while bridging information from adults, is proposed in
the dfped package.  The dose range can be calculated under three extrapolation
methods: linear, allometry and maturation adjustment, using pharmacokinetic (PK)
data.  To do this, it is assumed that target exposures are the same in both
populations.  The working model and prior distribution parameters of the
dose-toxicity and dose-efficacy relationships can be obtained using early phase
adult toxicity and efficacy data at several dose levels through dfped package.
Priors are used into the dose finding process through a Bayesian model selection
or adaptive priors, to facilitate adjusting the amount of prior information to
differences between adults and children.  This calibrates the model to adjust
for misspecification if the adult and paediatric data are very different.  User
can use his/her own Bayesian model written in Stan code through the dfped
package.  A template of this model is proposed in the examples of the
corresponding R functions in the package.  Finally, in this package you can find
a simulation function for one trial or for more than one trial.  These methods
are proposed by Petit et al, (2016) <doi:10.1177/0962280216671348>.")
    (license license:gpl3+)))

(define-public r-dformula
  (package
    (name "r-dformula")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dformula" version))
       (sha256
        (base32 "1vylfnivkp4gv7wv7pjby918x3v8pnh0qds1hwmw5980na283qif"))))
    (properties `((upstream-name . "dformula")))
    (build-system r-build-system)
    (propagated-inputs (list r-formula-tools))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/serafinialessio/dformula")
    (synopsis "Data Manipulation using Formula")
    (description
     "This package provides a tool for manipulating data using the generic formula.  A
single formula allows to easily add, replace and remove variables before running
the analysis.")
    (license license:gpl2+)))

(define-public r-dforest
  (package
    (name "r-dforest")
    (version "0.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Dforest" version))
       (sha256
        (base32 "19jyph2zqfyq9vv22kb6fqy89l0vcviv19zgk10hbd7q850f6ryn"))))
    (properties `((upstream-name . "Dforest")))
    (build-system r-build-system)
    (propagated-inputs (list r-rpart r-ggplot2))
    (home-page "https://cran.r-project.org/package=Dforest")
    (synopsis "Decision Forest")
    (description
     "This package provides R-implementation of Decision forest algorithm, which
combines the predictions of multiple independent decision tree models for a
consensus decision.  In particular, Decision Forest is a novel
pattern-recognition method which can be used to analyze: (1) DNA microarray
data; (2) Surface-Enhanced Laser Desorption/Ionization Time-of-Flight Mass
Spectrometry (SELDI-TOF-MS) data; and (3) Structure-Activity Relation (SAR)
data.  In this package, three fundamental functions are provided, as
(1)DF_train, (2)DF_pred, and (3)DF_CV. run Dforest() to see more instructions.
Weida Tong (2003) <doi:10.1021/ci020058s>.")
    (license license:gpl2)))

(define-public r-dfoptim
  (package
    (name "r-dfoptim")
    (version "2023.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfoptim" version))
       (sha256
        (base32 "0c2ws249n8ib7fx8vp32l2hswicjxsds7xm1f4gcfky9cvcacdn4"))))
    (properties `((upstream-name . "dfoptim")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dfoptim")
    (synopsis "Derivative-Free Optimization")
    (description
     "Derivative-Free optimization algorithms.  These algorithms do not require
gradient information.  More importantly, they can be used to solve non-smooth
optimization problems.")
    (license license:gpl2+)))

(define-public r-dfoliatr
  (package
    (name "r-dfoliatr")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfoliatR" version))
       (sha256
        (base32 "0gl1acd5z67c2wkb806myr0ccm87waxdrnnjdq2wi8zndbc30j74"))))
    (properties `((upstream-name . "dfoliatR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-glue
                             r-ggpubr
                             r-ggplot2
                             r-forcats
                             r-dplyr
                             r-dplr))
    (native-inputs (list r-knitr))
    (home-page "https://chguiterman.github.io/dfoliatR/")
    (synopsis
     "Detection and Analysis of Insect Defoliation Signals in Tree Rings")
    (description
     "This package provides tools to identify, quantify, analyze, and visualize growth
suppression events in tree rings that are often produced by insect defoliation.
Described in Guiterman et al. (2020) <doi:10.1016/j.dendro.2020.125750>.")
    (license license:gpl3+)))

(define-public r-dfmta
  (package
    (name "r-dfmta")
    (version "1.7-6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfmta" version))
       (sha256
        (base32 "0g1fi9m9j5z43n9037qq2a4i88y3p3h2q00x3q3xvhzhnqc5lrns"))))
    (properties `((upstream-name . "dfmta")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppprogress r-rcpparmadillo r-rcpp r-bh))
    (home-page "https://cran.r-project.org/package=dfmta")
    (synopsis "Phase I/II Adaptive Dose-Finding Design for MTA")
    (description
     "Phase I/II adaptive dose-finding design for single-agent Molecularly Targeted
Agent (MTA), according to the paper \"Phase I/II Dose-Finding Design for
Molecularly Targeted Agent: Plateau Determination using Adaptive Randomization\",
Riviere Marie-Karelle et al. (2016) <doi:10.1177/0962280216631763>.")
    (license license:gpl3)))

(define-public r-dfms
  (package
    (name "r-dfms")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfms" version))
       (sha256
        (base32 "0p3fbvmrdrsiz3dy23i5fjldc7l5hwfh7v73sg8dkhvxxnn1ciw4"))))
    (properties `((upstream-name . "dfms")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-collapse))
    (native-inputs (list r-knitr))
    (home-page "https://sebkrantz.github.io/dfms/")
    (synopsis "Dynamic Factor Models")
    (description
     "Efficient estimation of Dynamic Factor Models using the Expectation Maximization
(EM) algorithm or Two-Step (2S) estimation, supporting datasets with missing
data.  The estimation options follow advances in the econometric literature:
either running the Kalman Filter and Smoother once with initial values from PCA
- 2S estimation as in Doz, Giannone and Reichlin (2011)
<doi:10.1016/j.jeconom.2011.02.012> - or via iterated Kalman Filtering and
Smoothing until EM convergence - following Doz, Giannone and Reichlin (2012)
<doi:10.1162/REST_a_00225> - or using the adapted EM algorithm of Banbura and
Modugno (2014) <doi:10.1002/jae.2306>, allowing arbitrary patterns of missing
data.  The implementation makes heavy use of the Armadillo C++ library and the
collapse package, providing for particularly speedy estimation.  A comprehensive
set of methods supports interpretation and visualization of the model as well as
forecasting.  Information criteria to choose the number of factors are also
provided - following Bai and Ng (2002) <doi:10.1111/1468-0262.00273>.")
    (license license:gpl3)))

(define-public r-dfmirror
  (package
    (name "r-dfmirror")
    (version "2.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfmirroR" version))
       (sha256
        (base32 "0npd9yllsjbb49mqdwaw75lbgx4lr8qgga70yybd6c16wdfkg396"))))
    (properties `((upstream-name . "dfmirroR")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-fitdistrplus r-e1071))
    (home-page "https://github.com/jacobpstein/dfmirroR")
    (synopsis
     "Simulate a Data Frame Mirroring an Input and Produce Shareable Simulation Code")
    (description
     "The @code{dfmirroR} package allows users to input a data frame, simulate some
number of observations based on specified columns of that data frame, and then
outputs a string that contains the code to re-create the simulation.  The goal
is to both provide workable test data sets and provide users with the
information they need to set up reproducible examples with team members.  This
package was created out of a need to share examples in cases where data are
private and where a full data frame is not needed for testing or coordinating.")
    (license license:expat)))

(define-public r-dfmeta
  (package
    (name "r-dfmeta")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfmeta" version))
       (sha256
        (base32 "0ca48adfhaxac33jmxbynlyg3ak9l5mmjhlr69n4hnz6325gn9vb"))))
    (properties `((upstream-name . "dfmeta")))
    (build-system r-build-system)
    (propagated-inputs (list r-plyr r-lme4 r-ggplot2 r-data-table))
    (home-page "http://github.com/artemis-toumazi/dfmeta")
    (synopsis "Meta-Analysis of Phase I Dose-Finding Early Clinical Trials")
    (description
     "Meta-analysis approaches for Phase I dose finding early phases clinical trials
in order to better suit requirements in terms of maximum tolerated dose (MTD)
and maximal dose regimen (MDR).  This package has currently three different
approaches: (a) an approach proposed by Zohar et al, 2011,
<doi:10.1002/sim.4121> (denoted as ZKO), (b) the Variance Weighted pooling
analysis (called @code{VarWT}) and (c) the Random Effects Model Based (REMB)
algorithm, where user can input his/her own model based approach or use the
existing random effect logistic regression model (named as glimem) through the
dfmeta package.")
    (license (list license:gpl3+
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-dfit
  (package
    (name "r-dfit")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DFIT" version))
       (sha256
        (base32 "1220ax93b9xwmq1crgl1fnf63gk72jqbra5b5q25wn6ynv1kilkx"))))
    (properties `((upstream-name . "DFIT")))
    (build-system r-build-system)
    (propagated-inputs (list r-simex r-mvtnorm r-msm r-mirt r-ggplot2))
    (home-page "https://cran.r-project.org/package=DFIT")
    (synopsis "Differential Functioning of Items and Tests")
    (description
     "This package provides a set of functions to perform Raju, van der Linden and
Fleer's (1995, <doi:10.1177/014662169501900405>) Differential Functioning of
Items and Tests (DFIT) analyses.  It includes functions to use the Monte Carlo
Item Parameter Replication approach (Oshima, Raju, & Nanda, 2006,
<doi:10.1111/j.1745-3984.2006.00001.x>) for obtaining the associated statistical
significance tests cut-off points.  They may also be used for a priori and
post-hoc power calculations (Cervantes, 2017, <doi:10.18637/jss.v076.i05>).")
    (license license:gpl2+)))

(define-public r-dfidx
  (package
    (name "r-dfidx")
    (version "0.1-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfidx" version))
       (sha256
        (base32 "0ygbw1z0v2s2w7d45b09x54xycfglpd1ipgkgxq8w2q004rkdp9d"))))
    (properties `((upstream-name . "dfidx")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-tidyselect
                             r-rdpack
                             r-pillar
                             r-glue
                             r-formula
                             r-dplyr))
    (native-inputs (list r-quarto))
    (home-page "https://cran.r-project.org/package=dfidx")
    (synopsis "Indexed Data Frames")
    (description
     "This package provides extended data frames, with a special data frame column
which contains two indexes, with potentially a nesting structure.")
    (license license:gpl2+)))

(define-public r-dfexpand
  (package
    (name "r-dfexpand")
    (version "0.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfexpand" version))
       (sha256
        (base32 "0rskd4bs9y56g5fh8dym11kj764pvlnx5lll5idybi67pjgv7b79"))))
    (properties `((upstream-name . "dfexpand")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr))
    (home-page "https://github.com/jlpainter/dfexpand")
    (synopsis
     "Automatically Expand Delimited Column Values into Multiple Binary Columns with 'dfexpand'")
    (description
     "This package implements an algorithm to effortlessly split a column in an R data
frame filled with multiple values separated by delimiters.  This automates the
process of creating separate columns for each unique value, transforming them
into binary outcomes.")
    (license license:gpl3+)))

(define-public r-dfdr
  (package
    (name "r-dfdr")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfdr" version))
       (sha256
        (base32 "1s7i11sl6m80hryggxby4c0knzk6nxqnlwfpzgg4a2bnqnwygfya"))))
    (properties `((upstream-name . "dfdr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-r6 r-purrr r-pryr))
    (home-page "https://cran.r-project.org/package=dfdr")
    (synopsis "Automatic Differentiation of Simple Functions")
    (description
     "Implementation of automatically computing derivatives of functions (see Mailund
Thomas (2017) <doi:10.1007/978-1-4842-2881-4>).  Moreover, calculating
gradients, Hessian and Jacobian matrices is possible.")
    (license license:gpl3)))

(define-public r-dfd
  (package
    (name "r-dfd")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DFD" version))
       (sha256
        (base32 "11nqhhngxhb2zk63zychkxi55jqrxr28yz4l9vin29hd391wqwzd"))))
    (properties `((upstream-name . "DFD")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-scales
                             r-gridextra
                             r-gprofiler2
                             r-ggpubr
                             r-ggplot2))
    (home-page "https://github.com/MohmedSoudy/DFD")
    (synopsis
     "Extract Drugs from Differential Expression Data from LINCS Database")
    (description
     "Get Drug information from given differential expression profile.  The package
search for the bioactive compounds from reference databases such as LINCS
containing the genome-wide gene expression signature (GES) from tens of
thousands of drug and genetic perturbations (Subramanian et al. (2017)
<DOI:10.1016/j.cell.2017.10.049>).")
    (license license:gpl3)))

(define-public r-dfcrm
  (package
    (name "r-dfcrm")
    (version "0.2-2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfcrm" version))
       (sha256
        (base32 "01rn3zvi9xljmx48lkclckhnixian1vwq1frr8n784dsclp86spg"))))
    (properties `((upstream-name . "dfcrm")))
    (build-system r-build-system)
    (home-page "http://www.columbia.edu/~yc632")
    (synopsis "Dose-Finding by the Continual Reassessment Method")
    (description
     "This package provides functions to run the CRM and TITE-CRM in phase I trials
and calibration tools for trial planning purposes.")
    (license license:gpl2)))

(define-public r-dfcompare
  (package
    (name "r-dfcompare")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfCompare" version))
       (sha256
        (base32 "1lhx69j0bkjbnp5jz23hrbxjcf04vf3big4k593ixz003xs2077f"))))
    (properties `((upstream-name . "dfCompare")))
    (build-system r-build-system)
    (home-page "https://github.com/swaldroff/DFCompare")
    (synopsis "Compare Two Dataframes and Return Adds, Changes, and Deletes")
    (description
     "Compares two dataframes with a common key and returns the delta records.  The
package will return three dataframes that contain the added, changed, and
deleted records.")
    (license license:gpl3)))

(define-public r-dfcomb
  (package
    (name "r-dfcomb")
    (version "3.1-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfcomb" version))
       (sha256
        (base32 "1h5x9759ljlyv9h7bmybm2ygw60ivnfrqc1f7drx700m71cwc6kk"))))
    (properties `((upstream-name . "dfcomb")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppprogress r-rcpp r-bh))
    (home-page "https://cran.r-project.org/package=dfcomb")
    (synopsis
     "Phase I/II Adaptive Dose-Finding Design for Combination Studies")
    (description
     "Phase I/II adaptive dose-finding design for combination studies where toxicity
rates are supposed to increase with both agents.")
    (license license:gpl3)))

(define-public r-dfba
  (package
    (name "r-dfba")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DFBA" version))
       (sha256
        (base32 "12ywksp6zb2xkxvpmnvjpan9wllfzhngvwnsw6813z11jdhrhnpr"))))
    (properties `((upstream-name . "DFBA")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DFBA")
    (synopsis "Distribution-Free Bayesian Analysis")
    (description
     "This package provides a set of functions to perform distribution-free Bayesian
analyses.  Included are Bayesian analogues to the frequentist Mann-Whitney U
test, the Wilcoxon Signed-Ranks test, Kendall's Tau Rank Correlation
Coefficient, Goodman and Kruskal's Gamma, @code{McNemar's} Test, the binomial
test, the sign test, the median test, as well as distribution-free methods for
testing contrasts among condition and for computing Bayes factors for
hypotheses.  The package also includes procedures to estimate the power of
distribution-free Bayesian tests based on data simulations using various
probability models for the data.  The set of functions provide data analysts
with a set of Bayesian procedures that avoids requiring parametric assumptions
about measurement error and is robust to problem of extreme outlier scores.")
    (license license:gpl2)))

(define-public r-dfadjust
  (package
    (name "r-dfadjust")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dfadjust" version))
       (sha256
        (base32 "0x44alfb0ryd7m0y2gqq7sqhyf6yzk4pcwb129d2qazhwya6p2y5"))))
    (properties `((upstream-name . "dfadjust")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page
     "https://github.com/kolesarm/Robust-Small-Sample-Standard-Errors")
    (synopsis "Degrees of Freedom Adjustment for Robust Standard Errors")
    (description
     "Computes small-sample degrees of freedom adjustment for heteroskedasticity
robust standard errors, and for clustered standard errors in linear regression.
See Imbens and KolesÃ¡r (2016) <doi:10.1162/REST_a_00552> for a discussion of
these adjustments.")
    (license license:expat)))

(define-public r-dfa-cancor
  (package
    (name "r-dfa-cancor")
    (version "0.2.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DFA.CANCOR" version))
       (sha256
        (base32 "1i0bf9w4f0djwqsmwjiyfxnvsj220bmk4vfvz3l4l0wmdxil9cda"))))
    (properties `((upstream-name . "DFA.CANCOR")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvn r-bayesfactor))
    (home-page "https://cran.r-project.org/package=DFA.CANCOR")
    (synopsis
     "Linear Discriminant Function and Canonical Correlation Analysis")
    (description
     "This package produces SPSS- and SAS-like output for linear discriminant function
analysis and canonical correlation analysis.  The methods are described in Manly
& Alberto (2017, ISBN:9781498728966), Rencher (2002, ISBN:0-471-41889-7), and
Tabachnik & Fidell (2019, ISBN:9780134790541).")
    (license license:gpl2+)))

(define-public r-dfa
  (package
    (name "r-dfa")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DFA" version))
       (sha256
        (base32 "1ilfkwn8r841byl1kn7rn2d6jdda3r7mm7ixvvyx6szqbmyhp8zd"))))
    (properties `((upstream-name . "DFA")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DFA")
    (synopsis "Detrended Fluctuation Analysis")
    (description
     "Containing the Detrended Fluctuation Analysis (DFA), Detrended Cross-Correlation
Analysis (DCCA), Detrended Cross-Correlation Coefficient (@code{rhoDCCA}), Delta
Amplitude Detrended Cross-Correlation Coefficient (@code{DeltarhoDCCA}), log
amplitude Detrended Fluctuation Analysis (@code{DeltalogDFA}), and the Activity
Balance Index, it also includes two DFA automatic methods for identifying
crossover points and a Deltalog automatic method for identifying reference
channels.")
    (license license:asl2.0)))

(define-public r-df2yaml
  (package
    (name "r-df2yaml")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "df2yaml" version))
       (sha256
        (base32 "1ni61pf7sjwvgbfvwy91n6fbs6aa5vviq0xy6jsgddbwrk9diigj"))))
    (properties `((upstream-name . "df2yaml")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-tibble
                             r-rrapply
                             r-rlang
                             r-magrittr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=df2yaml")
    (synopsis "Convert Dataframe to 'YAML'")
    (description
     "The df2yaml aims to simplify the process of converting dataframe to YAML
<https://yaml.org/>.  The dataframe with multiple key columns and one value
column will be converted to the multi-level hierarchy.")
    (license license:expat)))

(define-public r-dextermst
  (package
    (name "r-dextermst")
    (version "0.9.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dexterMST" version))
       (sha256
        (base32 "073xx30gavig6nhi6ppll7jdgf7yvci8nv6pyxcy9vl177l1k62b"))))
    (properties `((upstream-name . "dexterMST")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rsqlite
                             r-rlang
                             r-rcpparmadillo
                             r-rcpp
                             r-igraph
                             r-dplyr
                             r-dexter
                             r-dbi
                             r-crayon))
    (native-inputs (list r-knitr))
    (home-page "https://dexter-psychometrics.github.io/dexter/")
    (synopsis "CML and Bayesian Calibration of Multistage Tests")
    (description
     "Conditional Maximum Likelihood Calibration and data management of multistage
tests.  Supports polytomous items and incomplete designs with linear as well as
multistage tests.  Extended Nominal Response and Interaction models, DIF and
profile analysis.  See Robert J. Zwitser and Gunter Maris
(2015)<doi:10.1007/s11336-013-9369-6>.")
    (license license:lgpl3)))

(define-public r-dextergui
  (package
    (name "r-dextergui")
    (version "0.2.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dextergui" version))
       (sha256
        (base32 "10v3djwani0zd27cjlf7lch7rfipnmb2p5wa7n2y5qxjqxli9z3x"))))
    (properties `((upstream-name . "dextergui")))
    (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-writexl
                             r-tidyr
                             r-tibble
                             r-shinyjs
                             r-shinyfiles
                             r-shinybs
                             r-shiny
                             r-rlang
                             r-readxl
                             r-readods
                             r-rcurl
                             r-networkd3
                             r-jsonlite
                             r-htmlwidgets
                             r-htmltools
                             r-ggridges
                             r-ggplot2
                             r-ggextra
                             r-dt
                             r-dplyr
                             r-dexter
                             r-dbi
                             r-cairo))
    (native-inputs (list r-knitr esbuild))
    (home-page "https://dexter-psychometrics.github.io/dexter/")
    (synopsis "Graphical User Interface for Dexter")
    (description
     "Classical Test and Item analysis, Item Response analysis and data management for
educational and psychological tests.")
    (license license:gpl3)))

(define-public r-dexter
  (package
    (name "r-dexter")
    (version "1.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dexter" version))
       (sha256
        (base32 "1sppaqnv9nkxww0bw0x2sp51fl4v7845npvmhwwdh4yrnrmzbd07"))))
    (properties `((upstream-name . "dexter")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-sitmo
                             r-rsqlite
                             r-rlang
                             r-rcpparmadillo
                             r-rcpp
                             r-mass
                             r-dqrng
                             r-dplyr
                             r-dbi
                             r-bh))
    (native-inputs (list r-knitr))
    (home-page "https://dexter-psychometrics.github.io/dexter/")
    (synopsis "Data Management and Analysis of Tests")
    (description
     "This package provides a system for the management, assessment, and psychometric
analysis of data from educational and psychological tests.")
    (license license:lgpl3)))

(define-public r-dexir
  (package
    (name "r-dexir")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DEXiR" version))
       (sha256
        (base32 "1a1z5pcw6mcm04fww498mbxxv677wk00dv9xhgniixasnnsmmysl"))))
    (properties `((upstream-name . "DEXiR")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2 r-stringr))
    (home-page "https://cran.r-project.org/package=DEXiR")
    (synopsis "'DEXi' Library")
    (description
     "This package provides a software package for using DEXi models.  DEXi models are
hierarchical qualitative multi-criteria decision models developed according to
the method DEX (Decision EXpert,
<https://dex.ijs.si/documentation/DEX_Method/DEX_Method.html>), using the
program DEXi (<https://kt.ijs.si/@code{MarkoBohanec/dexi.html>}) or
DE@code{XiWin} (<https://dex.ijs.si/dexisuite/dexiwin.html>).  A typical
workflow with DE@code{XiR} consists of: (1) reading a .dxi file, previously made
using the DEXi software (function read_dexi()), (2) making a data frame
containing input values of one or more decision alternatives, (3) evaluating
those alternatives (function evaluate()), (4) analyzing alternatives
(selective_explanation(), plus_minus(), compare_alternatives()), (5) drawing
charts.  DE@code{XiR} is restricted to using models produced externally by the
DEXi software and does not provide functionality for creating and/or editing
DEXi models directly in R'.")
    (license license:expat)))

(define-public r-devtreatrules
  (package
    (name "r-devtreatrules")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DevTreatRules" version))
       (sha256
        (base32 "1h4p78mwl5ir31hfb38x1dwq5xxbdlsasvk5vxa3c7xdvhsd2yrf"))))
    (properties `((upstream-name . "DevTreatRules")))
    (build-system r-build-system)
    (propagated-inputs (list r-modelobj r-glmnet r-dyntxregime))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DevTreatRules")
    (synopsis "Develop Treatment Rules with Observational Data")
    (description
     "Develop and evaluate treatment rules based on: (1) the standard indirect
approach of split-regression, which fits regressions separately in both
treatment groups and assigns an individual to the treatment option under which
predicted outcome is more desirable; (2) the direct approach of
outcome-weighted-learning proposed by Yingqi Zhao, Donglin Zeng, A. John Rush,
and Michael Kosorok (2012) <doi:10.1080/01621459.2012.695674>; (3) the direct
approach, which we refer to as direct-interactions, proposed by Shuai Chen, Lu
Tian, Tianxi Cai, and Menggang Yu (2017) <doi:10.1111/biom.12676>.  Please see
the vignette for a walk-through of how to start with an observational dataset
whose design is understood scientifically and end up with a treatment rule that
is trustworthy statistically, along with an estimation of rule benefit in an
independent sample.")
    (license license:gpl2+)))

(define-public r-devrate
  (package
    (name "r-devrate")
    (version "0.2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "devRate" version))
       (sha256
        (base32 "06060wxji3mfwq6c58gmb07mz9sk9d5ls9d152vywjnz20ndpscd"))))
    (properties `((upstream-name . "devRate")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/frareb/devRate/")
    (synopsis
     "Quantify the Relationship Between Development Rate and Temperature in Ectotherms")
    (description
     "This package provides a set of functions to quantify the relationship between
development rate and temperature and to build phenological models.  The package
comprises a set of models and estimated parameters borrowed from a literature
review in ectotherms.  The methods and literature review are described in
Rebaudo et al. (2018) <doi:10.1111/2041-210X.12935>, Rebaudo and Rabhi (2018)
<doi:10.1111/eea.12693>, and Regnier et al. (2021) <doi:10.1093/ee/nvab115>.  An
example can be found in Rebaudo et al. (2017) <doi:10.1007/s13355-017-0480-5>.")
    (license license:gpl2)))

(define-public r-devore7
  (package
    (name "r-devore7")
    (version "0.7.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Devore7" version))
       (sha256
        (base32 "1m18p8h9vv4v0aq2fkjyj39vzb8a09azbbczhfiv4y88w540i8nw"))))
    (properties `((upstream-name . "Devore7")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-lattice))
    (home-page "https://cran.r-project.org/package=Devore7")
    (synopsis "Data sets from Devore's \"Prob and Stat for Eng (7th ed)\"")
    (description
     "Data sets and sample analyses from Jay L. Devore (2008), \"Probability and
Statistics for Engineering and the Sciences (7th ed)\", Thomson.")
    (license license:gpl2+)))

(define-public r-devoid
  (package
    (name "r-devoid")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "devoid" version))
       (sha256
        (base32 "1hdqww5al3wv3jncfj8zqwypv487hc4pdb1d4f1c3w68fp0b1zni"))))
    (properties `((upstream-name . "devoid")))
    (build-system r-build-system)
    (home-page "https://github.com/r-lib/devoid")
    (synopsis "Graphic Device that Does Nothing")
    (description
     "This package provides a non-drawing graphic device for benchmarking purpose.  In
order to properly benchmark graphic drawing code it is necessary to factor out
the device implementation itself so that results are not related to the specific
graphics device used during benchmarking.  The devoid package implements a
graphic device that accepts all the required calls from R's graphic engine but
performs no action.  Apart from benchmarking it is unlikely that this device has
any practical use.")
    (license license:expat)))

(define-public r-devfunc
  (package
    (name "r-devfunc")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "devFunc" version))
       (sha256
        (base32 "0f2s5gssk9napmah7zcss1rnh7pzlq90gzwcnvyr9rrq6k118n8q"))))
    (properties `((upstream-name . "devFunc")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-plyr))
    (home-page "https://cran.r-project.org/package=devFunc")
    (synopsis "Clear and Condense Argument Check for User-Defined Functions")
    (description
     "This package provides a concise check of the format of one or multiple input
arguments (data type, length or value) is provided.  Since multiple input
arguments can be tested simultaneously, a lengthly list of checks at the
beginning of your function can be avoided, hereby enhancing the readability and
maintainability of your code.")
    (license license:gpl3)))

(define-public r-devemf
  (package
    (name "r-devemf")
    (version "4.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "devEMF" version))
       (sha256
        (base32 "03iwl6h6f158qc2i5b0ac9g1nnspqr958cvprjm4rgs1pcywplga"))))
    (properties `((upstream-name . "devEMF")))
    (build-system r-build-system)
    (native-inputs (list pkg-config))
    (home-page "https://github.com/plfjohnson/devEMF")
    (synopsis "EMF Graphics Output Device")
    (description "Output graphics to EMF+/EMF.")
    (license license:gpl3)))

(define-public r-detzrcr
  (package
    (name "r-detzrcr")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "detzrcr" version))
       (sha256
        (base32 "0afi1ir8il5xmzkpmbc2m5mvmgzlqw8qdn04gbnwl74a03yaxxmj"))))
    (properties `((upstream-name . "detzrcr")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-mass r-ggplot2 r-dt))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/magnuskristoffersen/detzrcr")
    (synopsis "Compare Detrital Zircon Suites")
    (description
     "Compare detrital zircon suites by uploading univariate, U-Pb age, or bivariate,
U-Pb age and Lu-Hf data, in a shiny'-based user-interface.  Outputs publication
quality figures using ggplot2', and tables of statistics currently in use in the
detrital zircon geochronology community.")
    (license license:gpl3)))

(define-public r-dets
  (package
    (name "r-dets")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deTS" version))
       (sha256
        (base32 "08yq7vfcd8fv8qw2w0f1rnj3rzys9kslmkqspmiz6prmzqvj1zf1"))))
    (properties `((upstream-name . "deTS")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer r-pheatmap))
    (home-page "https://cran.r-project.org/package=deTS")
    (synopsis "Tissue-Specific Enrichment Analysis")
    (description
     "Tissue-specific enrichment analysis to assess lists of candidate genes or
RNA-Seq expression profiles.  Pei G., Dai Y., Zhao Z. Jia P. (2019) @code{deTS}:
Tissue-Specific Enrichment Analysis to decode tissue specificity.
Bioinformatics, In submission.")
    (license license:gpl2+)))

(define-public r-detrendr
  (package
    (name "r-detrendr")
    (version "0.6.15")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "detrendr" version))
       (sha256
        (base32 "00j35i45a55srvdlhv0b9vcrsp44fmdv49giqm03ha015pgmsbdd"))))
    (properties `((upstream-name . "detrendr")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr
                             r-stringr
                             r-rlang
                             r-rcppparallel
                             r-rcpp
                             r-purrr
                             r-plyr
                             r-magrittr
                             r-iterators
                             r-ijtiff
                             r-foreach
                             r-filesstrings
                             r-dplyr
                             r-doparallel
                             r-checkmate
                             r-autothresholdr
                             r-arrayhelpers))
    (native-inputs (list r-knitr))
    (home-page "https://rorynolan.github.io/detrendr/")
    (synopsis "Detrend Images")
    (description
     "Detrend fluorescence microscopy image series for fluorescence fluctuation and
correlation spectroscopy ('FCS and FFS') analysis.  This package contains
functionality published in a 2016 paper <doi:10.1093/bioinformatics/btx434> but
it has been extended since then with the Robin Hood algorithm and thus contains
unpublished work.")
    (license license:bsd-3)))

(define-public r-detrender
  (package
    (name "r-detrender")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "detrendeR" version))
       (sha256
        (base32 "1kx404z0xp22d1jhpn217l8wcn6p587by908a6465dfpkhc8vyyb"))))
    (properties `((upstream-name . "detrendeR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tkrplotr r-dplr))
    (home-page "https://cran.r-project.org/package=detrendeR")
    (synopsis
     "Graphical User Interface (GUI) to Visualize and Analyze Dendrochronological Data")
    (description
     "This package provides a Graphical User Interface (GUI) to import, save, detrend
and perform standard tree-ring analyses.  The interactive detrending allows the
user to check how well the detrending curve fits each time-series and change it
when needed.")
    (license license:gpl2+)))

(define-public r-detr
  (package
    (name "r-detr")
    (version "0.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DetR" version))
       (sha256
        (base32 "1dd4nzkgj5pl9397aa0z3q5fpl27xbdf7q0pqbs821dyynylxzn9"))))
    (properties `((upstream-name . "DetR")))
    (build-system r-build-system)
    (propagated-inputs (list r-robustbase r-rcppeigen r-rcpp r-pcapp r-mass))
    (home-page "https://cran.r-project.org/package=DetR")
    (synopsis
     "Suite of Deterministic and Robust Algorithms for Linear Regression")
    (description
     "@code{DetLTS}, @code{DetMM} (and @code{DetS}) Algorithms for Deterministic,
Robust Linear Regression.")
    (license license:gpl2+)))

(define-public r-detpack
  (package
    (name "r-detpack")
    (version "1.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "detpack" version))
       (sha256
        (base32 "1mk2k9akagz7knd4n5p8nxkmnm2mdv9izk4i5yl2v9nv5v39mc4h"))))
    (properties `((upstream-name . "detpack")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=detpack")
    (synopsis
     "Density Estimation and Random Number Generation with Distribution Element Trees")
    (description
     "Density estimation for possibly large data sets and conditional/unconditional
random number generation or bootstrapping with distribution element trees.  The
function det.construct translates a dataset into a distribution element tree.
To evaluate the probability density based on a previously computed tree at
arbitrary query points, the function det.query is available.  The functions det1
and det2 provide density estimation and plotting for one- and two-dimensional
datasets.  Conditional/unconditional smooth bootstrapping from an available
distribution element tree can be performed by det.rnd'.  For more details on
distribution element trees, see: Meyer, D.W. (2016) <@code{arXiv:1610.00345>} or
Meyer, D.W., Statistics and Computing (2017) <doi:10.1007/s11222-017-9751-9> and
Meyer, D.W. (2017) <@code{arXiv:1711.04632>} or Meyer, D.W., Journal of
Computational and Graphical Statistics (2018)
<doi:10.1080/10618600.2018.1482768>.")
    (license license:gpl2)))

(define-public r-detourr
  (package
    (name "r-detourr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "detourr" version))
       (sha256
        (base32 "1kic6a5s8wm59za9zr8n2z33kfvahgfaa0izy2lp4j75am0jxlra"))))
    (properties `((upstream-name . "detourr")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridislite
                             r-tourr
                             r-tidyselect
                             r-tibble
                             r-rlang
                             r-purrr
                             r-htmlwidgets))
    (home-page "https://casperhart.github.io/detourr/")
    (synopsis "Portable and Performant Tour Animations")
    (description
     "This package provides 2D and 3D tour animations as HTML widgets.  The user can
interact with the widgets using orbit controls, tooltips, brushing, and timeline
controls.  Linked brushing is supported using crosstalk', and widgets can be
embedded in Shiny apps or HTML documents.")
    (license license:expat)))

(define-public r-detmcd
  (package
    (name "r-detmcd")
    (version "0.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DetMCD" version))
       (sha256
        (base32 "034wb5hwpikli6h2rwiqr19qvzxrr4qwi4q436y7c5a5wgkfzgl5"))))
    (properties `((upstream-name . "DetMCD")))
    (build-system r-build-system)
    (propagated-inputs (list r-robustbase r-rcppeigen r-rcpp r-pcapp))
    (home-page "https://cran.r-project.org/package=DetMCD")
    (synopsis
     "Implementation of the DetMCD Algorithm (Robust and Deterministic Estimation of Location and Scatter)")
    (description
     "Implementation of @code{DetMCD}, a new algorithm for robust and deterministic
estimation of location and scatter.  The benefits of robust and deterministic
estimation are explained in Hubert, Rousseeuw and Verdonck (2012)
<doi:10.1080/10618600.2012.672100>.")
    (license license:gpl2+)))

(define-public r-detlifeinsurance
  (package
    (name "r-detlifeinsurance")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DetLifeInsurance" version))
       (sha256
        (base32 "15yh66mn84cm5ix99lg5lp783dp8il03dyirkhil7m5pwzss42r4"))))
    (properties `((upstream-name . "DetLifeInsurance")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/JoaquinAuza/DetLifeInsurance")
    (synopsis "Life Insurance Premium and Reserves Valuation")
    (description
     "This package provides methods for valuation of life insurance premiums and
reserves (including variable-benefit and fractional coverage) based on
\"Actuarial Mathematics\" by Bowers, H.U. Gerber, J.C. Hickman, D.A. Jones and
C.J. Nesbitt (1997, ISBN: 978-0938959465), \"Actuarial Mathematics for Life
Contingent Risks\" by Dickson, David C. M., Hardy, Mary R. and Waters, Howard R
(2009) <doi:10.1017/CBO9780511800146> and \"Life Contingencies\" by Jordan, C. W
(1952) <doi:10.1017/S002026810005410X>.  It also contains functions for
equivalent interest and discount rate calculation, present and future values of
annuities, and loan amortization schedule.")
    (license license:gpl3)))

(define-public r-detectruns
  (package
    (name "r-detectruns")
    (version "0.9.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "detectRUNS" version))
       (sha256
        (base32 "0yl1x0jz66hingbl094picsiyrxzxvnz0grq63rva6nwn7pv1c0b"))))
    (properties `((upstream-name . "detectRUNS")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2
                             r-rcpp
                             r-plyr
                             r-itertools
                             r-iterators
                             r-gridextra
                             r-ggplot2
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page
     "https://github.com/bioinformatics-ptp/detectRUNS/tree/master/detectRUNS")
    (synopsis
     "Detect Runs of Homozygosity and Runs of Heterozygosity in Diploid Genomes")
    (description
     "Detection of runs of homozygosity and of heterozygosity in diploid genomes using
two methods: sliding windows (Purcell et al (2007) <doi:10.1086/519795>) and
consecutive runs (Marras et al (2015) <doi:10.1111/age.12259>).")
    (license license:gpl3)))

(define-public r-detectr
  (package
    (name "r-detectr")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "detectR" version))
       (sha256
        (base32 "002wv6krzmpikfmcn5bw12y7acbwvbf057i31jhsqj081spdicb0"))))
    (properties `((upstream-name . "detectR")))
    (build-system r-build-system)
    (propagated-inputs (list r-signal
                             r-logconcdead
                             r-lavaan
                             r-glasso
                             r-foreach
                             r-doparallel))
    (home-page "https://github.com/crbaek/detectR")
    (synopsis "Change Point Detection")
    (description
     "Time series analysis of network connectivity.  Detects and visualizes change
points between networks.  Methods included in the package are discussed in depth
in Baek, C., Gates, K. M., Leinwand, B., Pipiras, V. (2021) \"Two sample tests
for high-dimensional auto-covariances\" <doi:10.1016/j.csda.2020.107067> and
Baek, C., Gampe, M., Leinwand B., Lindquist K., Hopfinger J. and Gates K. (2023)
âDetecting functional connectivity changes in @code{fMRI} dataâ
<doi:10.1007/s11336-023-09908-7>.")
    (license (license:fsdg-compatible "Unlimited"))))

(define-public r-detectors
  (package
    (name "r-detectors")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "detectors" version))
       (sha256
        (base32 "0bi14jv2za3a5xanqchzs7qpm71syaw5j1lcs5q2fc5hbyfp0lvw"))))
    (properties `((upstream-name . "detectors")))
    (build-system r-build-system)
    (home-page "https://simonpcouch.github.io/detectors/")
    (synopsis "Prediction Data from GPT Detectors")
    (description
     "Researchers carried out a series of experiments passing a number of essays to
different GPT detection models.  Juxtaposing detector predictions for papers
written by native and non-native English writers, the authors argue that GPT
detectors disproportionately classify real writing from non-native English
writers as AI-generated.")
    (license license:expat)))

(define-public r-detector
  (package
    (name "r-detector")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "detector" version))
       (sha256
        (base32 "010i063b94hzx7qac8gpl67gmk7hzgqm9i1c7pbbw4la3wcd9lz7"))))
    (properties `((upstream-name . "detector")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr))
    (home-page "https://github.com/paulhendricks/detector")
    (synopsis "Detect Data Containing Personally Identifiable Information")
    (description
     "Allows users to quickly and easily detect data containing Personally
Identifiable Information (PII) through convenience functions.")
    (license license:expat)))

(define-public r-detectnorm
  (package
    (name "r-detectnorm")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "detectnorm" version))
       (sha256
        (base32 "1cr5i73iigmsg0ywlm61iv1yw91vafbbf4dhvcd448qnv05cjlaw"))))
    (properties `((upstream-name . "detectnorm")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncnorm r-rdpack r-psych r-nleqslv r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/irissun/detectnorm")
    (synopsis "Detect Nonnormality in Meta-Analysis without Raw Data")
    (description
     "Non-normality could greatly distort the meta-analytic results, according to the
simulation in Sun and Cheung (2020) <doi: 10.3758/s13428-019-01334-x>.  This
package aims to detect non-normality for two independent groups with only
limited descriptive statistics, including mean, standard deviation, minimum, and
maximum.")
    (license license:expat)))

(define-public r-detect
  (package
    (name "r-detect")
    (version "0.4-6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "detect" version))
       (sha256
        (base32 "10cfpmps2r0zcdqskzacflpz8g4wy2cfx920flr93lxmrb6i57sv"))))
    (properties `((upstream-name . "detect")))
    (build-system r-build-system)
    (propagated-inputs (list r-pbapply r-matrix r-formula))
    (home-page "https://github.com/psolymos/detect")
    (synopsis "Analyzing Wildlife Data with Detection Error")
    (description
     "Models for analyzing site occupancy and count data models with detection error,
including single-visit based models, conditional distance sampling and
time-removal models.  Package development was supported by the Alberta
Biodiversity Monitoring Institute and the Boreal Avian Modelling Project.")
    (license license:gpl2)))

(define-public r-details
  (package
    (name "r-details")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "details" version))
       (sha256
        (base32 "0mygkmfmfp3a2hgql514zyh4rw3v8i4g4cls6rss0fplg4pskwc7"))))
    (properties `((upstream-name . "details")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-withr
                             r-png
                             r-magrittr
                             r-knitr
                             r-httr
                             r-htmltools
                             r-desc
                             r-clipr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/yonicd/details")
    (synopsis "Create Details HTML Tag for Markdown and Package Documentation")
    (description
     "Create a details HTML tag around R objects to place in a Markdown, Rmarkdown and
roxygen2 documentation.")
    (license license:expat)))

(define-public r-desplot
  (package
    (name "r-desplot")
    (version "1.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "desplot" version))
       (sha256
        (base32 "1994fqd9d1g314bj0qx7gcb6qmv38gl2brc2gwms3zy4r4b86f57"))))
    (properties `((upstream-name . "desplot")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-reshape2 r-lattice r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://kwstat.github.io/desplot/")
    (synopsis "Plotting Field Plans for Agricultural Experiments")
    (description
     "This package provides a function for plotting maps of agricultural field
experiments that are laid out in grids.  See Ryder (1981)
<doi:10.1017/S0014479700011601>.")
    (license license:gpl3)))

(define-public r-despair
  (package
    (name "r-despair")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "despair" version))
       (sha256
        (base32 "03lsyfqbywrqa8jnnybjvacgmxy12kqnsql8y7iqmh770i602qp1"))))
    (properties `((upstream-name . "despair")))
    (build-system r-build-system)
    (home-page "https://github.com/jpmonteagudo28/despair")
    (synopsis
     "Motivational Quotes and Shakespearean Bardâbits for Personal Projects")
    (description
     "Generate motivational quotes and Shakespearean word combinations (bardâbits)
that a user can consider for their personal projects.  Each of the package
functions takes two arguments, cat which default to any, and a a numeric or
character seed to ensure reproducible results.")
    (license license:gpl3+)))

(define-public r-desla
  (package
    (name "r-desla")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "desla" version))
       (sha256
        (base32 "18q1rw8p69p5jcqxb4hryyn2bak6pjmx91g203xrilx7k1za4p23"))))
    (properties `((upstream-name . "desla")))
    (build-system r-build-system)
    (propagated-inputs (list r-sitmo
                             r-rdpack
                             r-rcppprogress
                             r-rcpparmadillo
                             r-rcpp
                             r-parallelly))
    (home-page "https://github.com/RobertAdamek/desla")
    (synopsis "Desparsified Lasso Inference for Time Series")
    (description
     "Calculates the desparsified lasso as originally introduced in van de Geer et al.
(2014) <doi:10.1214/14-AOS1221>, and provides inference suitable for
high-dimensional time series, based on the long run covariance estimator in
Adamek et al. (2020) <@code{arXiv:2007.10952>}.  Also estimates high-dimensional
local projections by the desparsified lasso, as described in Adamek et al.
(2022) <@code{arXiv:2209.03218>}.")
    (license license:gpl2+)))

(define-public r-desk
  (package
    (name "r-desk")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "desk" version))
       (sha256
        (base32 "0pv54lxd326xlwscyngrfmvqf8inqqg587bi4n42wy6c76p4kbm5"))))
    (properties `((upstream-name . "desk")))
    (build-system r-build-system)
    (propagated-inputs (list r-rstudioapi r-cli))
    (home-page "https://github.com/OvGU-SH/desk")
    (synopsis "Didactic Econometrics Starter Kit")
    (description
     "Written to help undergraduate as well as graduate students to get started with R
for basic econometrics without the need to import specific functions and
datasets from many different sources.  Primarily, the package is meant to
accompany the German textbook Auer, L.v., Hoffmann, S., Kranz, T. (2023, ISBN:
978-3-662-68263-0) from which the exercises cover all the topics from the
textbook Auer, L.v. (2023, ISBN: 978-3-658-42699-6).")
    (license license:gpl3+)))

(define-public r-desirability2
  (package
    (name "r-desirability2")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "desirability2" version))
       (sha256
        (base32 "0x5v6mak68h6a03hccf8gksj3wmgcd3l84bplx1s4jr755wdm5ih"))))
    (properties `((upstream-name . "desirability2")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-rlang r-purrr r-glue))
    (home-page "https://desirability2.tidymodels.org")
    (synopsis "Desirability Functions for Multiparameter Optimization")
    (description
     "In-line functions for multivariate optimization via desirability functions
(Derringer and Suich, 1980, <doi:10.1080/00224065.1980.11980968>) with easy use
within dplyr pipelines.")
    (license license:expat)))

(define-public r-desirability
  (package
    (name "r-desirability")
    (version "2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "desirability" version))
       (sha256
        (base32 "094gxvp6a60lfcc0a0gk9rv1p6ajnzq9m58sy8cvhcj5337g4fmk"))))
    (properties `((upstream-name . "desirability")))
    (build-system r-build-system)
    (home-page "https://github.com/topepo/desirability")
    (synopsis "Function Optimization and Ranking via Desirability Functions")
    (description
     "S3 classes for multivariate optimization using the desirability function by
Derringer and Suich (1980).")
    (license license:gpl2)))

(define-public r-desir
  (package
    (name "r-desir")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "desiR" version))
       (sha256
        (base32 "149wgg5mbq95wizpc24mwb8qfxjdia4qkz66bnzjgiiyfh6r46wp"))))
    (properties `((upstream-name . "desiR")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/stanlazic/desiR")
    (synopsis
     "Desirability Functions for Ranking, Selecting, and Integrating Data")
    (description
     "This package provides functions for (1) ranking, selecting, and prioritising
genes, proteins, and metabolites from high dimensional biology experiments, (2)
multivariate hit calling in high content screens, and (3) combining data from
diverse sources.")
    (license license:gpl3)))

(define-public r-designsize
  (package
    (name "r-designsize")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "designsize" version))
       (sha256
        (base32 "1c9b320vssw3s1ybyialg5s85k1vfllbw40qfgmvnsr3imc2inb2"))))
    (properties `((upstream-name . "designsize")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=designsize")
    (synopsis "Sample Size Calculation of Various Study Designs")
    (description
     "Different sample size calculations with different study designs.  These
techniques are explained by Chow (2007) <doi:10.1201/9781584889830>.")
    (license license:gpl3)))

(define-public r-designr
  (package
    (name "r-designr")
    (version "0.1.13")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "designr" version))
       (sha256
        (base32 "13rj2xxxxj35zl7q570c3i4p2wjpxf79dza0sg9bhbq3yal6j6r2"))))
    (properties `((upstream-name . "designr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-mass r-lme4 r-dplyr r-crossdes))
    (native-inputs (list r-knitr))
    (home-page "https://maxrabe.com/designr")
    (synopsis "Balanced Factorial Designs")
    (description
     "Generate balanced factorial designs with crossed and nested random and fixed
effects <https://github.com/mmrabe/designr>.")
    (license license:gpl3)))

(define-public r-designmatch
  (package
    (name "r-designmatch")
    (version "0.5.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "designmatch" version))
       (sha256
        (base32 "1x3pcwml6pa56ij2bc9jymfp066v7fd2avjl6awgpy3503qr56q1"))))
    (properties `((upstream-name . "designmatch")))
    (build-system r-build-system)
    (propagated-inputs (list r-slam r-mass r-lattice r-highs))
    (home-page "https://cran.r-project.org/package=designmatch")
    (synopsis "Matched Samples that are Balanced and Representative by Design")
    (description
     "Includes functions for the construction of matched samples that are balanced and
representative by design.  Among others, these functions can be used for
matching in observational studies with treated and control units, with cases and
controls, in related settings with instrumental variables, and in discontinuity
designs.  Also, they can be used for the design of randomized experiments, for
example, for matching before randomization.  By default, designmatch uses the
highs optimization solver, but its performance is greatly enhanced by the Gurobi
optimization solver and its associated R interface.  For their installation,
please follow the instructions at
<https://www.gurobi.com/documentation/quickstart.html> and
<https://www.gurobi.com/documentation/7.0/refman/r_api_overview.html>.  We have
also included directions in the gurobi_installation file in the inst folder.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-designlibrary
  (package
    (name "r-designlibrary")
    (version "0.1.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DesignLibrary" version))
       (sha256
        (base32 "0himpw5aq8dqlkvvsbdfffflwxh8v2r3zw3sa72djdrdbzkk6qg5"))))
    (properties `((upstream-name . "DesignLibrary")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-randomizr
                             r-glue
                             r-generics
                             r-fabricatr
                             r-estimatr
                             r-declaredesign))
    (home-page "https://declaredesign.org/r/designlibrary/")
    (synopsis "Library of Research Designs")
    (description
     "This package provides a simple interface to build designs using the package
@code{DeclareDesign}'.  In one line of code, users can specify the parameters of
individual designs and diagnose their properties.  The designers can also be
used to compare performance of a given design across a range of combinations of
parameters, such as effect size, sample size, and assignment probabilities.")
    (license license:expat)))

(define-public r-designit
  (package
    (name "r-designit")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "designit" version))
       (sha256
        (base32 "0h1slgxxz92zk1m6gk67s1ir95jyqzvr6mys9c9lakpffiwwn4b2"))))
    (properties `((upstream-name . "designit")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-scales
                             r-rlang
                             r-r6
                             r-purrr
                             r-ggplot2
                             r-dplyr
                             r-data-table
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://bedapub.github.io/designit/")
    (synopsis "Blocking and Randomization for Experimental Design")
    (description
     "Intelligently assign samples to batches in order to reduce batch effects.  Batch
effects can have a significant impact on data analysis, especially when the
assignment of samples to batches coincides with the contrast groups being
studied.  By defining a batch container and a scoring function that reflects the
contrasts, this package allows users to assign samples in a way that minimizes
the potential impact of batch effects on the comparison of interest.  Among
other functionality, we provide an implementation for OSAT score by Yan et al.
(2012, <doi:10.1186/1471-2164-13-689>).")
    (license license:expat)))

(define-public r-designer
  (package
    (name "r-designer")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "designer" version))
       (sha256
        (base32 "0fsvlrciym2g9mp96kwb04md1jnqxwj39zd8q5dihijj0p1ib5mi"))))
    (properties `((upstream-name . "designer")))
    (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-shinyscreenshot
                             r-shiny
                             r-shinipsum
                             r-rappdirs
                             r-jsonlite
                             r-htmltools
                             r-golem
                             r-fontawesome
                             r-config
                             r-cicerone
                             r-bslib
                             r-bs4dash))
    (native-inputs (list r-knitr esbuild))
    (home-page "https://ashbaldry.github.io/designer/")
    (synopsis "'Shiny' UI Prototype Builder")
    (description
     "This package provides a shiny application that enables the user to create a
prototype UI, being able to drag and drop UI components before being able to
save or download the equivalent R code.")
    (license license:expat)))

(define-public r-designctpb
  (package
    (name "r-designctpb")
    (version "1.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DesignCTPB" version))
       (sha256
        (base32 "1872spxzi5mxxz68nw3ahh6yj50yybrpff4q1xpx0xk89yks13hg"))))
    (properties `((upstream-name . "DesignCTPB")))
    (build-system r-build-system)
    (inputs (list openssl))
    (propagated-inputs (list r-reticulate r-plotly r-mnormt r-fields r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ubcxzhang/DesignCTPB")
    (synopsis "Design Clinical Trials with Potential Biomarker Effect")
    (description
     "Applying CUDA GPUs via Numba for optimal clinical design.  It allows the user to
utilize a reticulate Python environment and run intensive Monte Carlo simulation
to get the optimal cutoff for the clinical design with potential biomarker
effect, which can guide the realistic clinical trials.")
    (license license:gpl2+)))

(define-public r-design-parameters
  (package
    (name "r-design-parameters")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Design.parameters" version))
       (sha256
        (base32 "0wyzz1rncb2260i7p09vziszg2ycmxwgs0zm8qycfamyfii32k7y"))))
    (properties `((upstream-name . "Design.parameters")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=Design.parameters")
    (synopsis "Parameters of the Experimental Designs")
    (description
     "Here, a function has been developed to generate parameters of the input designs,
as well as incidence matrices.  This is a general function that can be used to
investigate the characterization properties of any block design.")
    (license license:gpl3)))

(define-public r-deseats
  (package
    (name "r-deseats")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deseats" version))
       (sha256
        (base32 "11qhsiqq0f1s6b7x7fmvgwwhirhilf9x37pk90pwgg3h4khjl1j5"))))
    (properties `((upstream-name . "deseats")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-tidyr
                             r-shiny
                             r-rlang
                             r-rcpparmadillo
                             r-rcpp
                             r-purrr
                             r-progressr
                             r-ggplot2
                             r-future-apply
                             r-future
                             r-furrr
                             r-animation))
    (home-page "https://cran.r-project.org/package=deseats")
    (synopsis
     "Data-Driven Locally Weighted Regression for Trend and Seasonality in TS")
    (description
     "Various methods for the identification of trend and seasonal components in time
series (TS) are provided.  Among them is a data-driven locally weighted
regression approach with automatically selected bandwidth for equidistant
short-memory time series.  The approach is a combination / extension of the
algorithms by Feng (2013) <doi:10.1080/02664763.2012.740626> and Feng, Y.,
Gries, T., and Fritz, M. (2020) <doi:10.1080/10485252.2020.1759598> and a brief
description of this new method is provided in the package documentation.
Furthermore, the package allows its users to apply the base model of the Berlin
procedure, version 4.1, as described in Speth (2004)
<https://www.destatis.de/DE/Methoden/Saisonbereinigung/BV41-methodenbericht-Heft3_2004.pdf?__blob=@code{publicationFile>}.
 Permission to include this procedure was kindly provided by the Federal
Statistical Office of Germany.")
    (license license:gpl3)))

(define-public r-desctoolsaddins
  (package
    (name "r-desctoolsaddins")
    (version "1.11")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DescToolsAddIns" version))
       (sha256
        (base32 "160xd95njj1pk11grdrs2mzx1h98q8fin46yg8jiyi16rlyvxm4l"))))
    (properties `((upstream-name . "DescToolsAddIns")))
    (build-system r-build-system)
    (propagated-inputs (list r-writexl r-rstudioapi r-manipulate r-foreign
                             r-desctools))
    (home-page "https://github.com/AndriSignorell/DescToolsAddIns/")
    (synopsis "Interactive Functions to be Used as Shortcuts in 'RStudio'")
    (description
     "RStudio as of recently offers the option to define addins and assign shortcuts
to them.  This package contains addins for a few most frequently used functions
in a data scientist's (at least mine) daily work (like str(), example(), plot(),
head(), view(), Desc()).  Most of these functions will use the current selection
in the editor window and send the specific command to the console while
instantly executing it.  Assigning shortcuts to these addins will save you quite
a few keystrokes.")
    (license license:gpl2+)))

(define-public r-desctable
  (package
    (name "r-desctable")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "desctable" version))
       (sha256
        (base32 "1i0124lnmzdbx468lyqmzbd6disxjifqjy8ss10fl8cin4f868lb"))))
    (properties `((upstream-name . "desctable")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rlang
                             r-pander
                             r-htmltools
                             r-dt
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://desctable.github.io")
    (synopsis "Produce Descriptive and Comparative Tables Easily")
    (description
     "Easily create descriptive and comparative tables.  It makes use and integrates
directly with the tidyverse family of packages, and pipes.  Tables are produced
as (nested) dataframes for easy manipulation.")
    (license license:gpl3)))

(define-public r-descstatsr
  (package
    (name "r-descstatsr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "descstatsr" version))
       (sha256
        (base32 "1pz5lww1dkkqvsq6h0vkch39bj76qffmmag3zlag5in75s4wj0wl"))))
    (properties `((upstream-name . "descstatsr")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-moments))
    (home-page "https://cran.r-project.org/package=descstatsr")
    (synopsis "Descriptive Univariate Statistics")
    (description
     "It generates summary statistics on the input dataset using different descriptive
univariate statistical measures on entire data or at a group level.  Though
there are other packages which does similar job but each of these are deficient
in one form or other, in the measures generated, in treating numeric, character
and date variables alike, no functionality to view these measures on a group
level or the way the output is represented.  Given the foremost role of the
descriptive statistics in any of the exploratory data analysis or solution
development, there is a need for a more constructive, structured and refined
version over these packages.  This is the idea behind the package and it brings
together all the required descriptive measures to give an initial understanding
of the data quality, distribution in a faster,easier and elaborative way.The
function brings an additional capability to be able to generate these
statistical measures on the entire dataset or at a group level.  It calculates
measures of central tendency (mean, median), distribution (count, proportion),
dispersion (min, max, quantile, standard deviation, variance) and shape
(skewness, kurtosis).  Addition to these measures, it provides information on
the data type, count on no.  of rows, unique entries and percentage of missing
entries.  More importantly the measures are generated based on the data types as
required by them,rather than applying numerical measures on character and data
variables and vice versa.  Output as a dataframe object gives a very neat
representation, which often is useful when working with a large number of
columns.  It can easily be exported as csv and analyzed further or presented as
a summary report for the data.")
    (license license:gpl2)))

(define-public r-descstat
  (package
    (name "r-descstat")
    (version "0.1-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "descstat" version))
       (sha256
        (base32 "0q463p0bq80c9lhwfv4imbhgx6f1w2jqm3022p5zvycfa9w39rin"))))
    (properties `((upstream-name . "descstat")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-forcats
                             r-dplyr
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://www.r-project.org")
    (synopsis "Tools for Descriptive Statistics")
    (description
     "This package provides a toolbox for descriptive statistics, based on the
computation of frequency and contingency tables.  Several statistical functions
and plot methods are provided to describe univariate or bivariate distributions
of factors, integer series and numerical series either provided as individual
values or as bins.")
    (license license:gpl2+)))

(define-public r-descrtab2
  (package
    (name "r-descrtab2")
    (version "2.1.16")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DescrTab2" version))
       (sha256
        (base32 "07921k8h50wycj0sijy8428p3c8ach90swgzz0s06b6z1yl2mnyg"))))
    (properties `((upstream-name . "DescrTab2")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-scales
                             r-rmarkdown
                             r-rlang
                             r-officer
                             r-nlme
                             r-magrittr
                             r-knitr
                             r-kableextra
                             r-hmisc
                             r-haven
                             r-forcats
                             r-flextable
                             r-exact2x2
                             r-dplyr
                             r-desctools
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://imbi-heidelberg.github.io/DescrTab2/")
    (synopsis "Publication Quality Descriptive Statistics Tables")
    (description
     "This package provides functions to create descriptive statistics tables for
continuous and categorical variables.  By default, summary statistics such as
mean, standard deviation, quantiles, minimum and maximum for continuous
variables and relative and absolute frequencies for categorical variables are
calculated. @code{DescrTab2} features a sophisticated algorithm to choose
appropriate test statistics for your data and provides p-values.  On top of
this, confidence intervals for group differences of appropriated summary
measures are automatically produces for two-group comparison.  Tables generated
by @code{DescrTab2} can be integrated in a variety of document formats,
including .html, .tex and .docx documents. @code{DescrTab2} also allows printing
tables to console and saving table objects for later use.")
    (license license:gpl3+)))

(define-public r-descriptr
  (package
    (name "r-descriptr")
    (version "0.5.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "descriptr" version))
       (sha256
        (base32 "1shqcykp8ahgarsam56zv4gcbj0mmfm7jy1i9fgbmy5ddksnific"))))
    (properties `((upstream-name . "descriptr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-scales
                             r-rlang
                             r-magrittr
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://descriptr.rsquaredacademy.com/")
    (synopsis "Generate Descriptive Statistics")
    (description
     "Generate descriptive statistics such as measures of location, dispersion,
frequency tables, cross tables, group summaries and multiple one/two way tables.")
    (license license:expat)))

(define-public r-descriptivewh
  (package
    (name "r-descriptivewh")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DescriptiveWH" version))
       (sha256
        (base32 "17baga9vs8959bzm7qs11zj35a6glh1ig5qz8kwq7m69h51l2gar"))))
    (properties `((upstream-name . "DescriptiveWH")))
    (build-system r-build-system)
    (home-page "https://github.com/William-HC/DescriptiveWH")
    (synopsis "Descriptive Statistics")
    (description
     "Exploratory analysis of a data base.  Using the functions of this package is
possible to filter the data set detecting atypical values (outliers) and to
perform exploratory analysis through visual inspection or dispersion measures.
With this package you can explore the structure of your data using several
parameters at the same time joining statistical parameters with different
graphics.  Finally, this package aid to confirm or reject the hypothesis that
your data structure presents a normal distribution.  Therefore this package is
useful to get a previous insight of your data before to carry out statistical
analysis.")
    (license license:gpl3)))

(define-public r-descriptivestats-obeu
  (package
    (name "r-descriptivestats-obeu")
    (version "1.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DescriptiveStats.OBeu" version))
       (sha256
        (base32 "0f2inlfkwl2q9ll5lh0ynpsbf6zci149s5nj0s0x0g98z72z8mly"))))
    (properties `((upstream-name . "DescriptiveStats.OBeu")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape r-rcurl r-magrittr r-jsonlite r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/okgreece/DescriptiveStats.OBeu")
    (synopsis "Descriptive Statistics 'OpenBudgets.eu'")
    (description
     "Estimate and return the needed parameters for visualizations designed for
@code{OpenBudgets.eu} <http://openbudgets.eu/> datasets.  Calculate descriptive
statistical measures in budget data of municipalities across Europe, according
to the @code{OpenBudgets.eu} data model.  There are functions for measuring
central tendency and dispersion of amount variables along with their
distributions and correlations and the frequencies of categorical variables for
a given dataset.  Also, can be used generally to other datasets, to extract
visualization 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-descriptiverepresentationcalculator
  (package
    (name "r-descriptiverepresentationcalculator")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DescriptiveRepresentationCalculator" version))
       (sha256
        (base32 "0p0n5zjaxhr0rba93ikaw30lrf8zgx35yfjimwlg2375ns0zpmr6"))))
    (properties `((upstream-name . "DescriptiveRepresentationCalculator")))
    (build-system r-build-system)
    (home-page
     "https://github.com/cjerzak/DescriptiveRepresentationCalculator-software/")
    (synopsis
     "Descriptive Representation Calculator: Characterizing Observed and Expected Representation")
    (description
     "This package provides a system for analyzing descriptive representation,
especially for comparing the composition of a political body to the population
it represents.  Users can compute the expected degree of representation for a
body under a random sampling model, the expected degree of representation
variability, as well as representation scores from observed political bodies.
The package is based on Gerring, Jerzak, and Oncel (2023)
<doi:10.1017/S0003055423000680>.")
    (license license:gpl3)))

(define-public r-descriptio
  (package
    (name "r-descriptio")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "descriptio" version))
       (sha256
        (base32 "0ic44blsi7ys6075zsawf4rxqgjsv1d7hr8y2j3psk6pjchlgx18"))))
    (properties `((upstream-name . "descriptio")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-mass r-ggplot2))
    (home-page "https://github.com/nicolas-robette/descriptio")
    (synopsis "Descriptive Statistical Analysis")
    (description
     "Description of statistical associations between two variables : measures of
local and global association between variables (phi, CramÃ©r V, correlations,
eta-squared, Goodman and Kruskal tau, permutation tests, etc.), multiple
graphical representations of the associations between two variables (using
ggplot2') and weighted statistics.")
    (license license:gpl2+)))

(define-public r-describer
  (package
    (name "r-describer")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "describer" version))
       (sha256
        (base32 "1pjyihmn4gkaamixsc3qwynsc02pwv9bgn6s7z7acmmsybhhs6xn"))))
    (properties `((upstream-name . "describer")))
    (build-system r-build-system)
    (home-page "https://github.com/paulhendricks/describer")
    (synopsis "Describe Data in R Using Common Descriptive Statistics")
    (description
     "Allows users to quickly and easily describe data using common descriptive
statistics.")
    (license license:expat)))

(define-public r-describedisplay
  (package
    (name "r-describedisplay")
    (version "0.2.11")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DescribeDisplay" version))
       (sha256
        (base32 "19fwg93p2vdl2sbg8llwijklsvim5vrgcvv2048akbdahvfj9rxb"))))
    (properties `((upstream-name . "DescribeDisplay")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales r-reshape2 r-plyr r-ggplot2 r-ggally))
    (home-page "https://github.com/ggobi/DescribeDisplay")
    (synopsis "An Interface to the 'DescribeDisplay' 'GGobi' Plugin")
    (description
     "Produce publication quality graphics from output of GGobi describe display
plugin.")
    (license license:expat)))

(define-public r-describedf
  (package
    (name "r-describedf")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DescribeDF" version))
       (sha256
        (base32 "1nah46s4psi272idpkpzkx7zqy6vr6wdz5zfxyz17cld9q2lld47"))))
    (properties `((upstream-name . "DescribeDF")))
    (build-system r-build-system)
    (propagated-inputs (list r-tseries r-psych r-fnonlinear r-e1071 r-dplyr))
    (home-page "https://cran.r-project.org/package=DescribeDF")
    (synopsis "Description of a Data Frame")
    (description
     "Helps to describe a data frame in hand.  Has been developed during @code{PhD}
work of the maintainer.  More information may be obtained from Garai and Paul
(2023) <doi:10.1016/j.iswa.2023.200202>.")
    (license license:gpl3)))

(define-public r-describedata
  (package
    (name "r-describedata")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "describedata" version))
       (sha256
        (base32 "10ryy886jr2gwi6h90girl82ivwrmhz1vcwi4f6khmmpwsy95hav"))))
    (properties `((upstream-name . "describedata")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-purrr
                             r-lmtest
                             r-haven
                             r-ggplot2
                             r-forcats
                             r-dplyr
                             r-broom))
    (home-page "https://cran.r-project.org/package=describedata")
    (synopsis "Miscellaneous Descriptive Functions")
    (description
     "Helper functions for descriptive tasks such as making print-friendly bivariate
tables, sample size flow counts, and visualizing sample distributions.  Also
contains R approximations of some common SAS and Stata functions such as PROC
MEANS from SAS and ladder', gladder', and pwcorr from Stata'.")
    (license license:gpl3)))

(define-public r-descr
  (package
    (name "r-descr")
    (version "1.1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "descr" version))
       (sha256
        (base32 "0yyxh1030pfjriwm8xfx9rp32cq7jfqlxq8mim1qvx06siah545c"))))
    (properties `((upstream-name . "descr")))
    (build-system r-build-system)
    (propagated-inputs (list r-xtable))
    (home-page "https://github.com/jalvesaq/descr")
    (synopsis "Descriptive Statistics")
    (description
     "Weighted frequency and contingency tables of categorical variables and of the
comparison of the mean value of a numerical variable by the levels of a factor,
and methods to produce xtable objects of the tables and to plot them.  There are
also functions to facilitate the character encoding conversion of objects, to
quickly convert fixed width files into csv ones, and to export a data.frame to a
text file with the necessary R and SPSS codes to reread the data.")
    (license license:gpl2+)))

(define-public r-descomponer
  (package
    (name "r-descomponer")
    (version "1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "descomponer" version))
       (sha256
        (base32 "1yznb6j850gap1bacvx5dkh4030x38041ll61z6an6h7j71yyc5p"))))
    (properties `((upstream-name . "descomponer")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=descomponer")
    (synopsis "Seasonal Adjustment by Frequency Analysis")
    (description
     "Decompose a time series into seasonal, trend and irregular components using
transformations to amplitude-frequency domain.")
    (license license:gpl2+)))

(define-public r-des
  (package
    (name "r-des")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DES" version))
       (sha256
        (base32 "16p38i8ykwc8gjw6c9dhdwjjpa1b17n9wqhz3rhkbzjh978pky31"))))
    (properties `((upstream-name . "DES")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DES")
    (synopsis "Discrete Event Simulation")
    (description
     "Discrete event simulation (DES) involves modeling of systems having discrete,
i.e.  abrupt, state changes.  For instance, when a job arrives to a queue, the
queue length abruptly increases by 1.  This package is an R implementation of
the event-oriented approach to DES; see the tutorial in Matloff (2008)
<http://heather.cs.ucdavis.edu/~matloff/156/PLN/DE@code{SimIntro.pdf>}.")
    (license license:expat)))

(define-public r-derivmkts
  (package
    (name "r-derivmkts")
    (version "0.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "derivmkts" version))
       (sha256
        (base32 "0zjdpjd7qa7zg0dyyq1y4rskk8bi2jpsxzrdg43lnsyrxg99q1n6"))))
    (properties `((upstream-name . "derivmkts")))
    (build-system r-build-system)
    (propagated-inputs (list r-mnormt))
    (native-inputs (list r-tidyr
                         r-pander
                         r-knitr
                         r-ggplot2
                         r-dplyr
                         r-bookdown))
    (home-page "https://cran.r-project.org/package=derivmkts")
    (synopsis "Functions and R Code to Accompany Derivatives Markets")
    (description
     "This package provides a set of pricing and expository functions that should be
useful in teaching a course on financial derivatives.")
    (license license:expat)))

(define-public r-derezende-ferreira
  (package
    (name "r-derezende-ferreira")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DeRezende.Ferreira" version))
       (sha256
        (base32 "05c99z3hlwwm0p02cl9z6gjwfxfq2b2qn90l85270bi16llgf42h"))))
    (properties `((upstream-name . "DeRezende.Ferreira")))
    (build-system r-build-system)
    (propagated-inputs (list r-xts))
    (home-page "https://cran.r-project.org/package=DeRezende.Ferreira")
    (synopsis "Zero Coupon Yield Curve Modelling")
    (description
     "Modeling the zero coupon yield curve using the dynamic De Rezende and Ferreira
(2011) <doi:10.1002/for.1256> five factor model with variable or fixed decaying
parameters.  For explanatory purposes, the package also includes various short
datasets of interest rates for the BRICS countries.")
    (license license:gpl2+)))

(define-public r-depthtools
  (package
    (name "r-depthtools")
    (version "0.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "depthTools" version))
       (sha256
        (base32 "00pn4ccsg1hjv83xqk4g0g24cz2a87shlbg8kd2dri4dcagzifg0"))))
    (properties `((upstream-name . "depthTools")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=depthTools")
    (synopsis "Depth Tools Package")
    (description
     "Implementation of different statistical tools for the description and analysis
of gene expression data based on the concept of data depth, namely, the scale
curves for visualizing the dispersion of one or various groups of samples (e.g.
types of tumors), a rank test to decide whether two groups of samples come from
a single distribution and two methods of supervised classification techniques,
the DS and TAD methods.  All these techniques are based on the Modified Band
Depth, which is a recent notion of depth with a low computational cost, what
renders it very appropriate for high dimensional data such as gene expression
data.")
    (license license:gpl2+)))

(define-public r-depthproc
  (package
    (name "r-depthproc")
    (version "2.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DepthProc" version))
       (sha256
        (base32 "0i7fks5hglf3xj8cj3sghjf0xcldhiqwf0jlpyk2a3mj9gaszc76"))))
    (properties `((upstream-name . "DepthProc")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-sm
                             r-rrcov
                             r-rcpparmadillo
                             r-rcpp
                             r-np
                             r-mass
                             r-lattice
                             r-ggplot2
                             r-geometry
                             r-colorspace))
    (home-page "https://www.depthproc.zstat.pl/")
    (synopsis "Statistical Depth Functions for Multivariate Analysis")
    (description
     "Data depth concept offers a variety of powerful and user friendly tools for
robust exploration and inference for multivariate data.  The offered techniques
may be successfully used in cases of lack of our knowledge on parametric models
generating data due to their nature.  The package consist of among others
implementations of several data depth techniques involving multivariate
quantile-quantile plots, multivariate scatter estimators, multivariate Wilcoxon
tests and robust regressions.")
    (license license:gpl2)))

(define-public r-depth-plot
  (package
    (name "r-depth-plot")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "depth.plot" version))
       (sha256
        (base32 "0zjg9iyqmcnkvwc9w2j7lmk3k9nsg6n8m6vq5x44d1bp4g2gr6jv"))))
    (properties `((upstream-name . "depth.plot")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm))
    (home-page "https://cran.r-project.org/package=depth.plot")
    (synopsis "Multivariate Analogy of Quantiles")
    (description
     "Could be used to obtain spatial depths, spatial ranks and outliers of
multivariate random variables.  Could also be used to visualize DD-plots (a
multivariate generalization of QQ-plots).")
    (license license:gpl2)))

(define-public r-deps
  (package
    (name "r-deps")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deps" version))
       (sha256
        (base32 "147lb9dibn8ayj6znld64sk1qn6lzpp5pamxkagmqcbxl78r1g6h"))))
    (properties `((upstream-name . "deps")))
    (build-system r-build-system)
    (propagated-inputs (list r-renv r-remotes r-jsonlite))
    (home-page "https://hub.analythium.io/deps/")
    (synopsis "Dependency Management with 'roxygen'-Style Comments")
    (description
     "Manage your source code dependencies by decorating your existing R code with
special, roxygen'-style comments.")
    (license license:expat)))

(define-public r-depons2r
  (package
    (name "r-depons2r")
    (version "1.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DEPONS2R" version))
       (sha256
        (base32 "1l09nl6dvm0h005m7wpic95d710qv0v7q4ac67cr5zsr2l0prj1z"))))
    (properties `((upstream-name . "DEPONS2R")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-terra
                             r-sp
                             r-sf
                             r-raster
                             r-jsonlite))
    (home-page "https://cran.r-project.org/package=DEPONS2R")
    (synopsis "Read, Plot and Analyse Output from the DEPONS Model")
    (description
     "This package provides methods for analyzing population dynamics and movement
tracks simulated using the DEPONS model <https://www.depons.eu> (v.3.0), for
manipulating input raster files, shipping routes and for analyzing sound
propagated from ships.")
    (license license:gpl3)))

(define-public r-depmix
  (package
    (name "r-depmix")
    (version "0.9.16")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "depmix" version))
       (sha256
        (base32 "1vi9fi131ni34z9p3x6pdp6y9v0y0nx71zg1q8898frhqwbwhd9c"))))
    (properties `((upstream-name . "depmix")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=depmix")
    (synopsis "Dependent Mixture Models")
    (description
     "Fits (multigroup) mixtures of latent or hidden Markov models on mixed
categorical and continuous (timeseries) data.  The Rdonlp2 package can
optionally be used for optimization of the log-likelihood and is available from
R-forge.  See Visser et al. (2009, <DOI:10.1007/978-0-387-95922-1_13>) for
examples and applications.")
    (license license:gpl3)))

(define-public r-deploid
  (package
    (name "r-deploid")
    (version "0.5.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DEploid" version))
       (sha256
        (base32 "1ljha520yjbzyrw4h77y1r29rymzk2x8z8hczc0lh539mfi4jll6"))))
    (properties `((upstream-name . "DEploid")))
    (build-system r-build-system)
    (inputs (list zlib))
    (propagated-inputs (list r-scales
                             r-rmarkdown
                             r-rcpp
                             r-plotly
                             r-magrittr
                             r-htmlwidgets))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/DEploid-dev/DEploid-r")
    (synopsis "Deconvolute Mixed Genomes with Unknown Proportions")
    (description
     "Traditional phasing programs are limited to diploid organisms.  Our method
modifies Li and Stephens algorithm with Markov chain Monte Carlo (MCMC)
approaches, and builds a generic framework that allows haplotype searches in a
multiple infection setting.  This package is primarily developed as part of the
Pf3k project, which is a global collaboration using the latest sequencing
technologies to provide a high-resolution view of natural variation in the
malaria parasite Plasmodium falciparum.  Parasite DNA are extracted from patient
blood sample, which often contains more than one parasite strain, with unknown
proportions.  This package is used for deconvoluting mixed haplotypes, and
reporting the mixture proportions from each sample.")
    (license license:gpl3+)))

(define-public r-deplogo
  (package
    (name "r-deplogo")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DepLogo" version))
       (sha256
        (base32 "13mk52ssiig76rnc02fq3b2g986b161gvncnr6krk7v9a4s5cjqk"))))
    (properties `((upstream-name . "DepLogo")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DepLogo")
    (synopsis "Dependency Logo")
    (description
     "Plots dependency logos from a set of aligned input sequences.")
    (license license:gpl3)))

(define-public r-depigner
  (package
    (name "r-depigner")
    (version "0.9.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "depigner" version))
       (sha256
        (base32 "0vzrdw4rhrwiyc4g4ancfd43h56b72lkvabqdwdsg54hjm35c1ky"))))
    (properties `((upstream-name . "depigner")))
    (build-system r-build-system)
    (propagated-inputs (list r-usethis
                             r-tidyr
                             r-tibble
                             r-telegram-bot
                             r-stringr
                             r-rprojroot
                             r-rms
                             r-rlang
                             r-readr
                             r-purrr
                             r-progress
                             r-magrittr
                             r-hmisc
                             r-ggplot2
                             r-fs
                             r-dplyr
                             r-desc))
    (home-page "https://corradolanera.github.io/depigner/")
    (synopsis "Utility Package to Help you Deal with \"Pignas\"")
    (description
     "Pigna [_pÃ¬n'n'a_] is the Italian word for pine cone.  In jargon, it is used to
identify a task which is boring, banal, annoying, painful, frustrating and maybe
even with a not so beautiful or rewarding result, just like the obstinate act of
trying to challenge yourself in extracting pine nuts from a pine cone, provided
that, in the end, you will find at least one inside it.  Here you can find a
backpack of functions to be used to solve small everyday problems of coding or
analyzing (clinical) data, which would be normally solved using quick-and-dirty
patches.  You will be able to convert Hmisc and rms summary()es into data.frames
ready to be rendered by pander and knitr'.  You can access easy-to-use wrappers
to activate essential but useful progress bars (from progress') into your loops
or functionals.  Easy setup and control Telegram's bots (from telegram.bot') to
send messages or to divert error messages to a Telegram's chat.  You also have
some utilities helping you in the development of packages, like the activation
of the same user interface of usethis into your package, or call polite
functions to ask a user to install other packages.  Finally, you find a set of
thematic sets of packages you may use to set up new environments quickly,
installing them in a single call.")
    (license license:gpl3)))

(define-public r-depend-truncation
  (package
    (name "r-depend-truncation")
    (version "3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "depend.truncation" version))
       (sha256
        (base32 "1jym52qxx8v4kbq2578d03q2593q96jccr85if47djikw0aaxmcr"))))
    (properties `((upstream-name . "depend.truncation")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm))
    (home-page "https://cran.r-project.org/package=depend.truncation")
    (synopsis
     "Statistical Methods for the Analysis of Dependently Truncated Data")
    (description
     "Estimation and testing methods for dependently truncated data.  Semi-parametric
methods are based on Emura et al. (2011)<Stat Sinica 21:349-67>, Emura & Wang
(2012)<doi:10.1016/j.jmva.2012.03.012>, and Emura & Murotani
(2015)<doi:10.1007/s11749-015-0432-8>.  Parametric approaches are based on Emura
& Konno (2012)<doi:10.1007/s00362-014-0626-2> and Emura & Pan
(2017)<doi:10.1007/s00362-017-0947-z>.  A regression approach is based on Emura
& Wang (2016)<doi:10.1007/s10463-015-0526-9>.  Quasi-independence tests are
based on Emura & Wang (2010)<doi:10.1016/j.jmva.2009.07.006>.  Right-truncated
data for Japanese male centenarians are given by Emura & Murotani
(2015)<doi:10.1007/s11749-015-0432-8>.")
    (license license:gpl2)))

(define-public r-depcoeff
  (package
    (name "r-depcoeff")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "depcoeff" version))
       (sha256
        (base32 "08vs0yzfvd4ahcs5rz4i4spp8l6fg45bm0m22gn5rzxc4759mzac"))))
    (properties `((upstream-name . "depcoeff")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-copula))
    (home-page "https://cran.r-project.org/package=depcoeff")
    (synopsis "Dependency Coefficients")
    (description
     "This package provides functions to compute coefficients measuring the dependence
of two or more than two variables.  The functions can be deployed to gain
information about functional dependencies of the variables with emphasis on
monotone functions.  The statistics describe how well one response variable can
be approximated by a monotone function of other variables.  In regression
analysis the variable selection is an important issue.  In this framework the
functions could be useful tools in modeling the regression function.  Detailed
explanations on the subject can be found in papers Liebscher (2014)
<doi:10.2478/demo-2014-0004>; Liebscher (2017) <doi:10.1515/demo-2017-0012>;
Liebscher (2019, submitted).")
    (license license:gpl2)))

(define-public r-depcensoring
  (package
    (name "r-depcensoring")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "depCensoring" version))
       (sha256
        (base32 "0wsdwsv09k55ipbpps5aaf81a4p5mp9r63p36bvhj91f7ckvnwg0"))))
    (properties `((upstream-name . "depCensoring")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-stringr
                             r-semipar-depcens
                             r-rvinecopulib
                             r-rafalib
                             r-pbivnorm
                             r-openmx
                             r-numderiv
                             r-nloptr
                             r-nleqslv
                             r-mvtnorm
                             r-matrixcalc
                             r-mass
                             r-foreach
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=depCensoring")
    (synopsis "Statistical Methods for Survival Data with Dependent Censoring")
    (description
     "Several statistical methods for analyzing survival data under various forms of
dependent censoring are implemented in the package.  In addition to accounting
for dependent censoring, it offers tools to adjust for unmeasured confounding
factors.  The implemented approaches allow users to estimate the dependency
between survival time and dependent censoring time, based solely on observed
survival data.  For more details on the methods, refer to Deresa and Van
Keilegom (2021) <doi:10.1093/biomet/asaa095>, Czado and Van Keilegom (2023)
<doi:10.1093/biomet/asac067>, Crommen et al. (2024)
<doi:10.1007/s11749-023-00903-9> and Willems et al. (2024+)
<doi:10.48550/@code{arXiv.2403.11860>}.")
    (license license:gpl3)))

(define-public r-depcens
  (package
    (name "r-depcens")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DepCens" version))
       (sha256
        (base32 "0sz7bj6pqwj6appyymajav0q5g1hrpaa8m75rx4drfjdp0lv7ihq"))))
    (properties `((upstream-name . "DepCens")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rootsolve r-matrixstats r-formula
                             r-dlm))
    (home-page "https://github.com/GabrielGrandemagne/DepCens")
    (synopsis "Dependent Censoring Regression Models")
    (description
     "Dependent censoring regression models for survival multivariate data.  These
models are based on extensions of the frailty models, capable to accommodating
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. (2019)
<doi:10.1002/bimj.201800391>.")
    (license license:gpl2+)))

(define-public r-depcache
  (package
    (name "r-depcache")
    (version "0.1-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "depcache" version))
       (sha256
        (base32 "1gmxf6fffjgv7xzjckqmb7b79dn7km2hbv8z6s2scd7gic8iwg0i"))))
    (properties `((upstream-name . "depcache")))
    (build-system r-build-system)
    (propagated-inputs (list r-codetools))
    (home-page "https://cran.r-project.org/package=depcache")
    (synopsis "Cache R Expressions, Taking Their Dependencies into Account")
    (description
     "Hash an expression with its dependencies and store its value, reloading it from
a file as long as both the expression and its dependencies stay the same.")
    (license license:gpl3+)))

(define-public r-deoptim
  (package
    (name "r-deoptim")
    (version "2.2-8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DEoptim" version))
       (sha256
        (base32 "0k7mvf7j8y1sqv8zpiwkw4xcmgki37drkxjijrsmmhkfybfan7k3"))))
    (properties `((upstream-name . "DEoptim")))
    (build-system r-build-system)
    (home-page "https://github.com/ArdiaD/DEoptim")
    (synopsis "Global Optimization by Differential Evolution")
    (description
     "This package implements the Differential Evolution algorithm for global
optimization of a real-valued function of a real-valued parameter vector as
described in Mullen et al. (2011) <doi:10.18637/jss.v040.i06>.")
    (license license:gpl2+)))

(define-public r-denvax
  (package
    (name "r-denvax")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "denvax" version))
       (sha256
        (base32 "0a8x7z7jagshc5h6xy24xrvqv0gm08f78ik6y8ki4i0mhl8c5fyx"))))
    (properties `((upstream-name . "denvax")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://gitlab.com/cabp_LSHTM/denvax")
    (synopsis "Simple Dengue Test and Vaccinate Cost Thresholds")
    (description
     "This package provides the mathematical model described by \"Serostatus Testing &
Dengue Vaccine Cost-Benefit Thresholds\" in <doi:10.1098/rsif.2019.0234>.  Using
the functions in the package, that analysis can be repeated using sample life
histories, either synthesized from local seroprevalence data using other
functions in this package (as in the manuscript) or from some other source.  The
package provides a vignette which walks through the analysis in the publication,
as well as a function to generate a project skeleton for such an analysis.")
    (license license:expat)))

(define-public r-denstrip
  (package
    (name "r-denstrip")
    (version "1.5.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "denstrip" version))
       (sha256
        (base32 "0hzxphj740q6pfa1q42knr7n12bmnawg7b2fs74msxn83dka5cmq"))))
    (properties `((upstream-name . "denstrip")))
    (build-system r-build-system)
    (propagated-inputs (list r-lattice))
    (home-page "https://cran.r-project.org/package=denstrip")
    (synopsis
     "Density Strips and Other Methods for Compactly Illustrating Distributions")
    (description
     "Graphical methods for compactly illustrating probability distributions,
including density strips, density regions, sectioned density plots and varying
width strips.")
    (license license:gpl2+)))

(define-public r-densratio
  (package
    (name "r-densratio")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "densratio" version))
       (sha256
        (base32 "0x333kfx5mdzzjsqy37j4bmv9iddlgp3wi4774lx8d159lbr6irp"))))
    (properties `((upstream-name . "densratio")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/hoxo-m/densratio")
    (synopsis "Density Ratio Estimation")
    (description
     "Density ratio estimation.  The estimated density ratio function can be used in
many applications such as anomaly detection, change-point detection, covariate
shift adaptation.  The implemented methods are @code{uLSIF} (Hido et al. (2011)
<doi:10.1007/s10115-010-0283-2>), @code{RuLSIF} (Yamada et al. (2011)
<doi:10.1162/NECO_a_00442>), and KLIEP (Sugiyama et al. (2007)
<doi:10.1007/s10463-008-0197-x>).")
    (license license:expat)))

(define-public r-densparcorr
  (package
    (name "r-densparcorr")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DensParcorr" version))
       (sha256
        (base32 "1ifkg7cpimf27yhr60rks77r16kmhwa5h10wv7b64sbfncnyzfmj"))))
    (properties `((upstream-name . "DensParcorr")))
    (build-system r-build-system)
    (propagated-inputs (list r-gplots r-clime))
    (home-page "https://cran.r-project.org/package=DensParcorr")
    (synopsis
     "Dens-Based Method for Partial Correlation Estimation in Large Scale Brain Networks")
    (description
     "Provide a Dens-based method for estimating functional connection in large scale
brain networks using partial correlation.")
    (license license:gpl2)))

(define-public r-densityarea
  (package
    (name "r-densityarea")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "densityarea" version))
       (sha256
        (base32 "0blcpclwa6507vna9j8ysj0rs57r15f9vhp78d8fnl1436zlm217"))))
    (properties `((upstream-name . "densityarea")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-tibble
                             r-sfheaders
                             r-sf
                             r-rlang
                             r-purrr
                             r-isoband
                             r-ggdensity
                             r-dplyr
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/JoFrhwld/densityarea")
    (synopsis "Polygons of Bivariate Density Distributions")
    (description
     "With bivariate data, it is possible to calculate 2-dimensional kernel density
estimates that return polygons at given levels of probability.  densityarea
returns these polygons for analysis, including for calculating their area.")
    (license license:gpl3+)))

(define-public r-densitr
  (package
    (name "r-densitr")
    (version "0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "densitr" version))
       (sha256
        (base32 "04k98id4y5b6bdzayzignzyha8l693wk3dsla4abfpdf4wpqs17a"))))
    (properties `((upstream-name . "densitr")))
    (build-system r-build-system)
    (propagated-inputs (list r-changepoint))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/krajnc/densitr")
    (synopsis "Analysing Density Profiles from Resistance Drilling of Trees")
    (description
     "This package provides various tools for analysing density profiles obtained by
resistance drilling.  It can load individual or multiple files and trim the
starting and ending part of each density profile.  Tools are also provided to
trim profiles manually, to remove the trend from measurements using several
methods, to plot the profiles and to detect tree rings automatically.  Written
with a focus on forestry use of resistance drilling in standing trees.")
    (license license:gpl3)))

(define-public r-denseflmm
  (package
    (name "r-denseflmm")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "denseFLMM" version))
       (sha256
        (base32 "1lfhd73zvvz6glq41lb2a9x63fjwjfp53zmy9g78fg6gz5lbnbpm"))))
    (properties `((upstream-name . "denseFLMM")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-mgcv r-matrix r-mass))
    (home-page "https://cran.r-project.org/package=denseFLMM")
    (synopsis "Functional Linear Mixed Models for Densely Sampled Data")
    (description
     "Estimation of functional linear mixed models for densely sampled data based on
functional principal component analysis.")
    (license license:gpl2)))

(define-public r-denovolyzer
  (package
    (name "r-denovolyzer")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "denovolyzeR" version))
       (sha256
        (base32 "03ya5clzqp12lfhw073ri0pwgxn53a6pvnais317a8bv1yinxspb"))))
    (properties `((upstream-name . "denovolyzeR")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2 r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "http://denovolyzeR.org")
    (synopsis "Statistical Analyses of De Novo Genetic Variants")
    (description
     "An integrated toolset for the analysis of de novo (sporadic) genetic sequence
variants. @code{denovolyzeR} implements a mutational model that estimates the
probability of a de novo genetic variant arising in each human gene, from which
one can infer the expected number of de novo variants in a given population
size.  Observed variant frequencies can then be compared against expectation in
a Poisson framework. @code{denovolyzeR} provides a suite of functions to
implement these analyses for the interpretation of de novo variation in human
disease.")
    (license license:gpl3)))

(define-public r-denoiser
  (package
    (name "r-denoiser")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "denoiseR" version))
       (sha256
        (base32 "1q5kxiwfkrf2k0gpidzhl4hyzyjcm33rwlw4dan9nkx1181naw9l"))))
    (properties `((upstream-name . "denoiseR")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-irlba r-factominer))
    (home-page "https://cran.r-project.org/package=denoiseR")
    (synopsis "Regularized Low Rank Matrix Estimation")
    (description
     "Estimate a low rank matrix from noisy data using singular values thresholding
and shrinking functions.  Impute missing values with matrix completion.  The
method is described in <@code{arXiv:1602.01206>}.")
    (license license:gpl2+)))

(define-public r-denoiseq
  (package
    (name "r-denoiseq")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "denoiSeq" version))
       (sha256
        (base32 "18w69gxbnazg5k8bzi76slcqxnbfmrndp548zazz8bpxz3jns699"))))
    (properties `((upstream-name . "denoiSeq")))
    (build-system r-build-system)
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://cran.r-project.org/package=denoiSeq")
    (synopsis "Differential Expression Analysis Using a Bottom-Up Model")
    (description
     "Given count data from two conditions, it determines which transcripts are
differentially expressed across the two conditions using Bayesian inference of
the parameters of a bottom-up model for PCR amplification.  This model is
developed in Ndifon Wilfred, Hilah Gal, Eric Shifrut, Rina Aharoni, Nissan
Yissachar, Nir Waysbort, Shlomit Reich Zeliger, Ruth Arnon, and Nir Friedman
(2012), <http://www.pnas.org/content/109/39/15865.full>, and results in a
distribution for the counts that is a superposition of the binomial and negative
binomial distribution.")
    (license license:gpl2)))

(define-public r-denim
  (package
    (name "r-denim")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "denim" version))
       (sha256
        (base32 "1janjmhfz0vgrmvw0plncxlg7y1sd9578arpjkaivqgqwbkhz4r1"))))
    (properties `((upstream-name . "denim")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridislite r-testthat r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://drthinhong.com/denim/")
    (synopsis
     "Generate and Simulate Deterministic Discrete-Time Compartmental Models")
    (description
     "R package to build and simulate deterministic discrete-time compartmental models
that can be non-Markov.  Length of stay in each compartment can be defined to
follow a parametric distribution (d_exponential(), d_gamma(), d_weibull(),
d_lognormal()) or a non-parametric distribution (nonparametric()).  Other
supported types of transition from one compartment to another includes fixed
transition (constant()), multinomial (multinomial()), fixed transition
probability (transprob()).")
    (license license:expat)))

(define-public r-denguedatahub
  (package
    (name "r-denguedatahub")
    (version "2.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "denguedatahub" version))
       (sha256
        (base32 "1s7in7hh90gs9lzdijdl8q2xx24dbvslyd0ykdl7l3sn7qf4cp92"))))
    (properties `((upstream-name . "denguedatahub")))
    (build-system r-build-system)
    (inputs (list))
    (propagated-inputs (list r-xml2
                             r-tidyr
                             r-tibble
                             r-tabulapdf
                             r-stringr
                             r-rvest
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-lifecycle
                             r-here
                             r-dplyr))
    (home-page "https://denguedatahub.netlify.app/")
    (synopsis "Tidy Format Datasets of Dengue by Country")
    (description
     "This package provides a weekly, monthly, yearly summary of dengue cases by
state/ province/ country.")
    (license license:gpl3)))

(define-public r-dendser
  (package
    (name "r-dendser")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DendSer" version))
       (sha256
        (base32 "1naz8sx5ksb3gqhgfsgdsf5377c96za829m7lmbpr7zlzlxg5jyf"))))
    (properties `((upstream-name . "DendSer")))
    (build-system r-build-system)
    (propagated-inputs (list r-seriation r-gclus))
    (home-page "https://cran.r-project.org/package=DendSer")
    (synopsis "Dendrogram Seriation: Ordering for Visualisation")
    (description
     "Re-arranges a dendrogram to optimize visualisation-based cost functions.")
    (license license:gpl2)))

(define-public r-dendrotools
  (package
    (name "r-dendrotools")
    (version "1.2.13")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dendroTools" version))
       (sha256
        (base32 "1dvisplghjyh607ns5xnwv1v8bg7i05sp4w96g6bmkwpgshaa6b0"))))
    (properties `((upstream-name . "dendroTools")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis
                             r-scales
                             r-reshape2
                             r-randomforest
                             r-psych
                             r-plotly
                             r-oce
                             r-mlmetrics
                             r-magrittr
                             r-lubridate
                             r-knitr
                             r-ggplot2
                             r-dplyr
                             r-dplr
                             r-cubist
                             r-brnn
                             r-boot))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jernejjevsenak/dendroTools")
    (synopsis
     "Linear and Nonlinear Methods for Analyzing Daily and Monthly Dendroclimatological Data")
    (description
     "This package provides novel dendroclimatological methods, primarily used by the
Tree-ring research community.  There are four core functions.  The first one is
daily_response(), which finds the optimal sequence of days that are related to
one or more tree-ring proxy records.  Similar function is
daily_response_seascorr(), which implements partial correlations in the analysis
of daily response functions.  For the enthusiast of monthly data, there is
monthly_response() function.  The last core function is compare_methods(), which
effectively compares several linear and nonlinear regression algorithms on the
task of climate reconstruction.")
    (license license:gpl3)))

(define-public r-dendrosync
  (package
    (name "r-dendrosync")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DendroSync" version))
       (sha256
        (base32 "0jypfdjcjqv2vd3l52hq696gdni303dw5l0nq9hhngc18v2imqa2"))))
    (properties `((upstream-name . "DendroSync")))
    (build-system r-build-system)
    (propagated-inputs (list r-nlme r-gridextra r-ggplot2))
    (home-page "https://bitbucket.org/josucham/dendrosync/src/issues/")
    (synopsis
     "Set of Tools for Calculating Spatial Synchrony Between Tree-Ring Chronologies")
    (description
     "This package provides functions for the calculation and plotting of synchrony in
tree growth from tree-ring width chronologies (TRW index).  It combines
variance-covariance (VCOV) mixed modelling with functions that quantify the
degree to which the TRW chronologies contain a common temporal signal.  It also
implements temporal trends in spatial synchrony using a moving window.  These
methods can also be used with other kind of ecological variables that have
temporal autocorrelation corrected.")
    (license license:gpl2)))

(define-public r-dendronetwork
  (package
    (name "r-dendronetwork")
    (version "0.5.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dendroNetwork" version))
       (sha256
        (base32 "0jns6nfihb9wqz4sh8pbsy01kp0ml2x16jls4vqhixkbfpns4vkf"))))
    (properties `((upstream-name . "dendroNetwork")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-reshape2
                             r-rcy3
                             r-rcolorbrewer
                             r-lifecycle
                             r-igraph
                             r-foreach
                             r-dplyr
                             r-dplr
                             r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ropensci/dendroNetwork")
    (synopsis
     "Create Networks of Dendrochronological Series using Pairwise Similarity")
    (description
     "Creating dendrochronological networks based on the similarity between tree-ring
series or chronologies.  The package includes various functions to compare
tree-ring curves building upon the @code{dplR} package.  The networks can be
used to visualise and understand the relations between tree-ring curves.  These
networks are also very useful to estimate the provenance of wood as described in
Visser (2021) <DOI:10.5334/jcaa.79> or wood-use within a structure/context/site
as described in Visser and Vorst (2022) <DOI:10.1163/27723194-bja10014>.")
    (license license:gpl3+)))

(define-public r-dendrometry
  (package
    (name "r-dendrometry")
    (version "0.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dendrometry" version))
       (sha256
        (base32 "0zxavg34mmxkl5i5mi3x0g1m8pd4f9vc70906iazmmvimvvhp22c"))))
    (properties `((upstream-name . "dendrometry")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dendrometry")
    (synopsis "Forest Estimations and Dendrometric Computations")
    (description
     "Computation of dendrometric and structural parameters from forest inventory
data.  The objective is to provide an user-friendly R package for researchers,
ecologists, foresters, statisticians, loggers and others persons who deal with
forest inventory data.  Useful conversion of angle value from degree to radian,
conversion from angle to slope (in percentage) and their reciprocals as well as
principal angle determination are also included.  Position and dispersion
parameters usually found in forest studies are implemented.  The package
contains Fibonacci series, its extensions and the Golden Number computation.
Useful references are Arcadius Y. J. Akossou, Soufianou Arzouma, Eloi Y.
Attakpa, NoÃ«l H. Fonton and Kouami Kokou (2013) <doi:10.3390/d5010099> and W.
Bonou, R. Glele KakaÃ¯, A.E. Assogbadjo, H.N. Fonton, B. Sinsin (2009)
<doi:10.1016/j.foreco.2009.05.032> .")
    (license license:gpl3)))

(define-public r-dendrometer
  (package
    (name "r-dendrometer")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dendrometeR" version))
       (sha256
        (base32 "1lnnra7hnaxdpck2nkdg30ywq4k9wjv6h1zbkqmm369pw21n3x2b"))))
    (properties `((upstream-name . "dendrometeR")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-pspline r-forecast))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/smiljanicm/dendrometeR")
    (synopsis "Analyzing Dendrometer Data")
    (description
     "Various functions to import, verify, process and plot high-resolution
dendrometer data using daily and stem-cycle approaches as described in
Deslauriers et al, 2007 <doi:10.1016/j.dendro.2007.05.003>.  For more details
about the package please see: Van der Maaten et al.  2016
<doi:10.1016/j.dendro.2016.06.001>.")
    (license license:gpl2+)))

(define-public r-dendroextras
  (package
    (name "r-dendroextras")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dendroextras" version))
       (sha256
        (base32 "0hb7crbgsnbcwvbk05iz5ik45n7zgysmwjj6xc46131yd8l0i1qx"))))
    (properties `((upstream-name . "dendroextras")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dendroextras")
    (synopsis "Extra Functions to Cut, Label and Colour Dendrogram Clusters")
    (description
     "This package provides extra functions to manipulate dendrograms that build on
the base functions provided by the stats package.  The main functionality it is
designed to add is the ability to colour all the edges in an object of class
dendrogram according to cluster membership i.e.  each subtree is coloured, not
just the terminal leaves.  In addition it provides some utility functions to cut
dendrogram and hclust objects and to set/get labels.")
    (license license:gpl2+)))

(define-public r-dendroanalyst
  (package
    (name "r-dendroanalyst")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dendRoAnalyst" version))
       (sha256
        (base32 "16pj1s9ph0gfk9n2kxwinvmxqzwzqlryn7ph15x8navxxwwbss9g"))))
    (properties `((upstream-name . "dendRoAnalyst")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-tidyverse
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-readxl
                             r-pspline
                             r-minpack-lm
                             r-mgcv
                             r-lubridate
                             r-ggplot2
                             r-forecast
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dendRoAnalyst")
    (synopsis "Tool for Processing and Analyzing Dendrometer Data")
    (description
     "There are various functions for managing and cleaning data before the
application of different approaches.  This includes identifying and erasing
sudden jumps in dendrometer data not related to environmental change,
identifying the time gaps of recordings, and changing the temporal resolution of
data to different frequencies.  Furthermore, the package calculates daily
statistics of dendrometer data, including the daily amplitude of tree growth.
Various approaches can be applied to separate radial growth from daily cyclic
shrinkage and expansion due to uptake and loss of stem water.  In addition, it
identifies periods of consecutive days with user-defined climatic conditions in
daily meteorological data, then check what trees are doing during that period.")
    (license license:gpl3)))

(define-public r-demu
  (package
    (name "r-demu")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "demu" version))
       (sha256
        (base32 "1mp5iz8mg0d6cyqi3f6fdhk6x5xxvng5bi13b7jnlp60wpjrq0il"))))
    (properties `((upstream-name . "demu")))
    (build-system r-build-system)
    (propagated-inputs (list r-spam
                             r-rcpparmadillo
                             r-rcpp
                             r-matrix
                             r-fields
                             r-clusterr))
    (home-page "https://cran.r-project.org/package=demu")
    (synopsis "Optimal Design Emulators via Point Processes")
    (description
     "This package implements the Determinantal point process (DPP) based optimal
design emulator described in Pratola, Lin and Craigmile (2018)
<@code{arXiv:1804.02089>} for Gaussian process regression models.  See
<http://www.matthewpratola.com/software> for more information and examples.")
    (license license:agpl3)))

(define-public r-demova
  (package
    (name "r-demova")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DEMOVA" version))
       (sha256
        (base32 "09dqhhhihphhdnplmhdq4q5zwc0qvqhirdrxa9x6fr43vwa5zfp4"))))
    (properties `((upstream-name . "DEMOVA")))
    (build-system r-build-system)
    (propagated-inputs (list r-leaps))
    (home-page "https://cran.r-project.org/package=DEMOVA")
    (synopsis
     "DEvelopment (of Multi-Linear QSPR/QSAR) MOdels VAlidated using Test Set")
    (description
     "Tool for the development of multi-linear QSPR/QSAR models (Quantitative
structure-property/activity relationship).  Theses models are used in chemistry,
biology and pharmacy to find a relationship between the structure of a molecule
and its property (such as activity, toxicology but also physical properties).
The various functions of this package allows: selection of descriptors based of
variances, intercorrelation and user expertise; selection of the best
multi-linear regression in terms of correlation and robustness; methods of
internal validation (Leave-One-Out, Leave-Many-Out, Y-scrambling) and external
using test sets.")
    (license license:gpl2+)))

(define-public r-demoshiny
  (package
    (name "r-demoshiny")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "demoShiny" version))
       (sha256
        (base32 "15zfm8dxsjwqj1xlwz7r61cvnsajw4n6viqkakxrgsfpv1x62qaf"))))
    (properties `((upstream-name . "demoShiny")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=demoShiny")
    (synopsis "Runs a 'Shiny' App as Demo or Lists All Demo 'Shiny' Apps")
    (description
     "Mimics the demo functionality for Shiny apps in a package.  Apps stored to the
package subdirectory inst/shiny can be called by @code{demoShiny(topic}).")
    (license license:gpl3)))

(define-public r-demokin
  (package
    (name "r-demokin")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DemoKin" version))
       (sha256
        (base32 "0ph60ifffg29a88f9qxkx6zvcv8rxl1q5wd39j5zz2fqm3ggz47v"))))
    (properties `((upstream-name . "DemoKin")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-purrr
                             r-progress
                             r-matrixcalc
                             r-matrix
                             r-mass
                             r-magrittr
                             r-lifecycle
                             r-igraph
                             r-dplyr
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/IvanWilli/DemoKin")
    (synopsis "Estimate Population Kin Distribution")
    (description
     "Estimate population kin counts and its distribution by type, age and sex.  The
package implements one-sex and two-sex framework for studying living-death
availability, with time varying rates or not, and multi-stage model.")
    (license license:expat)))

(define-public r-demokde
  (package
    (name "r-demokde")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "demoKde" version))
       (sha256
        (base32 "1yhk77dgl45gs1j8ganr1y8prkczpyh8zrxf93mbrx1y9h54n34x"))))
    (properties `((upstream-name . "demoKde")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=demoKde")
    (synopsis "Kernel Density Estimation for Demonstration Purposes")
    (description
     "Demonstration code showing how (univariate) kernel density estimates are
computed, at least conceptually, and allowing users to experiment with different
kernels, should they so wish.  The method used follows directly the definition,
but gains efficiency by replacing the observations by frequencies in a very fine
grid covering the sample range.  A canonical reference is B. W. Silverman,
(1998) <doi: 10.1201/9781315140919>.  NOTE: the density function in the stats
package uses a more sophisticated method based on the fast Fourier transform and
that function should be used if computational efficiency is a prime
consideration.")
    (license license:gpl2)))

(define-public r-demography
  (package
    (name "r-demography")
    (version "2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "demography" version))
       (sha256
        (base32 "0smkfivhhpa5cz5kh33dh3vl4zb102mjazxsxd382z7cwfqldffd"))))
    (properties `((upstream-name . "demography")))
    (build-system r-build-system)
    (propagated-inputs (list r-strucchange
                             r-rainbow
                             r-mgcv
                             r-hmdhfdplus
                             r-ftsa
                             r-forecast
                             r-cobs))
    (home-page "https://pkg.robjhyndman.com/demography/")
    (synopsis
     "Forecasting Mortality, Fertility, Migration and Population Data")
    (description
     "This package provides functions for demographic analysis including lifetable
calculations; Lee-Carter modelling; functional data analysis of mortality rates,
fertility rates, net migration numbers; and stochastic population forecasting.")
    (license license:gpl3+)))

(define-public r-demographictable
  (package
    (name "r-demographictable")
    (version "0.1.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DemographicTable" version))
       (sha256
        (base32 "1vxz426ryi8mdvcyzs7lckv4yy7r8mai0y3jw2hzhpgnx6gb59sp"))))
    (properties `((upstream-name . "DemographicTable")))
    (build-system r-build-system)
    (propagated-inputs (list r-xtable r-flextable r-e1071))
    (home-page "https://cran.r-project.org/package=DemographicTable")
    (synopsis "Creating Demographic Table")
    (description
     "This package provides functions for creating demographic table with simple
summary statistics, with optional comparison(s) over one or more groups.
Numeric variables are summarized in means, standard deviations, medians,
inter-quartile-ranges (IQR), skewness, Shapiro-Wilk normality test and ranges,
and compared using two-sample t-test, Wilcoxon test, ANOVA and/or Kruskal-Wallis
test.  Logical and factor variables are summarized in counts and percentages and
compared using chi-squared test and/or Fisher's exact test.")
    (license license:gpl2)))

(define-public r-demographic
  (package
    (name "r-demographic")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "demoGraphic" version))
       (sha256
        (base32 "0b2fqa0z875wwd7qdqh2qfvkzh2cpbmck4smf9c0p31wv5yin0sq"))))
    (properties `((upstream-name . "demoGraphic")))
    (build-system r-build-system)
    (propagated-inputs (list r-officer r-mass r-magrittr))
    (home-page "https://cran.r-project.org/package=demoGraphic")
    (synopsis
     "Providing Demographic Table with the P-Value, Standardized Mean Difference Value")
    (description
     "The Demographic Table in R combines contingency table for categorical variables,
mean and standard deviation for continuous variables.  t-test, chi-square test
and Fisher's exact test calculated the p-value of two groups.  The standardized
mean difference were performed with 95 % confident interval, and writing table
into document file.")
    (license license:gpl3)))

(define-public r-demografixer
  (package
    (name "r-demografixer")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DemografixeR" version))
       (sha256
        (base32 "16qd1wbzizvg86bqkk8fvb53g6h30l5v99cjxpnr43qf0r4drz3j"))))
    (properties `((upstream-name . "DemografixeR")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-jsonlite r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://matbmeijer.github.io/DemografixeR")
    (synopsis "Extrapolate Gender, Age and Nationality of a Name")
    (description
     "Connects to the <https://genderize.io/>, <https://agify.io/> and
<https://nationalize.io/> APIs to estimate gender, age and nationality of a
first name.")
    (license license:expat)))

(define-public r-demogr
  (package
    (name "r-demogr")
    (version "0.6.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "demogR" version))
       (sha256
        (base32 "06x82ffbdv6ifl8xh52d3npdwha67v1ylfjp78j5pa4wdqkg221b"))))
    (properties `((upstream-name . "demogR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=demogR")
    (synopsis "Analysis of Age-Structured Demographic Models")
    (description "Construction and analysis of matrix population models in R.")
    (license license:gpl2+)))

(define-public r-demodelr
  (package
    (name "r-demodelr")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "demodelr" version))
       (sha256
        (base32 "1jldvlw8xl5hbyw4m443r41nw9ck7dmkd4rmag4wqw4scra7qj46"))))
    (properties `((upstream-name . "demodelr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-rlang
                             r-purrr
                             r-ggplot2
                             r-ggally
                             r-formula-tools
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=demodelr")
    (synopsis "Simulating Differential Equations with Data")
    (description
     "Designed to support the visualization, numerical computation, qualitative
analysis, model-data fusion, and stochastic simulation for autonomous systems of
differential equations.  Euler and Runge-Kutta methods are implemented, along
with tools to visualize the two-dimensional phaseplane.  Likelihood surfaces and
a simple Markov Chain Monte Carlo parameter estimator can be used for model-data
fusion of differential equations and empirical models.  The Euler-Maruyama
method is provided for simulation of stochastic differential equations.  The
package was originally written for internal use to support teaching by Zobitz,
and refined to support the text \"Exploring modeling with data and differential
equations using R\" by John Zobitz (2021)
<https://jmzobitz.github.io/@code{ModelingWithR/index.html>}.")
    (license license:expat)))

(define-public r-demodecomp
  (package
    (name "r-demodecomp")
    (version "1.14.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DemoDecomp" version))
       (sha256
        (base32 "1ks0lqnq811gkx6k1440v5wkh9pjrbpdkw5c5hc0iclx3lfs6g7n"))))
    (properties `((upstream-name . "DemoDecomp")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-numderiv))
    (home-page "https://cran.r-project.org/package=DemoDecomp")
    (synopsis "Decompose Demographic Functions")
    (description
     "Three general demographic decomposition methods: Pseudo-continuous decomposition
proposed by Horiuchi, Wilmoth, and Pletcher (2008) <doi:10.1353/dem.0.0033>,
stepwise replacement decomposition proposed by Andreev, Shkolnikov and Begun
(2002) <doi:10.4054/@code{DemRes.2002.7.14>}, and lifetable response experiments
proposed by Caswell (1989) <doi:10.1016/0304-3800(89)90019-7>.")
    (license license:gpl3)))

(define-public r-demic
  (package
    (name "r-demic")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "demic" version))
       (sha256
        (base32 "1vxh8rlmq3jnrv0gzaywilqhn60vq8b56skbqgzghzk5qg95gi0k"))))
    (properties `((upstream-name . "demic")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2 r-matrix r-lme4))
    (home-page "https://github.com/Ulthran/DEMIC")
    (synopsis "Dynamic Estimator of Microbial Communities")
    (description
     "Multi-sample algorithm based on contigs and coverage values, to infer the
relative distances of contigs from the replication origin and to accurately
compare bacterial growth rates between samples.  Yuan Gao and Hongzhe Li (2018)
<doi:10.1038/s41592-018-0182-0>.")
    (license license:gpl3+)))

(define-public r-dematel
  (package
    (name "r-dematel")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dematel" version))
       (sha256
        (base32 "1m84sd46cg7188wnjx09g88xvxdp7i0mdxnynwlqkgcmnwx4bdjw"))))
    (properties `((upstream-name . "dematel")))
    (build-system r-build-system)
    (propagated-inputs (list r-knitr r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dematel")
    (synopsis "Decision Making Trial and Evaluation Laboratory Technique in R")
    (description
     "Developed to Solve the Multi-Criteria Decision Making Problems with Decision
Making Trial and Evaluation Laboratory Technique in R.")
    (license license:gpl3)))

(define-public r-dem
  (package
    (name "r-dem")
    (version "0.0.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DEM" version))
       (sha256
        (base32 "17ibq5cavzkl2vfrmrkz77m28l4xpj97skad5pfvk1nhzyrg2k1l"))))
    (properties `((upstream-name . "DEM")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm))
    (home-page "https://cran.r-project.org/package=DEM")
    (synopsis
     "The Distributed EM Algorithms in Multivariate Gaussian Mixture Models")
    (description
     "The distributed expectation maximization algorithms are used to solve parameters
of multivariate Gaussian mixture models.  The philosophy of the package is
described in Guo, G. (2022) <doi:10.1080/02664763.2022.2053949>.")
    (license license:expat)))

(define-public r-deltd
  (package
    (name "r-deltd")
    (version "2.6.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DELTD" version))
       (sha256
        (base32 "0s5qiy2cb6fcm9fnbzmqs2x39im5r1vb45avh9isc71f7xl3my36"))))
    (properties `((upstream-name . "DELTD")))
    (build-system r-build-system)
    (home-page "https://CRAN.R-project.org/package=DELTD")
    (synopsis "Kernel Density Estimation using Lifetime Distributions")
    (description
     "This package provides a collection of asymmetrical kernels belong to lifetime
distributions for kernel density estimation is presented.  Mean Squared Errors
(MSE) are calculated for estimated curves.  For this purpose, R functions allow
the distribution to be Gamma, Exponential or Weibull.  For details see Chen
(2000a,b), Jin and Kawczak (2003) and Salha et al. (2014)
<doi:10.12988/pms.2014.4616>.")
    (license license:gpl2)))

(define-public r-deltaplotr
  (package
    (name "r-deltaplotr")
    (version "1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deltaPlotR" version))
       (sha256
        (base32 "15vjg3viyfrxvvh34p8i7j8p0vpg5628g8198adhi0i2ri3ygz9a"))))
    (properties `((upstream-name . "deltaPlotR")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=deltaPlotR")
    (synopsis
     "Identification of Dichotomous Differential Item Functioning (DIF) using Angoff's Delta Plot Method")
    (description
     "The @code{deltaPlotR} package implements Angoff's Delta Plot method to detect
dichotomous DIF. Several detection thresholds are included, either from
multivariate normality assumption or by prior determination.  Item purification
is supported (Magis and Facon (2014) <doi:10.18637/jss.v059.c01>).")
    (license license:gpl2+)))

(define-public r-deltaman
  (package
    (name "r-deltaman")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DeltaMAN" version))
       (sha256
        (base32 "08barq4s7m3migjs80207n6l10pr3v2hb1dy72fi59j9x9xgnn4v"))))
    (properties `((upstream-name . "DeltaMAN")))
    (build-system r-build-system)
    (propagated-inputs (list r-xtable r-shinymatrix r-shinybs r-shiny r-knitr))
    (home-page "https://cran.r-project.org/package=DeltaMAN")
    (synopsis "Delta Measurement of Agreement for Nominal Data")
    (description
     "Analysis of agreement for nominal data between two raters using the Delta model.
 This model is proposed as an alternative to the widespread measure Cohen kappa
coefficient, which performs poorly when the marginal distributions are very
asymmetric (Martin-Andres and Femia-Marzo (2004), <doi:10.1348/000711004849268>;
Martin-Andres and Femia-Marzo (2008) <doi:10.1080/03610920701669884>).  The
package also contains a function to perform a massive analysis of multiple
raters against a gold standard.  A shiny app is also provided to obtain the
measures of nominal agreement between two raters.")
    (license license:lgpl3)))

(define-public r-deltaccd
  (package
    (name "r-deltaccd")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deltaccd" version))
       (sha256
        (base32 "1iqyycjfmclr9y8gfj61naxwafjgmfwahyrc110qxzb239b501rw"))))
    (properties `((upstream-name . "deltaccd")))
    (build-system r-build-system)
    (propagated-inputs (list r-statmod
                             r-scales
                             r-rlang
                             r-ggplot2
                             r-foreach
                             r-dorng
                             r-data-table))
    (home-page "https://deltaccd.hugheylab.org")
    (synopsis "Quantify Rhythmic Gene Co-Expression Relative to a Reference")
    (description
     "Infer progression of circadian rhythms in transcriptome data in which samples
are not labeled with time of day and coverage of the circadian cycle may be
incomplete.  See Shilts et al. (2018) <doi:10.7717/peerj.4327>.")
    (license license:gpl2)))

(define-public r-delta
  (package
    (name "r-delta")
    (version "0.2.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Delta" version))
       (sha256
        (base32 "0bi9qca4ky481zycp8r7ihvqfjkpvi7hb9wrjsw9avawqa6ck9bv"))))
    (properties `((upstream-name . "Delta")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=Delta")
    (synopsis "Measure of Agreement Between Two Raters")
    (description
     "Measure of agreement delta was originally by MartÃ­n & Femia (2004)
<DOI:10.1348/000711004849268>.  Since then has been considered as agreement
measure for different fields, since their behavior is usually better than the
usual kappa index by Cohen (1960) <DOI:10.1177/001316446002000104>.  The main
issue with delta is that can not be computed by hand contrary to kappa.  The
current algorithm is based on the Version 5 of the delta windows program that
can be found on
<https://www.ugr.es/~bioest/software/delta/cmd.php?seccion=downloads>.")
    (license license:gpl3)))

(define-public r-delayedeffect-design
  (package
    (name "r-delayedeffect-design")
    (version "1.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DelayedEffect.Design" version))
       (sha256
        (base32 "0iplpnhxzipvyk89dn13hi0pw1yqfbi8dm4dp2xmvn3avk76pjgs"))))
    (properties `((upstream-name . "DelayedEffect.Design")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DelayedEffect.Design")
    (synopsis
     "Sample Size and Power Calculations using the APPLE, SEPPLE, APPLE+ and SEPPLE+ Methods")
    (description
     "This package provides sample size and power calculations when the treatment
time-lag effect is present and the lag duration is either homogeneous across the
individual subject, or varies heterogeneously from individual to individual
within a certain domain and following a specific pattern.  The methods used are
described in Xu, Z., Zhen, B., Park, Y., & Zhu, B. (2017)
<doi:10.1002/sim.7157>.")
    (license license:gpl2)))

(define-public r-delayed
  (package
    (name "r-delayed")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "delayed" version))
       (sha256
        (base32 "17v9gis82yn0fvp4apv906sz8j77cr5rlj4xxxa3vkfvh196a40l"))))
    (properties `((upstream-name . "delayed")))
    (build-system r-build-system)
    (propagated-inputs (list r-visnetwork
                             r-uuid
                             r-rstackdeque
                             r-rlang
                             r-r6
                             r-r-utils
                             r-r-oo
                             r-progress
                             r-igraph
                             r-future
                             r-data-table
                             r-bbmisc))
    (native-inputs (list r-knitr))
    (home-page "https://tlverse.org/delayed/")
    (synopsis "Framework for Parallelizing Dependent Tasks")
    (description
     "Mechanisms to parallelize dependent tasks in a manner that optimizes the compute
resources available.  It provides access to \"delayed\" computations, which may be
parallelized using futures.  It is, to an extent, a facsimile of the Dask
library (<https://www.dask.org/>), for the Python language.")
    (license license:gpl3)))

(define-public r-dejavu
  (package
    (name "r-dejavu")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dejaVu" version))
       (sha256
        (base32 "102jg8bfhxbynk6v8ly73pkkhbqvgx4x1gmr7kxkdc648zspg48d"))))
    (properties `((upstream-name . "dejaVu")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dejaVu")
    (synopsis "Multiple Imputation for Recurrent Events")
    (description
     "This package performs reference based multiple imputation of recurrent event
data based on a negative binomial regression model, as described by Keene et al
(2014) <doi:10.1002/pst.1624>.")
    (license license:gpl2+)))

(define-public r-dehogt
  (package
    (name "r-dehogt")
    (version "0.99.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DEHOGT" version))
       (sha256
        (base32 "01r45xzy1bhh3fprcqnnibhlmn5nhv08l897js137k4gnb1jc5mn"))))
    (properties `((upstream-name . "DEHOGT")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-foreach r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ahshen26/DEHOGT")
    (synopsis
     "Differentially Expressed Heterogeneous Overdispersion Gene Test for Count Data")
    (description
     "This package implements a generalized linear model approach for detecting
differentially expressed genes across treatment groups in count data.  The
package supports both quasi-Poisson and negative binomial models to handle
over-dispersion, ensuring robust identification of differential expression.  It
allows for the inclusion of treatment effects and gene-wise covariates, as well
as normalization factors for accurate scaling across samples.  Additionally, it
incorporates statistical significance testing with options for p-value
adjustment and log2 fold range thresholds, making it suitable for RNA-seq
analysis as described in by Xu et al., (2024)
<doi:10.1371/journal.pone.0300565>.")
    (license license:gpl3)))

(define-public r-degross
  (package
    (name "r-degross")
    (version "0.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "degross" version))
       (sha256
        (base32 "17n389a0k4jswgs908bcdhi410wpd1ljxh5izv35cldfq7dhjb3k"))))
    (properties `((upstream-name . "degross")))
    (build-system r-build-system)
    (propagated-inputs (list r-cubicbsplines))
    (home-page "https://cran.r-project.org/package=degross")
    (synopsis "Density Estimation from GROuped Summary Statistics")
    (description
     "Estimation of a density from grouped (tabulated) summary statistics evaluated in
each of the big bins (or classes) partitioning the support of the variable.
These statistics include class frequencies and central moments of order one up
to four.  The log-density is modelled using a linear combination of penalised
B-splines.  The multinomial log-likelihood involving the frequencies adds up to
a roughness penalty based on the differences in the coefficients of neighbouring
B-splines and the log of a root-n approximation of the sampling density of the
observed vector of central moments in each class.  The so-obtained penalized
log-likelihood is maximized using the EM algorithm to get an estimate of the
spline parameters and, consequently, of the variable density and related
quantities such as quantiles, see Lambert, P. (2021) <@code{arXiv:2107.03883>}
for details.")
    (license license:gpl3)))

(define-public r-degreenet
  (package
    (name "r-degreenet")
    (version "1.3-6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "degreenet" version))
       (sha256
        (base32 "1z9b91c5ngjs3rngfvnk3j5q5vjnj08y8amd2xm50xyvlkcblgxh"))))
    (properties `((upstream-name . "degreenet")))
    (build-system r-build-system)
    (propagated-inputs (list r-network r-igraph))
    (home-page "https://statnet.org")
    (synopsis "Models for Skewed Count Distributions Relevant to Networks")
    (description
     "Likelihood-based inference for skewed count distributions, typically of degrees
used in network modeling. \"degreenet\" is a part of the \"statnet\" suite of
packages for network analysis.  See Jones and Handcock
<doi:10.1098/rspb.2003.2369>.")
    (license (license:fsdg-compatible "GPL-3 + file LICENSE"))))

(define-public r-degre
  (package
    (name "r-degre")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DEGRE" version))
       (sha256
        (base32 "040hfpvqwl8r0iazwpnq7fmkydsxqc7mck7wbjqf6c19cw3zziz7"))))
    (properties `((upstream-name . "DEGRE")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-parglm
                             r-glmmtmb
                             r-ggrepel
                             r-ggpubr
                             r-ggplot2
                             r-foreach
                             r-dplyr
                             r-car))
    (home-page "https://cran.r-project.org/package=DEGRE")
    (synopsis
     "Inferring Differentially Expressed Genes using Generalized Linear Mixed Models")
    (description
     "Genes that are differentially expressed between two or more experimental
conditions can be detected in RNA-Seq.  A high biological variability may impact
the discovery of these genes once it may be divergent between the fixed effects.
 However, this variability can be covered by the random effects.  DEGRE was
designed to identify the differentially expressed genes considering fixed and
random effects on individuals.  These effects are identified earlier in the
experimental design matrix.  DEGRE has the implementation of preprocessing
procedures to clean the near zero gene reads in the count matrix, normalize by
RLE published in the DESeq2 package, Love et al. (2014)
<doi:10.1186/s13059-014-0550-8> and it fits a regression for each gene using the
Generalized Linear Mixed Model with the negative binomial distribution, followed
by a Wald test to assess the regression coefficients.")
    (license license:artistic2.0)))

(define-public r-degday
  (package
    (name "r-degday")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "degday" version))
       (sha256
        (base32 "07a5zl56hh5vl94alsd9kvjdj5vy0vgx8dpyvr0qdiwj9m8a830y"))))
    (properties `((upstream-name . "degday")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-magrittr r-crayon))
    (home-page "https://github.com/ucanr-igis/degday/")
    (synopsis "Compute Degree Days")
    (description
     "Compute degree days from daily min and max temperatures for modeling plant and
insect development.")
    (license license:gpl3+)))

(define-public r-deformula
  (package
    (name "r-deformula")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deformula" version))
       (sha256
        (base32 "18jrznpw2vqb658wv88yq4x7z44ilkjg0xb5v2lww87wxbv4m0gj"))))
    (properties `((upstream-name . "deformula")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-cpp11))
    (home-page "https://github.com/okamumu/deformula/")
    (synopsis
     "Integration of One-Dimensional Functions with Double Exponential Formulas")
    (description
     "Numerical quadrature of functions of one variable over a finite or infinite
interval with double exponential formulas.")
    (license license:expat)))

(define-public r-deform
  (package
    (name "r-deform")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deform" version))
       (sha256
        (base32 "0crnwp5z3wy2zx273a7lchvyv5k5fyclhqrb9q0qhhv56drgvm0y"))))
    (properties `((upstream-name . "deform")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-mass))
    (home-page "https://cran.r-project.org/package=deform")
    (synopsis "Spatial Deformation and Dimension Expansion Gaussian Processes")
    (description
     "This package provides methods for fitting nonstationary Gaussian process models
by spatial deformation, as introduced by Sampson and Guttorp (1992)
<doi:10.1080/01621459.1992.10475181>, and by dimension expansion, as introduced
by Bornn et al. (2012) <doi:10.1080/01621459.2011.646919>.  Low-rank thin-plate
regression splines, as developed in Wood, S.N. (2003)
<doi:10.1111/1467-9868.00374>, are used to either transform co-ordinates or
create new latent dimensions.")
    (license license:gpl3)))

(define-public r-deforestable
  (package
    (name "r-deforestable")
    (version "3.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deforestable" version))
       (sha256
        (base32 "0p8psbsjxmc456flypdw2kh8kjsy2hw13nfcdilg527iy1dpif6i"))))
    (properties `((upstream-name . "deforestable")))
    (build-system r-build-system)
    (inputs (list sqlite proj geos gdal))
    (propagated-inputs (list r-terra
                             r-stableestim
                             r-rcpparmadillo
                             r-rcpp
                             r-plyr
                             r-jpeg))
    (home-page "https://cran.r-project.org/package=deforestable")
    (synopsis "Classify RGB Images into Forest or Non-Forest")
    (description
     "This package implements two out-of box classifiers presented in
<doi:10.48550/@code{arXiv.2112.01063>} for distinguishing forest and non-forest
terrain images.  Under these algorithms, there are frequentist approaches: one
parametric, using stable distributions, and another one- non-parametric, using
the squared Mahalanobis distance.  The package also contains functions for data
handling and building of new classifiers as well as some test data set.")
    (license license:gpl3)))

(define-public r-deflist
  (package
    (name "r-deflist")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deflist" version))
       (sha256
        (base32 "0m19yz3x4gn8zad7lgf343r41bqjvd5a279ykll8cw04y74c43lm"))))
    (properties `((upstream-name . "deflist")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-purrr r-memoise r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://bbuchsbaum.github.io/deflist/")
    (synopsis
     "Deferred List - A Read-Only List-Like Object with Deferred Access")
    (description
     "This package implements the deflist class, a read-only list-like object that
accesses its elements via a function.  The deflist class can be used to model
deferred access to data or computations by routing indexed list access to a
function.  This approach is particularly useful when sequential list-like access
to data is required but holding all the data in memory at once is not feasible.
The package also provides utilities for memoisation and caching to optimize
access to frequently requested elements.")
    (license license:lgpl2.1+)))

(define-public r-deflatebr
  (package
    (name "r-deflatebr")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deflateBR" version))
       (sha256
        (base32 "17zsy10k12gmffbk7nagi60xj347q0bf7wr885fiylqz2xiy9fl9"))))
    (properties `((upstream-name . "deflateBR")))
    (build-system r-build-system)
    (propagated-inputs (list r-lubridate r-httr r-dplyr))
    (home-page "https://github.com/meirelesff/deflatebr/")
    (synopsis "Deflate Nominal Brazilian Reais")
    (description
     "Simple functions to deflate nominal Brazilian Reais using several popular price
indexes downloaded from the Brazilian Institute for Applied Economic Research.")
    (license license:expat)))

(define-public r-defit
  (package
    (name "r-defit")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deFit" version))
       (sha256
        (base32 "0vsixnjz531i8m3qbv1cx1nv8gyjvvy2ys6i48zc9ncb56issjad"))))
    (properties `((upstream-name . "deFit")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6 r-ggplot2 r-desolve))
    (home-page "https://cran.r-project.org/package=deFit")
    (synopsis "Fitting Differential Equations to Time Series Data")
    (description
     "Use numerical optimization to fit ordinary differential equations (ODEs) to time
series data to examine the dynamic relationships between variables or the
characteristics of a dynamical system.  It can now be used to estimate the
parameters of ODEs up to second order, and can also apply to multilevel systems.
 See <https://github.com/yueqinhu/defit> for details.")
    (license license:gpl3+)))

(define-public r-definer
  (package
    (name "r-definer")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "defineR" version))
       (sha256
        (base32 "1wm6ynicwk2dlx8m0k45kc1pa8i3z8w78xk3v40szy2ys5j80m7v"))))
    (properties `((upstream-name . "defineR")))
    (build-system r-build-system)
    (propagated-inputs (list r-xslt
                             r-xml2
                             r-reporter
                             r-readxl
                             r-openxlsx
                             r-libr
                             r-glue
                             r-common))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=defineR")
    (synopsis "Creates Define XML Documents")
    (description
     "This package creates define.xml documents used for regulatory submissions based
on spreadsheet metadata.  Can also help create metadata and generate HTML data
explorer.")
    (license license:cc0)))

(define-public r-defineoptions
  (package
    (name "r-defineoptions")
    (version "0.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "defineOptions" version))
       (sha256
        (base32 "1al08lqiy8x6jc1mrxm785pqqlfqlhzxbr2lwnixj6mqmkqlwp6g"))))
    (properties `((upstream-name . "defineOptions")))
    (build-system r-build-system)
    (home-page "https://github.com/niceume/defineOptions")
    (synopsis "Define and Parse Command Line Options")
    (description
     "Parses command line arguments and supplies values to scripts.  Users can specify
names to which parsed inputs are assigned, value types into which inputs are
cast, long options or short options, input splitters and callbacks that define
how options should be specified and how input values are supplied.")
    (license license:gpl3+)))

(define-public r-default
  (package
    (name "r-default")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "default" version))
       (sha256
        (base32 "0hzxgp9la9kll5cw3m4gd02rii571xsn1v53kz407k7k6rfg5mda"))))
    (properties `((upstream-name . "default")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=default")
    (synopsis "Change the Default Arguments in R Functions")
    (description
     "This package provides a simple syntax to change the default values for function
arguments, whether they are in packages or defined locally.")
    (license license:expat)))

(define-public r-deevd
  (package
    (name "r-deevd")
    (version "1.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DEEVD" version))
       (sha256
        (base32 "1wa3h0z5sk8zrwblzb8w7hgj9yqw56vqi3vsnpva53qynf42r2n7"))))
    (properties `((upstream-name . "DEEVD")))
    (build-system r-build-system)
    (propagated-inputs (list r-evd))
    (home-page "https://CRAN.R-project.org/package=DEEVD")
    (synopsis "Density Estimation by Extreme Value Distributions")
    (description
     "This package provides mean squared error (MSE) and plot the kernel densities
related to extreme value distributions with their estimated values.  By using
Gumbel and Weibull Kernel.  See Salha et al. (2014) <doi:10.4236/ojs.2014.48061>
and Khan and Akbar (2021) <doi:10.4236/ojs.2021.112018 >.")
    (license license:gpl2)))

(define-public r-deet
  (package
    (name "r-deet")
    (version "1.0.12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DEET" version))
       (sha256
        (base32 "19y9s2v65z7g36akpyr0ljzch4csq9la0cafkh5xb4d18xpr2h0h"))))
    (properties `((upstream-name . "DEET")))
    (build-system r-build-system)
    (propagated-inputs (list r-pbapply
                             r-glmnet
                             r-ggrepel
                             r-ggplot2
                             r-dplyr
                             r-downloader
                             r-activepathways))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DEET")
    (synopsis "Differential Expression Enrichment Tool")
    (description
     "Abstract of Manuscript.  Differential gene expression analysis using RNA
sequencing (RNA-seq) data is a standard approach for making biological
discoveries.  Ongoing large-scale efforts to process and normalize publicly
available gene expression data enable rapid and systematic reanalysis.  While
several powerful tools systematically process RNA-seq data, enabling their
reanalysis, few resources systematically recompute differentially expressed
genes (DEGs) generated from individual studies.  We developed a robust
differential expression analysis pipeline to recompute 3162 human DEG lists from
The Cancer Genome Atlas, Genotype-Tissue Expression Consortium, and 142 studies
within the Sequence Read Archive.  After measuring the accuracy of the
recomputed DEG lists, we built the Differential Expression Enrichment Tool
(DEET), which enables users to interact with the recomputed DEG lists.  DEET,
available through CRAN and RShiny, systematically queries which of the
recomputed DEG lists share similar genes, pathways, and TF targets to their own
gene lists.  DEET identifies relevant studies based on shared results with the
userâs gene lists, aiding in hypothesis generation and data-driven literature
review.  Sokolowski, Dustin J., et al. \"Differential Expression Enrichment Tool
(DEET): an interactive atlas of human differential gene expression.\" Nucleic
Acids Research Genomics and Bioinformatics (2023).")
    (license license:gpl3)))

(define-public r-deeptrafo
  (package
    (name "r-deeptrafo")
    (version "0.1-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deeptrafo" version))
       (sha256
        (base32 "16lxxd75j9bwapfx716b9fmqfz6ms4x5g98wc1yykiahjpbj8156"))))
    (properties `((upstream-name . "deeptrafo")))
    (build-system r-build-system)
    (propagated-inputs (list r-variables
                             r-tfprobability
                             r-tensorflow
                             r-survival
                             r-reticulate
                             r-r6
                             r-purrr
                             r-mlt
                             r-keras
                             r-formula
                             r-deepregression))
    (home-page "https://cran.r-project.org/package=deeptrafo")
    (synopsis "Fitting Deep Conditional Transformation Models")
    (description
     "Allows for the specification of deep conditional transformation models (DCTMs)
and ordinal neural network transformation models, as described in Baumann et al
(2021) <doi:10.1007/978-3-030-86523-8_1> and Kook et al (2022)
<doi:10.1016/j.patcog.2021.108263>.  Extensions such as autoregressive DCTMs
(Ruegamer et al, 2022, <doi:10.48550/@code{arXiv.2110.08248>}) and
transformation ensembles (Kook et al, 2022,
<doi:10.48550/@code{arXiv.2205.12729>}) are implemented.")
    (license license:gpl3)))

(define-public r-deeptime
  (package
    (name "r-deeptime")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deeptime" version))
       (sha256
        (base32 "1hk5c7x0wrinmi51xgnh9srisfm2n98xbzaxp7i2lpz4fvphd7im"))))
    (properties `((upstream-name . "deeptime")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales
                             r-rlang
                             r-lifecycle
                             r-lattice
                             r-gtable
                             r-grimport2
                             r-gridextra
                             r-ggplot2
                             r-ggforce
                             r-ggfittext
                             r-curl
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://williamgearty.com/deeptime/")
    (synopsis "Plotting Tools for Anyone Working in Deep Time")
    (description
     "Extends the functionality of other plotting packages (notably ggplot2') to help
facilitate the plotting of data over long time intervals, including, but not
limited to, geological, evolutionary, and ecological data.  The primary goal of
deeptime is to enable users to add highly customizable timescales to their
visualizations.  Other functions are also included to assist with other areas of
deep time visualization.")
    (license license:gpl3+)))

(define-public r-deeprstudio
  (package
    (name "r-deeprstudio")
    (version "0.0.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deepRstudio" version))
       (sha256
        (base32 "0fqzxc8wnfvg7fjpmd02pbf7wnqa32n3pm42iwj6i9hbdx558rin"))))
    (properties `((upstream-name . "deepRstudio")))
    (build-system r-build-system)
    (propagated-inputs (list r-rstudioapi
                             r-jsonlite
                             r-httr
                             r-crayon
                             r-clipr
                             r-assertthat))
    (home-page "https://kumes.github.io/deepRstudio/")
    (synopsis
     "Seamless Language Translation in 'RStudio' using 'DeepL' API and 'Rstudioapi'")
    (description
     "Enhancing cross-language compatibility within the RStudio environment and
supporting seamless language understanding, the @code{deepRstudio} package
leverages the power of the @code{DeepL} API (see
<https://www.deepl.com/docs-api>) to enable seamless, fast, accurate, and
affordable translation of code comments, documents, and text.  This package
offers the ability to translate selected text into English (EN), as well as from
English into various languages, namely Japanese (JA), Chinese (ZH), Spanish
(ES), French (FR), Russian (RU), Portuguese (PT), and Indonesian (ID).  With
much of the text being written in English, the emphasis is on compatibility from
English.  It is also designed for developers working on multilingual projects
and data analysts collaborating with international teams, simplifying the
translation process and making code more accessible and comprehensible to people
with diverse language backgrounds.  This package uses the rstudioapi package and
@code{DeepL} API, and is simply implemented, executed from addins or via
shortcuts on RStudio'.  With just a few steps, content can be translated between
supported languages, promoting better collaboration and expanding the global
reach of work.  The functionality of this package works only on RStudio using
rstudioapi'.")
    (license license:artistic2.0)))

(define-public r-deepregression
  (package
    (name "r-deepregression")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deepregression" version))
       (sha256
        (base32 "15d33dsdhmw7n172rlsg70921d3z3bkn088qj565iclzmxknyfzj"))))
    (properties `((upstream-name . "deepregression")))
    (build-system r-build-system)
    (propagated-inputs (list r-tfruns
                             r-tfprobability
                             r-tensorflow
                             r-reticulate
                             r-r6
                             r-mgcv
                             r-matrix
                             r-magrittr
                             r-keras
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=deepregression")
    (synopsis "Fitting Deep Distributional Regression")
    (description
     "Allows for the specification of semi-structured deep distributional regression
models which are fitted in a neural network as proposed by Ruegamer et al.
(2023) <doi:10.18637/jss.v105.i02>.  Predictors can be modeled using structured
(penalized) linear effects, structured non-linear effects or using an
unstructured deep network model.")
    (license license:gpl3)))

(define-public r-deepredeff
  (package
    (name "r-deepredeff")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deepredeff" version))
       (sha256
        (base32 "027dsmc3wmm61qc0vybn02c5dbnz5nwf80m9sywci4nhirz978ik"))))
    (properties `((upstream-name . "deepredeff")))
    (build-system r-build-system)
    (propagated-inputs (list r-tensorflow
                             r-seqinr
                             r-rlang
                             r-reticulate
                             r-purrr
                             r-magrittr
                             r-keras
                             r-ggthemes
                             r-ggplot2
                             r-dplyr
                             r-biostrings))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ruthkr/deepredeff/")
    (synopsis "Deep Learning Prediction of Effectors")
    (description
     "This package provides a tool that contains trained deep learning models for
predicting effector proteins.  deepredeff has been trained to identify effector
proteins using a set of known experimentally validated effectors from either
bacteria, fungi, or oomycetes.  Documentation is available via several
vignettes, and the paper by Kristianingsih and @code{MacLean} (2020)
<doi:10.1101/2020.07.08.193250>.")
    (license license:expat)))

(define-public r-deepnn
  (package
    (name "r-deepnn")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deepNN" version))
       (sha256
        (base32 "1wlj70md5vgzad5q2n6qhh076q01zd0k8fsqafmswl4545hmmz69"))))
    (properties `((upstream-name . "deepNN")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix))
    (home-page "https://cran.r-project.org/package=deepNN")
    (synopsis "Deep Learning")
    (description
     "Implementation of some Deep Learning methods.  Includes multilayer perceptron,
different activation functions, regularisation strategies, stochastic gradient
descent and dropout.  Thanks go to the following references for helping to
inspire and develop the package: Ian Goodfellow, Yoshua Bengio, Aaron Courville,
Francis Bach (2016, ISBN:978-0262035613) Deep Learning.  Terrence J. Sejnowski
(2018, ISBN:978-0262038034) The Deep Learning Revolution.  Grant Sanderson
(3brown1blue)
<https://www.youtube.com/playlist?list=PLZHQ@code{ObOWTQDNU6R1_67000Dx_ZCJB-3pi>}
Neural Networks @code{YouTube} playlist.  Michael A. Nielsen
<http://neuralnetworksanddeeplearning.com/> Neural Networks and Deep Learning.")
    (license license:gpl3)))

(define-public r-deepnet
  (package
    (name "r-deepnet")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deepnet" version))
       (sha256
        (base32 "0gnf50007sj28daaz2r1rp8mvz1xpc2901bxl4yb1v4s4rcx6rhg"))))
    (properties `((upstream-name . "deepnet")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=deepnet")
    (synopsis "Deep Learning Toolkit in R")
    (description
     "Implement some deep learning architectures and neural network algorithms,
including BP,RBM,DBN,Deep autoencoder and so on.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-deepmou
  (package
    (name "r-deepmou")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deepMOU" version))
       (sha256
        (base32 "1r05wg01nighmhs2r8z91w091fz2r1ryb1j0mi96knqqdjgcbh4i"))))
    (properties `((upstream-name . "deepMOU")))
    (build-system r-build-system)
    (propagated-inputs (list r-skmeans
                             r-rfast
                             r-mass
                             r-ggplot2
                             r-extradistr
                             r-entropy
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=deepMOU")
    (synopsis
     "Clustering of Short Texts by Mixture of Unigrams and Its Deep Extensions")
    (description
     "This package provides functions providing an easy and intuitive way for fitting
and clusters data using the Mixture of Unigrams models by means the
Expectation-Maximization algorithm (Nigam, K. et al. (2000).
<doi:10.1023/A:1007692713085>), Mixture of Dirichlet-Multinomials estimated by
Gradient Descent (Anderlucci, Viroli (2020) <doi:10.1007/s11634-020-00399-3>)
and Deep Mixture of Multinomials whose estimates are obtained with Gibbs
sampling scheme (Viroli, Anderlucci (2020) <doi:10.1007/s11222-020-09989-9>).
There are also functions for graphical representation of clusters obtained.")
    (license license:gpl3)))

(define-public r-deeplr
  (package
    (name "r-deeplr")
    (version "2.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deeplr" version))
       (sha256
        (base32 "0xzhycw3yylq6hvaba3dv2wpmfaj9z6v6mzli8r4dbbzzaaa8214"))))
    (properties `((upstream-name . "deeplr")))
    (build-system r-build-system)
    (propagated-inputs (list r-utf8 r-tokenizers r-tibble r-purrr r-httr))
    (home-page "https://www.deepl.com/translator")
    (synopsis "Interface to the 'DeepL' Translation API")
    (description
     "This package provides a wrapper for the @code{DeepL} Pro API
<https://www.deepl.com/docs-api>, a web service for translating texts between
different languages.  A @code{DeepL} API developer account is required to use
the service (see <https://www.deepl.com/pro#developer>).")
    (license license:expat)))

(define-public r-deeplearningcausal
  (package
    (name "r-deeplearningcausal")
    (version "0.0.104")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DeepLearningCausal" version))
       (sha256
        (base32 "02n0prw6g0sslxwr3p5msbcqr2bny702pbf22vs6f0f9xc5gqkd6"))))
    (properties `((upstream-name . "DeepLearningCausal")))
    (build-system r-build-system)
    (propagated-inputs (list r-xgboost
                             r-weights
                             r-superlearner
                             r-rocr
                             r-randomforest
                             r-neuralnet
                             r-hmisc
                             r-glmnet
                             r-gbm
                             r-gam
                             r-e1071
                             r-class
                             r-caret))
    (home-page "https://github.com/hknd23/DeepLearningCausal")
    (synopsis "Causal Inference with Super Learner and Deep Neural Networks")
    (description
     "This package provides functions to estimate Conditional Average Treatment
Effects (CATE) and Population Average Treatment Effects on the Treated (PATT)
from experimental or observational data using the Super Learner (SL) ensemble
method and Deep neural networks.  The package first provides functions to
implement meta-learners such as the Single-learner (S-learner) and Two-learner
(T-learner) described in KÃ¼nzel et al. (2019) <doi:10.1073/pnas.1804597116> for
estimating the CATE. The S- and T-learner are each estimated using the SL
ensemble method and deep neural networks.  It then provides functions to
implement the Ottoboni and Poulos (2020) <doi:10.1515/jci-2018-0035> PATT-C
estimator to obtain the PATT from experimental data with noncompliance by using
the SL ensemble method and deep neural networks.")
    (license license:gpl3)))

(define-public r-deepgp
  (package
    (name "r-deepgp")
    (version "1.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deepgp" version))
       (sha256
        (base32 "1vdqsf0gn55j15dsfmbj76c5bb4799rkiwiq57n2rhl7sprvpdyr"))))
    (properties `((upstream-name . "deepgp")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo
                             r-rcpp
                             r-mvtnorm
                             r-matrix
                             r-gpgp
                             r-foreach
                             r-fnn
                             r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=deepgp")
    (synopsis "Bayesian Deep Gaussian Processes using MCMC")
    (description
     "This package performs Bayesian posterior inference for deep Gaussian processes
following Sauer, Gramacy, and Higdon (2023,
<doi:10.48550/@code{arXiv.2012.08015>}).  See Sauer (2023,
<http://hdl.handle.net/10919/114845>) for comprehensive methodological details
and <https://bitbucket.org/gramacylab/deepgp-ex/> for a variety of coding
examples.  Models are trained through MCMC including elliptical slice sampling
of latent Gaussian layers and Metropolis-Hastings sampling of kernel
hyperparameters.  Vecchia-approximation for faster computation is implemented
following Sauer, Cooper, and Gramacy (2023,
<doi:10.48550/@code{arXiv.2204.02904>}).  Optional monotonic warpings are
implemented following Barnett et al. (2024,
<doi:10.48550/@code{arXiv.2408.01540>}).  Downstream tasks include sequential
design through active learning Cohn/integrated mean squared error (ALC/IMSE;
Sauer, Gramacy, and Higdon, 2023), optimization through expected improvement
(EI; Gramacy, Sauer, and Wycoff, 2022 <doi:10.48550/@code{arXiv.2112.07457>}),
and contour location through entropy (Booth, Renganathan, and Gramacy, 2024
<doi:10.48550/@code{arXiv.2308.04420>}).  Models extend up to three layers deep;
a one layer model is equivalent to typical Gaussian process regression.
Incorporates @code{OpenMP} and SNOW parallelization and utilizes C/C++ under the
hood.")
    (license license:lgpl2.0+)))

(define-public r-deepgmm
  (package
    (name "r-deepgmm")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deepgmm" version))
       (sha256
        (base32 "0vwh8wgbva2a47b2yiiqjwq5qww2ckb4l66265sbp1lbis0g96li"))))
    (properties `((upstream-name . "deepgmm")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-mclust r-corpcor))
    (home-page "https://github.com/suren-rathnayake/deepgmm")
    (synopsis "Deep Gaussian Mixture Models")
    (description
     "Deep Gaussian mixture models as proposed by Viroli and @code{McLachlan} (2019)
<doi:10.1007/s11222-017-9793-z> provide a generalization of classical Gaussian
mixtures to multiple layers.  Each layer contains a set of latent variables that
follow a mixture of Gaussian distributions.  To avoid overparameterized
solutions, dimension reduction is applied at each layer by way of factor models.")
    (license license:gpl3+)))

(define-public r-deepdive
  (package
    (name "r-deepdive")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deepdive" version))
       (sha256
        (base32 "0q4jjq11bd52bx0vqjxsh0fz1b72pfy4gpj5p19z7p4czf4a46c6"))))
    (properties `((upstream-name . "deepdive")))
    (build-system r-build-system)
    (propagated-inputs (list r-treeclust
                             r-stringr
                             r-rpart
                             r-plyr
                             r-fastdummies
                             r-data-table))
    (home-page "https://rajeshb24.github.io/deepdive/")
    (synopsis "Deep Learning for General Purpose")
    (description
     "Aims to provide simple intuitive functions to create quick prototypes of
artificial neural network or deep learning models.  In addition novel ensemble
models like deeptree and deepforest has been included which combines decision
trees and neural network.")
    (license license:expat)))

(define-public r-deepdep
  (package
    (name "r-deepdep")
    (version "0.4.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deepdep" version))
       (sha256
        (base32 "1pz07zznlpqjkkpf5r1ik0shl7kj0vn4l5dmvs7ggc7k5n7ig3b2"))))
    (properties `((upstream-name . "deepdep")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr r-cranlogs))
    (native-inputs (list r-knitr))
    (home-page "https://dominikrafacz.github.io/deepdep/")
    (synopsis "Visualise and Explore the Deep Dependencies of R Packages")
    (description
     "This package provides tools for exploration of R package dependencies.  The main
deepdep() function allows to acquire deep dependencies of any package and plot
them in an elegant way.  It also adds some popularity measures for the packages
e.g. in the form of download count through the cranlogs package.  Uses the CRAN
metadata database <http://crandb.r-pkg.org> and Bioconductor metadata
<https://bioconductor.org>.  Other data acquire functions are:
get_dependencies(), get_downloads() and get_description().  The deepdep_shiny()
function runs shiny application that helps to produce a nice deepdep plot.")
    (license license:gpl3)))

(define-public r-deep
  (package
    (name "r-deep")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deep" version))
       (sha256
        (base32 "1764cnsax8jwp2pb6rnmlb0f5m99jss84yi9rp017hdm20izvzrq"))))
    (properties `((upstream-name . "deep")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=deep")
    (synopsis "Neural Networks Framework")
    (description
     "Explore neural networks in a layer oriented way, the framework is intended to
give the user total control of the internals of a net without much effort.  Use
classes like @code{PerceptronLayer} to create a layer of Percetron neurons, and
specify how many you want.  The package does all the tricky stuff internally
leaving you focused in what you want.  I wrote this package during a neural
networks course to help me with the problem set.")
    (license license:gpl3)))

(define-public r-dedupewider
  (package
    (name "r-dedupewider")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dedupewider" version))
       (sha256
        (base32 "18s8m0nzmx8ai4gcv5rv3rvmngw1q0pxj013v433xj76z2drqdaz"))))
    (properties `((upstream-name . "dedupewider")))
    (build-system r-build-system)
    (propagated-inputs (list r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/gsmolinski/dedupewider")
    (synopsis "Deduplication Across Multiple Columns")
    (description
     "Duplicated data can exist in different rows and columns and user may need to
treat observations (rows) connected by duplicated data as one observation, e.g.
companies can belong to one family (and thus: be one company) by sharing some
telephone numbers.  This package allows to find connected rows based on data on
chosen columns and collapse it into one row.")
    (license license:expat)))

(define-public r-deduped
  (package
    (name "r-deduped")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deduped" version))
       (sha256
        (base32 "0qb9g8fpb0ggkwhvp2l5y0lp0pgkfyxzcnmaq2ln9y2z1zgmh866"))))
    (properties `((upstream-name . "deduped")))
    (build-system r-build-system)
    (propagated-inputs (list r-fastmatch r-collapse))
    (home-page "https://github.com/orgadish/deduped")
    (synopsis "Making \"Deduplicated\" Functions")
    (description
     "This package contains one main function deduped() which speeds up slow,
vectorized functions by only performing computations on the unique values of the
input and expanding the results at the end.")
    (license license:expat)))

(define-public r-deductiver
  (package
    (name "r-deductiver")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DeductiveR" version))
       (sha256
        (base32 "0bx1ad2gw0pf03z0im31mzaa26jxwws6fkbcj319kd8b4s4wp92y"))))
    (properties `((upstream-name . "DeductiveR")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2 r-moments r-ggplot2 r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DeductiveR")
    (synopsis "Deductive Rational Method")
    (description
     "Apply the Deductive Rational Method to a monthly series of flow or precipitation
data to fill in missing data.  The method is as described in: Campos, D.F.,
(1984, ISBN:9686194444).")
    (license license:gpl3)))

(define-public r-deductive
  (package
    (name "r-deductive")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deductive" version))
       (sha256
        (base32 "11cn6wncd438g5ar5pjw6rw50060mksjf0xjcds92s97dz5m28a4"))))
    (properties `((upstream-name . "deductive")))
    (build-system r-build-system)
    (propagated-inputs (list r-validate r-stringdist r-lintools))
    (home-page "https://github.com/data-cleaning/deductive")
    (synopsis "Data Correction and Imputation Using Deductive Methods")
    (description
     "Attempt to repair inconsistencies and missing values in data records by using
information from valid values and validation rules restricting the data.")
    (license license:gpl3)))

(define-public r-deducorrect
  (package
    (name "r-deducorrect")
    (version "1.3.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deducorrect" version))
       (sha256
        (base32 "10lvhdnnc6xiy20hy6s5rpqcvilj8x0y6sn92rfjkdbfsl00sslp"))))
    (properties `((upstream-name . "deducorrect")))
    (build-system r-build-system)
    (propagated-inputs (list r-editrules))
    (home-page "https://github.com/data-cleaning/deducorrect")
    (synopsis
     "Deductive Correction, Deductive Imputation, and Deterministic Correction")
    (description
     "This package provides a collection of methods for automated data cleaning where
all actions are logged.")
    (license license:gpl3)))

(define-public r-deducer
  (package
    (name "r-deducer")
    (version "0.7-9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Deducer" version))
       (sha256
        (base32 "14kakyf28i654pndlswjzp6h3h7szpznrg6xznqg150mmn0bs3s6"))))
    (properties `((upstream-name . "Deducer")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (propagated-inputs (list r-scales
                             r-rjava
                             r-plyr
                             r-multcomp
                             r-mass
                             r-jgr
                             r-ggplot2
                             r-foreign
                             r-effects
                             r-e1071
                             r-car))
    (home-page "https://cran.r-project.org/package=Deducer")
    (synopsis "Data Analysis GUI for R")
    (description
     "An intuitive, cross-platform graphical data analysis system.  It uses menus and
dialogs to guide the user efficiently through the data manipulation and analysis
process, and has an excel like spreadsheet for easy data frame visualization and
editing.  Deducer works best when used with the Java based R GUI JGR, but the
dialogs can be called from the command line.  Dialogs have also been integrated
into the Windows Rgui.")
    (license license:gpl2)))

(define-public r-decp
  (package
    (name "r-decp")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "decp" version))
       (sha256
        (base32 "0mzpq8034yyhy9lika80mmwpixk120crgzj4kllypqhnvbcg1v4l"))))
    (properties `((upstream-name . "decp")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-purrr
                             r-matrixcalc
                             r-magrittr
                             r-ggplot2
                             r-geigen))
    (home-page "https://cran.r-project.org/package=decp")
    (synopsis "Complete Change Point Analysis")
    (description
     "This package provides a comprehensive approach for identifying and estimating
change points in multivariate time series through various statistical methods.
Implements the multiple change point detection methodology from Ryan & Killick
(2023) <doi:10.1080/00401706.2023.2183261> and a novel estimation methodology
from Fotopoulos et al. (2023) <doi:10.1007/s00362-023-01495-0> generalized to
fit the detection methodologies.  Performs both detection and estimation of
change points, providing visualization and summary information of the estimation
process for each detected change point.")
    (license license:gpl3)))

(define-public r-decorators
  (package
    (name "r-decorators")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "decorators" version))
       (sha256
        (base32 "1y47ggfsfrbsm8z78j5ibxbm4lhp90h3qwhyh4qw5dhsd6jspsbd"))))
    (properties `((upstream-name . "decorators")))
    (build-system r-build-system)
    (propagated-inputs (list r-purrr))
    (home-page "https://tidylab.github.io/decorators/")
    (synopsis
     "Extend the Behaviour of a Function without Explicitly Modifying it")
    (description
     "This package provides a decorator is a function that receives a function,
extends its behaviour, and returned the altered function.  Any caller that uses
the decorated function uses the same interface as it were the original,
undecorated function.  Decorators serve two primary uses: (1) Enhancing the
response of a function as it sends data to a second component; (2) Supporting
multiple optional behaviours.  An example of the first use is a timer decorator
that runs a function, outputs its execution time on the console, and returns the
original function's result.  An example of the second use is input type
validation decorator that during running time tests whether the caller has
passed input arguments of a particular class.  Decorators can reduce execution
time, say by memoization, or reduce bugs by adding defensive programming
routines.")
    (license license:expat)))

(define-public r-decorater
  (package
    (name "r-decorater")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DecorateR" version))
       (sha256
        (base32 "1za2qvdq96f75rmnm421xmq8s01ny4666ghv14i72iy3s4ml2hq9"))))
    (properties `((upstream-name . "DecorateR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rwekajars r-rweka r-rjava))
    (home-page "https://cran.r-project.org/package=DecorateR")
    (synopsis "Fit and Deploy DECORATE Trees")
    (description
     "DECORATE (Diverse Ensemble Creation by Oppositional Relabeling of Artificial
Training Examples) builds an ensemble of J48 trees by recursively adding
artificial samples of the training data (\"Melville, P., & Mooney, R. J. (2005)
<DOI:10.1016/j.inffus.2004.04.001>\").")
    (license license:gpl2+)))

(define-public r-decor
  (package
    (name "r-decor")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "decor" version))
       (sha256
        (base32 "1xki8vjn363v90x7a66apnzg43ngi7in9k678f62jls2h3rhqv1f"))))
    (properties `((upstream-name . "decor")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs r-tibble))
    (home-page "https://github.com/r-lib/decor")
    (synopsis "Retrieve Code Decorations")
    (description
     "Retrieves code comment decorations for C++ languages of the form \\\\ [[xyz]]',
which are used for automated wrapping of C++ functions.")
    (license license:expat)))

(define-public r-deconvolver
  (package
    (name "r-deconvolver")
    (version "1.2-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deconvolveR" version))
       (sha256
        (base32 "191bgncgwjhb13i27bf8072a0z3mkpjbbp06ys3nri0ggsv5r108"))))
    (properties `((upstream-name . "deconvolveR")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://bnaras.github.io/deconvolveR/")
    (synopsis "Empirical Bayes Estimation Strategies")
    (description
     "Empirical Bayes methods for learning prior distributions from data.  An unknown
prior distribution (g) has yielded (unobservable) parameters, each of which
produces a data point from a parametric exponential family (f).  The goal is to
estimate the unknown prior (\"g-modeling\") by deconvolution and Empirical Bayes
methods.  Details and examples are in the paper by Narasimhan and Efron (2020,
<doi:10.18637/jss.v094.i11>).")
    (license license:gpl2+)))

(define-public r-decompr
  (package
    (name "r-decompr")
    (version "6.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "decompr" version))
       (sha256
        (base32 "0bsin2hlb8sacmkzsv4b2fqdh5b55b67lkm41icacqnvxrisnxqp"))))
    (properties `((upstream-name . "decompr")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrixstats))
    (native-inputs (list r-knitr))
    (home-page "https://qua.st/decompr/")
    (synopsis "Global Value Chain Decomposition")
    (description
     "Three global value chain (GVC) decompositions are implemented.  The Leontief
decomposition derives the value added origin of exports by country and industry
as in Hummels, Ishii and Yi (2001).  The Koopman, Wang and Wei (2014)
decomposition splits country-level exports into 9 value added components, and
the Wang, Wei and Zhu (2013) decomposition splits bilateral exports into 16
value added components.  Various GVC indicators based on these decompositions
are computed in the complimentary gvc package. --- References: --- Hummels, D.,
Ishii, J., & Yi, K. M. (2001).  The nature and growth of vertical specialization
in world trade.  Journal of international Economics, 54(1), 75-96.  Koopman, R.,
Wang, Z., & Wei, S. J. (2014).  Tracing value-added and double counting in gross
exports.  American Economic Review, 104(2), 459-94.  Wang, Z., Wei, S. J., &
Zhu, K. (2013).  Quantifying international production sharing at the bilateral
and sector levels (No.  w19677).  National Bureau of Economic Research.")
    (license license:gpl3)))

(define-public r-decomposer
  (package
    (name "r-decomposer")
    (version "1.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DecomposeR" version))
       (sha256
        (base32 "0f5bagmn0s15qhw0c7fiv96r2ih365fak1rz3pxfnaqmm20l2j8i"))))
    (properties `((upstream-name . "DecomposeR")))
    (build-system r-build-system)
    (propagated-inputs (list r-usethis
                             r-tictoc
                             r-stratigrapher
                             r-hexbin
                             r-dplyr
                             r-colorramps))
    (home-page "https://cran.r-project.org/package=DecomposeR")
    (synopsis "Empirical Mode Decomposition for Cyclostratigraphy")
    (description
     "This package provides tools to apply Ensemble Empirical Mode Decomposition
(EEMD) for cyclostratigraphy purposes.  Mainly: a new algorithm, extricate, that
performs EEMD in seconds, a linear interpolation algorithm using the greatest
rational common divisor of depth or time, different algorithms to compute
instantaneous amplitude, frequency and ratios of frequencies, and functions to
verify and visualise the outputs.  The functions were developed during the CRASH
project (Checking the Reproducibility of Astrochronology in the Hauterivian).
When using for publication please cite Wouters, S., Crucifix, M., Sinnesael, M.,
Da Silva, A.C., Zeeden, C., Zivanovic, M., Boulvain, F., Devleeschouwer, X.,
2022, \"A decomposition approach to cyclostratigraphic signal processing\".
Earth-Science Reviews 225 (103894). <doi:10.1016/j.earscirev.2021.103894>.")
    (license license:gpl3)))

(define-public r-decomposedpsf
  (package
    (name "r-decomposedpsf")
    (version "0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "decomposedPSF" version))
       (sha256
        (base32 "12sb4zzvc29hvhlay97g84pn4saqyp16wckjrdgg4qqpc0rzrfz5"))))
    (properties `((upstream-name . "decomposedPSF")))
    (build-system r-build-system)
    (propagated-inputs (list r-tseries r-rlibeemd r-psf r-forecast))
    (native-inputs (list r-knitr))
    (home-page "https://www.neerajbokde.in/software/")
    (synopsis
     "Time Series Prediction with PSF and Decomposition Methods (EMD and EEMD)")
    (description
     "Predict future values with hybrid combinations of Pattern Sequence based
Forecasting (PSF), Autoregressive Integrated Moving Average (ARIMA), Empirical
Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD)
methods based hybrid methods.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-decompdl
  (package
    (name "r-decompdl")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "decompDL" version))
       (sha256
        (base32 "11xbxv2j8m1w4lz933jvwy20wsazqiffnn0awgv7fz6q3ma5cqkh"))))
    (properties `((upstream-name . "decompDL")))
    (build-system r-build-system)
    (propagated-inputs (list r-vmdecomp
                             r-tsutils
                             r-tsdeeplearning
                             r-tensorflow
                             r-rlibeemd
                             r-reticulate
                             r-magrittr
                             r-keras
                             r-biocgenerics))
    (home-page "https://cran.r-project.org/package=decompDL")
    (synopsis
     "Decomposition Based Deep Learning Models for Time Series Forecasting")
    (description
     "Hybrid model is the most promising forecasting method by combining decomposition
and deep learning techniques to improve the accuracy of time series forecasting.
 Each decomposition technique decomposes a time series into a set of intrinsic
mode functions (IMFs), and the obtained IMFs are modelled and forecasted
separately using the deep learning models.  Finally, the forecasts of all IMFs
are combined to provide an ensemble output for the time series.  The prediction
ability of the developed models are calculated using international monthly price
series of maize in terms of evaluation criteria like root mean squared error,
mean absolute percentage error and, mean absolute error.  For method details see
Choudhary, K. et al. (2023).
<https://ssca.org.in/media/14_SA44052022_R3_SA_21032023_Girish_Jha_FINAL_Finally.pdf>.")
    (license license:gpl3)))

(define-public r-decoder
  (package
    (name "r-decoder")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "decoder" version))
       (sha256
        (base32 "1jxgd32bn36ldal26wivhdxgjy247l7r4ickacr1p8rrwxvhpk18"))))
    (properties `((upstream-name . "decoder")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://www.bitbucket.com/cancercentrum/decoder")
    (synopsis "Decode Coded Variables to Plain Text and the Other Way Around")
    (description
     "Main function \"decode\" is used to decode coded key values to plain text.
Function \"code\" can be used to code plain text to code if there is a 1:1
relation between the two.  The concept relies on keyvalue objects used for
translation.  There are several keyvalue objects included in the areas of
geographical regional codes, administrative health care unit codes, diagnosis
codes and more.  It is also easy to extend the use by arbitrary code sets.")
    (license license:gpl2)))

(define-public r-decode
  (package
    (name "r-decode")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "decode" version))
       (sha256
        (base32 "1qp0765gl3pgfdzjwj7icf3zminxxmrlw6gx3vj51y6c2y5ws4as"))))
    (properties `((upstream-name . "decode")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=decode")
    (synopsis
     "Differential Co-Expression and Differential Expression Analysis")
    (description
     "Integrated differential expression (DE) and differential co-expression (DC)
analysis on gene expression data based on DECODE (@code{DifferEntial}
CO-expression and Differential Expression) algorithm.")
    (license license:gpl3)))

(define-public r-declaredesign
  (package
    (name "r-declaredesign")
    (version "1.0.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DeclareDesign" version))
       (sha256
        (base32 "0f1c1zkg4cd980b6fgh7dy4vfmwnacy3r98cwmwz99fkg7gcjvnl"))))
    (properties `((upstream-name . "DeclareDesign")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-randomizr r-generics r-fabricatr
                             r-estimatr))
    (home-page "https://declaredesign.org/r/declaredesign/")
    (synopsis "Declare and Diagnose Research Designs")
    (description
     "Researchers can characterize and learn about the properties of research designs
before implementation using `@code{DeclareDesign`}.  Ex ante declaration and
diagnosis of designs can help researchers clarify the strengths and limitations
of their designs and to improve their properties, and can help readers evaluate
a research strategy prior to implementation and without access to results.  It
can also make it easier for designs to be shared, replicated, and critiqued.")
    (license license:expat)))

(define-public r-declared
  (package
    (name "r-declared")
    (version "0.25")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "declared" version))
       (sha256
        (base32 "0qdzrmmn2p5wb502syk05hj3jn3wbqhjhs7ya08r5gp1fapsalq4"))))
    (properties `((upstream-name . "declared")))
    (build-system r-build-system)
    (home-page "https://github.com/dusadrian/declared")
    (synopsis "Functions for Declared Missing Values")
    (description
     "This package provides a zero dependency package containing functions to declare
labels and missing values, coupled with associated functions to create
(weighted) tables of frequencies and various other summary measures.  Some of
the base functions have been rewritten to make use of the specific information
about the missing values, most importantly to distinguish between empty NA and
declared NA values.  Some functions have similar functionality with the
corresponding ones from packages \"haven\" and \"labelled\".  The aim is to ensure
as much compatibility as possible with these packages, while offering an
alternative in the objects of class \"declared\".")
    (license license:gpl3+)))

(define-public r-deckgl
  (package
    (name "r-deckgl")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deckgl" version))
       (sha256
        (base32 "0cjvmdiqknrq8mlqxmhkhcib40asdyl2bpllx8v1jz3h1d62zs04"))))
    (properties `((upstream-name . "deckgl")))
    (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-yaml
                             r-tibble
                             r-readr
                             r-magrittr
                             r-jsonlite
                             r-htmlwidgets
                             r-htmltools
                             r-base64enc))
    (native-inputs (list r-knitr esbuild))
    (home-page "https://github.com/crazycapivara/deckgl/")
    (synopsis "An R Interface to 'deck.gl'")
    (description
     "Makes deck.gl <https://deck.gl/>, a @code{WebGL-powered} open-source
@code{JavaScript} framework for visual exploratory data analysis of large
datasets, available within R via the htmlwidgets package.  Furthermore, it
supports basemaps from mapbox <https://www.mapbox.com/> via mapbox-gl-js
<https://github.com/mapbox/mapbox-gl-js>.")
    (license license:expat)))

(define-public r-decisionsupport
  (package
    (name "r-decisionsupport")
    (version "1.114")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "decisionSupport" version))
       (sha256
        (base32 "1vd18v0wi56qd8anhwvvwab98lgh3aj785f6c6nd41ifwp2phzm3"))))
    (properties `((upstream-name . "decisionSupport")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-stringr
                             r-rriskdistributions
                             r-patchwork
                             r-nleqslv
                             r-mvtnorm
                             r-msm
                             r-magrittr
                             r-ggplot2
                             r-fancova
                             r-dplyr
                             r-class
                             r-chillr
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "http://www.worldagroforestry.org/")
    (synopsis "Quantitative Support of Decision Making under Uncertainty")
    (description
     "Supporting the quantitative analysis of binary welfare based decision making
processes using Monte Carlo simulations.  Decision support is given on two
levels: (i) The actual decision level is to choose between two alternatives
under probabilistic uncertainty.  This package calculates the optimal decision
based on maximizing expected welfare. (ii) The meta decision level is to
allocate resources to reduce the uncertainty in the underlying decision problem,
i.e to increase the current information to improve the actual decision making
process.  This problem is dealt with using the Value of Information Analysis.
The Expected Value of Information for arbitrary prospective estimates can be
calculated as well as Individual Expected Value of Perfect Information.  The
probabilistic calculations are done via Monte Carlo simulations.  This Monte
Carlo functionality can be used on its own.")
    (license license:gpl3)))

(define-public r-decision
  (package
    (name "r-decision")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "decision" version))
       (sha256
        (base32 "13d0yyg5zp7n3r92l0l1dsffxfph6vacrlzga9rz41l5pja72z6g"))))
    (properties `((upstream-name . "decision")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=decision")
    (synopsis "Statistical Decision Analysis")
    (description
     "This package contains a function called dmur() which accepts four parameters
like possible values, probabilities of the values, selling cost and preparation
cost.  The dmur() function generates various numeric decision parameters like
MEMV (Maximum (optimum) expected monitory value), best choice, EPPI (Expected
profit with perfect information), EVPI (Expected value of the perfect
information), EOL (Expected opportunity loss), which facilitate effective
decision-making.")
    (license license:gpl2+)))

(define-public r-decido
  (package
    (name "r-decido")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "decido" version))
       (sha256
        (base32 "14y3z5ys5y3kffgm0dk92rx4vd1mi9jvxn7pqvwi4jhyx7wx06pw"))))
    (properties `((upstream-name . "decido")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://hypertidy.github.io/decido")
    (synopsis "Bindings for 'Mapbox' Ear Cutting Triangulation Library")
    (description
     "This package provides constrained triangulation of polygons.  Ear cutting (or
ear clipping) applies constrained triangulation by successively cutting
triangles from a polygon defined by path/s.  Holes are supported by introducing
a bridge segment between polygon paths.  This package wraps the header-only
library earcut.hpp <https://github.com/mapbox/earcut.hpp.git> which includes a
reference to the method used by Held, M. (2001) <doi:10.1007/s00453-001-0028-4>.")
    (license license:expat)))

(define-public r-decide
  (package
    (name "r-decide")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DECIDE" version))
       (sha256
        (base32 "04hqr3r2ys6xni3a2mr2j45415wm3iix38xfxccrnx2wjk5w3b5b"))))
    (properties `((upstream-name . "DECIDE")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DECIDE")
    (synopsis "DEComposition of Indirect and Direct Effects")
    (description
     "Calculates various estimates for measures of educational differentials, the
relative importance of primary and secondary effects in the creation of such
differentials and compares the estimates obtained from two datasets.")
    (license license:gpl2+)))

(define-public r-decafs
  (package
    (name "r-decafs")
    (version "3.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DeCAFS" version))
       (sha256
        (base32 "0dj32rck6ssyv82d8b75qgsqw319q02iqd3xxazy6251wcjn321i"))))
    (properties `((upstream-name . "DeCAFS")))
    (build-system r-build-system)
    (propagated-inputs (list r-robustbase r-rcpp r-ggplot2))
    (home-page "https://cran.r-project.org/package=DeCAFS")
    (synopsis "Detecting Changes in Autocorrelated and Fluctuating Signals")
    (description
     "Detect abrupt changes in time series with local fluctuations as a random walk
process and autocorrelated noise as an AR(1) process.  See Romano, G., Rigaill,
G., Runge, V., Fearnhead, P. (2021) <doi:10.1080/01621459.2021.1909598>.")
    (license license:gpl2+)))

(define-public r-debugr
  (package
    (name "r-debugr")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "debugr" version))
       (sha256
        (base32 "0lfq0s0hibd00558vl3dmvrkzxjc7q62xr8sqzai0pv9a9lhixcn"))))
    (properties `((upstream-name . "debugr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rstudioapi r-rprojroot))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jsugarelli/debugr/")
    (synopsis
     "Debug Tool to Watch Objects/Expressions While Running an R Script")
    (description
     "Tool to print out the value of R objects/expressions while running an R script.
Outputs can be made dependent on user-defined conditions/criteria.  Debug
messages only appear when a global option for debugging is set.  This way,
debugr code can even remain in the debugged code for later use without any
negative effects during normal runtime.")
    (license license:gpl3)))

(define-public r-deboinr
  (package
    (name "r-deboinr")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DeBoinR" version))
       (sha256
        (base32 "0brwk24q2wgmn38y1w1rish8dfdbv10xdzmm2k1drdwgsn72hxis"))))
    (properties `((upstream-name . "DeBoinR")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma r-kernsmooth r-gridextra r-ggplot2
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=DeBoinR")
    (synopsis
     "Box-Plots and Outlier Detection for Probability Density Functions")
    (description
     "Orders a data-set consisting of an ensemble of probability density functions on
the same x-grid.  Visualizes a box-plot of these functions based on the notion
of distance determined by the user.  Reports outliers based on the distance
chosen and the scaling factor for an interquartile range rule.  For further
details, see: Alexander C. Murph et al. (2023). \"Visualization and Outlier
Detection for Probability Density Function Ensembles.\"
<https://sirmurphalot.github.io/publications>.")
    (license license:expat)))

(define-public r-debkeepr
  (package
    (name "r-debkeepr")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "debkeepr" version))
       (sha256
        (base32 "1w38qz0qs26ba1c89z1c40n4rwif989gh7was7wwazr2s61wjaha"))))
    (properties `((upstream-name . "debkeepr")))
    (build-system r-build-system)
    (propagated-inputs (list r-zeallot
                             r-vctrs
                             r-tibble
                             r-rlang
                             r-magrittr
                             r-dplyr
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jessesadler/debkeepr")
    (synopsis
     "Analysis of Non-Decimal Currencies and Double-Entry Bookkeeping")
    (description
     "Analysis of historical non-decimal currencies and value systems that use
tripartite or tetrapartite systems such as pounds, shillings, and pence.  It
introduces new vector classes to represent non-decimal currencies, making them
compatible with numeric classes, and provides functions to work with these
classes in data frames in the context of double-entry bookkeeping.")
    (license license:expat)))

(define-public r-debinfer
  (package
    (name "r-debinfer")
    (version "0.4.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deBInfer" version))
       (sha256
        (base32 "1l4wim82n5q51c1f7193d3i22qrn9kfcsddyrn8izhlwsjb9q3kp"))))
    (properties `((upstream-name . "deBInfer")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncdist
                             r-rcolorbrewer
                             r-plyr
                             r-pbsddesolve
                             r-mvtnorm
                             r-mass
                             r-desolve
                             r-coda))
    (native-inputs (list r-r-rsp r-knitr))
    (home-page "https://github.com/pboesu/debinfer")
    (synopsis "Bayesian Inference for Differential Equations")
    (description
     "This package provides a Bayesian framework for parameter inference in
differential equations.  This approach offers a rigorous methodology for
parameter inference as well as modeling the link between unobservable model
states and parameters, and observable quantities.  Provides templates for the DE
model, the observation model and data likelihood, and the model parameters and
their prior distributions.  A Markov chain Monte Carlo (MCMC) procedure
processes these inputs to estimate the posterior distributions of the parameters
and any derived quantities, including the model trajectories.  Further
functionality is provided to facilitate MCMC diagnostics and the visualisation
of the posterior distributions of model parameters and trajectories.")
    (license license:gpl3)))

(define-public r-debif
  (package
    (name "r-debif")
    (version "0.1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deBif" version))
       (sha256
        (base32 "0zy9pn6994bpbfjk4w52qvfckcilq5nz1v21bqc63grkz0lmlgzy"))))
    (properties `((upstream-name . "deBif")))
    (build-system r-build-system)
    (propagated-inputs (list r-shinyjs
                             r-shinydashboardplus
                             r-shinydashboard
                             r-shiny
                             r-rstudioapi
                             r-rootsolve
                             r-desolve))
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=deBif")
    (synopsis "Bifurcation Analysis of Ordinary Differential Equation Systems")
    (description
     "Shiny application that performs bifurcation and phaseplane analysis of systems
of ordinary differential equations.  The package allows for computation of
equilibrium curves as a function of a single free parameter, detection of
transcritical, saddle-node and hopf bifurcation points along these curves, and
computation of curves representing these transcritical, saddle-node and hopf
bifurcation points as a function of two free parameters.  The shiny-based GUI
allows visualization of the results in both 2D- and 3D-plots.  The implemented
methods for solution localisation and curve continuation are based on the book
\"Elements of applied bifurcation theory\" (Kuznetsov, Y. A., 1995; ISBN:
0-387-94418-4).")
    (license license:gpl3)))

(define-public r-debiasinfer
  (package
    (name "r-debiasinfer")
    (version "0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DebiasInfer" version))
       (sha256
        (base32 "02r1pc5s1vwnvz6cxb2gkc3x4x9vw8nb2zw1z8hyyxp5n8n8d2mf"))))
    (properties `((upstream-name . "DebiasInfer")))
    (build-system r-build-system)
    (propagated-inputs (list r-cvxr r-caret))
    (home-page "https://github.com/zhangyk8/Debias-Infer/")
    (synopsis
     "Efficient Inference on High-Dimensional Linear Model with Missing Outcomes")
    (description
     "This package provides a statistically and computationally efficient debiasing
method for conducting valid inference on the high-dimensional linear regression
function with missing outcomes.  The reference paper is Zhang, Giessing, and
Chen (2023) <@code{arXiv:2309.06429>}.")
    (license license:expat)))

(define-public r-debest
  (package
    (name "r-debest")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "debest" version))
       (sha256
        (base32 "1kbz17q8xg8nbak0y4f6g9pj20q02a00ijvk1xmbsbgl4xmww0ip"))))
    (properties `((upstream-name . "debest")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-flexsurv))
    (home-page "https://cran.r-project.org/package=debest")
    (synopsis
     "Duration Estimation for Biomarker Enrichment Studies and Trials")
    (description
     "This package provides a general framework using mixture Weibull distributions to
accurately predict biomarker-guided trial duration accounting for heterogeneous
population.  Extensive simulations are performed to evaluate the impact of
heterogeneous population and the dynamics of biomarker characteristics and
disease on the study duration.  Several influential parameters including median
survival time, enrollment rate, biomarker prevalence and effect size are
identified.  Efficiency gains of biomarker-guided trials can be quantitatively
compared to the traditional all-comers design.  For reference, see Zhang et al.
(2024) <@code{arXiv:2401.00540>}.")
    (license license:gpl2)))

(define-public r-debbi
  (package
    (name "r-debbi")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DEBBI" version))
       (sha256
        (base32 "09bsq5m33yj3ik3irj2ifjkylg259imrz499qp5j4ggcqgvk6v88"))))
    (properties `((upstream-name . "DEBBI")))
    (build-system r-build-system)
    (propagated-inputs (list r-randtoolbox r-numderiv r-doparallel))
    (home-page "https://github.com/bmgaldo/DEBBI")
    (synopsis "Differential Evolution-Based Bayesian Inference")
    (description
     "Bayesian inference algorithms based on the population-based \"differential
evolution\" (DE) algorithm.  Users can obtain posterior mode (MAP) estimates via
DEMAP, posterior samples via DEMCMC, and variational approximations via DEVI.")
    (license license:expat)))

(define-public r-debar
  (package
    (name "r-debar")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "debar" version))
       (sha256
        (base32 "0zx3rp0pnxbn57l6yafwzd66kvv6mfpr0alsp8mxhl2jl7c5f721"))))
    (properties `((upstream-name . "debar")))
    (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=debar")
    (synopsis "Post-Clustering Denoiser for COI-5P Barcode Data")
    (description
     "The debar sequence processing pipeline is designed for denoising high throughput
sequencing data for the animal DNA barcode marker cytochrome c oxidase I (COI).
The package is designed to detect and correct insertion and deletion errors
within sequencer outputs.  This is accomplished through comparison of input
sequences against a profile hidden Markov model (PHMM) using the Viterbi
algorithm (for algorithm details see Durbin et al.  1998, ISBN: 9780521629713).
Inserted base pairs are removed and deleted base pairs are accounted for through
the introduction of a placeholder character.  Since the PHMM is a probabilistic
representation of the COI barcode, corrections are not always perfect.  For this
reason debar censors base pairs adjacent to reported indel sites, turning them
into placeholder characters (default is 7 base pairs in either direction, this
feature can be disabled).  Testing has shown that this censorship results in the
correct sequence length being restored, and erroneous base pairs being masked
the vast majority of the time (>95%).")
    (license license:gpl3)))

(define-public r-dear
  (package
    (name "r-dear")
    (version "1.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deaR" version))
       (sha256
        (base32 "0rc12pr4br8kca90xcy5f8w1fyjzn6s7kyc3q3m3caxq8dlidn5v"))))
    (properties `((upstream-name . "deaR")))
    (build-system r-build-system)
    (propagated-inputs (list r-writexl
                             r-tidyr
                             r-plotly
                             r-lpsolve
                             r-igraph
                             r-gridextra
                             r-ggplot2
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=deaR")
    (synopsis "Conventional and Fuzzy Data Envelopment Analysis")
    (description
     "Set of functions for Data Envelopment Analysis.  It runs both classic and fuzzy
DEA models.  See: Banker, R.; Charnes, A.; Cooper, W.W. (1984).
<doi:10.1287/mnsc.30.9.1078>, Charnes, A.; Cooper, W.W.; Rhodes, E. (1978).
<doi:10.1016/0377-2217(78)90138-8> and Charnes, A.; Cooper, W.W.; Rhodes, E.
(1981). <doi:10.1287/mnsc.27.6.668>.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-deal
  (package
    (name "r-deal")
    (version "1.2-42")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deal" version))
       (sha256
        (base32 "0d516gvhqw6nfv9ijda9j04nlcjgdnnlgcf5774n8fgwjhm4azx1"))))
    (properties `((upstream-name . "deal")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=deal")
    (synopsis "Learning Bayesian Networks with Mixed Variables")
    (description
     "Bayesian networks with continuous and/or discrete variables can be learned and
compared from data.  The method is described in Boettcher and Dethlefsen (2003),
<doi:10.18637/jss.v008.i20>.")
    (license license:gpl2+)))

(define-public r-deadband
  (package
    (name "r-deadband")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "deadband" version))
       (sha256
        (base32 "02pq3d0l0wy8bdlyfir3zf46j1ascx4qajyq5cf28yl62q6ngq5d"))))
    (properties `((upstream-name . "deadband")))
    (build-system r-build-system)
    (propagated-inputs (list r-ttr))
    (home-page "https://cran.r-project.org/package=deadband")
    (synopsis "Statistical Deadband Algorithms Comparison")
    (description
     "Statistical deadband algorithms are based on the Send-On-Delta concept as in
Miskowicz(2006,<doi:10.3390/s6010049>).  A collection of functions compare
effectiveness and fidelity of sampled signals using statistical deadband
algorithms.")
    (license license:gpl2)))

(define-public r-ddtlcm
  (package
    (name "r-ddtlcm")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ddtlcm" version))
       (sha256
        (base32 "1xjpw5qx2wjq8y4ayg1d3scclsrn2bkmjk9gkff57gq2n0qlwnh0"))))
    (properties `((upstream-name . "ddtlcm")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncnorm
                             r-testthat
                             r-rdpack
                             r-r-utils
                             r-polca
                             r-phylobase
                             r-matrixstats
                             r-matrix
                             r-label-switching
                             r-ggtree
                             r-ggtext
                             r-ggpubr
                             r-ggplot2
                             r-extradistr
                             r-data-table
                             r-bayeslogit
                             r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/limengbinggz/ddtlcm")
    (synopsis
     "Latent Class Analysis with Dirichlet Diffusion Tree Process Prior")
    (description
     "This package implements a Bayesian algorithm for overcoming weak separation in
Bayesian latent class analysis.  Reference: Li et al. (2023)
<@code{arXiv:2306.04700>}.")
    (license license:expat)))

(define-public r-ddst
  (package
    (name "r-ddst")
    (version "1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ddst" version))
       (sha256
        (base32 "1y0immm337adkd2bjx8c5pf02w9wysv3gj26f4qf0jiba0f2wk8n"))))
    (properties `((upstream-name . "ddst")))
    (build-system r-build-system)
    (propagated-inputs (list r-orthopolynom r-evd))
    (home-page "https://cran.r-project.org/package=ddst")
    (synopsis "Data Driven Smooth Tests")
    (description
     "Smooth testing of goodness of fit.  These tests are data driven (alternative
hypothesis is dynamically selected based on data).  In this package you will
find various tests for exponent, Gaussian, Gumbel and uniform distribution.")
    (license license:gpl2)))

(define-public r-ddspls
  (package
    (name "r-ddspls")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ddsPLS" version))
       (sha256
        (base32 "0l5dcpqs57bp6b6b718annnhilkv6n4imynylg0wimik27ipmfwl"))))
    (properties `((upstream-name . "ddsPLS")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny
                             r-rcppeigen
                             r-rcpp
                             r-rcolorbrewer
                             r-foreach
                             r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ddsPLS")
    (synopsis "Data-Driven Sparse Partial Least Squares")
    (description
     "This package provides a sparse Partial Least Squares implementation which uses
soft-threshold estimation of the covariance matrices and therein introduces
sparsity.  Number of components and regularization coefficients are
automatically set.")
    (license license:expat)))

(define-public r-ddpna
  (package
    (name "r-ddpna")
    (version "0.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DDPNA" version))
       (sha256
        (base32 "10asskc757c2xmp2xc4v6gzp43jj4db93xjdq8hqqfvr0vyvmffy"))))
    (properties `((upstream-name . "DDPNA")))
    (build-system r-build-system)
    (propagated-inputs (list r-venndiagram
                             r-scales
                             r-plyr
                             r-megena
                             r-igraph
                             r-hmisc
                             r-ggplot2
                             r-ggalt))
    (home-page "https://github.com/liukf10/DDPNA")
    (synopsis
     "Disease-Drived Differential Proteins Co-Expression Network Analysis")
    (description
     "This package provides functions designed to connect disease-related differential
proteins and co-expression network.  It provides the basic statics analysis
included t test, ANOVA analysis.  The network construction is not offered by the
package, you can used WGCNA package which you can learn in Peter et al. (2008)
<doi:10.1186/1471-2105-9-559>.  It also provides module analysis included PCA
analysis, two enrichment analysis, Planner maximally filtered graph extraction
and hub analysis.")
    (license license:gpl2)))

(define-public r-ddpm
  (package
    (name "r-ddpm")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DDPM" version))
       (sha256
        (base32 "04fkbaw297i76gj6n0avqchjxh32q4vlrxad8sn9wfzpq86j8ln2"))))
    (properties `((upstream-name . "DDPM")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DDPM")
    (synopsis "Data Sets for Discrete Probability Models")
    (description
     "This package provides a wide collection of univariate discrete data sets from
various applied domains related to distribution theory.  The functions allow
quick, easy, and efficient access to 100 univariate discrete data sets.  The
data are related to different applied domains, including medical, reliability
analysis, engineering, manufacturing, occupational safety, geological sciences,
terrorism, psychology, agriculture, environmental sciences, road traffic
accidents, demography, actuarial science, law, and justice.  The documentation,
along with associated references for further details and uses, is presented.")
    (license license:gpl2+)))

(define-public r-ddplot
  (package
    (name "r-ddplot")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ddplot" version))
       (sha256
        (base32 "03zcnc6is4qdpz3krhhz820j0an6dr7562bnmzj787xf5parwq6r"))))
    (properties `((upstream-name . "ddplot")))
    (build-system r-build-system)
    (propagated-inputs (list r-r2d3))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/feddelegrand7/ddplot")
    (synopsis "Create D3 Based SVG Graphics")
    (description
     "Create D3 based SVG ('Scalable Vector Graphics') graphics using a simple R API.
The package aims to simplify the creation of many SVG plot types using a
straightforward R API. The package relies on the r2d3 R package and the D3
@code{JavaScript} library.  See <https://rstudio.github.io/r2d3/> and
<https://d3js.org/> respectively.")
    (license license:gpl3+)))

(define-public r-ddpcr
  (package
    (name "r-ddpcr")
    (version "1.15.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ddpcr" version))
       (sha256
        (base32 "1as25yc23n6jj87nccp7g2jrpvz6yxa7f6ba65g6ynvkzk57531b"))))
    (properties `((upstream-name . "ddpcr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-shinyjs
                             r-shinydisconnect
                             r-shiny
                             r-readr
                             r-plyr
                             r-mixtools
                             r-magrittr
                             r-lazyeval
                             r-ggplot2
                             r-dt
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/daattali/ddpcr")
    (synopsis
     "Analysis and Visualization of Droplet Digital PCR in R and on the Web")
    (description
     "An interface to explore, analyze, and visualize droplet digital PCR
(@code{ddPCR}) data in R. This is the first non-proprietary software for
analyzing two-channel @code{ddPCR} data.  An interactive tool was also created
and is available online to facilitate this analysis for anyone who is not
comfortable with using R.")
    (license license:expat)))

(define-public r-ddpca
  (package
    (name "r-ddpca")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ddpca" version))
       (sha256
        (base32 "1qsanid7sr2nc9pwzyz4cbjc1vg0rj255d3rnh1rb22agrgj2bc1"))))
    (properties `((upstream-name . "ddpca")))
    (build-system r-build-system)
    (propagated-inputs (list r-rspectra r-quantreg r-matrix r-mass))
    (home-page "https://cran.r-project.org/package=ddpca")
    (synopsis "Diagonally Dominant Principal Component Analysis")
    (description
     "Efficient procedures for fitting the DD-PCA (Ke et al., 2019,
<@code{arXiv:1906.00051>}) by decomposing a large covariance matrix into a
low-rank matrix plus a diagonally dominant matrix.  The implementation of DD-PCA
includes the convex approach using the Alternating Direction Method of
Multipliers (ADMM) and the non-convex approach using the iterative projection
algorithm.  Applications of DD-PCA to large covariance matrix estimation and
global multiple testing are also included in this package.")
    (license license:gpl2)))

(define-public r-ddp
  (package
    (name "r-ddp")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ddp" version))
       (sha256
        (base32 "03gszqzh73zq04hqa2zgxn4fkiyr1fbhx3byxsdfzmmji46f8qip"))))
    (properties `((upstream-name . "ddp")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ddp")
    (synopsis "Desirable Dietary Pattern")
    (description
     "The desirable Dietary Pattern (DDP)/ PPH score measures the variety of food
consumption.  The (weighted) score is calculated based on the type of food.
This package is intended to calculate the DDP/ PPH score that is faster than
traditional method via a manual calculation by BKP (2017)
<http://bkp.pertanian.go.id/storage/app/uploads/public/5bf/ca9/06b/5bfca906bc654274163456.pdf>
and is simpler than the nutrition survey <http://www.nutrisurvey.de>.  The
database to create weights and baseline values is the Indonesia national survey
in 2017.")
    (license license:gpl3)))

(define-public r-ddoutlier
  (package
    (name "r-ddoutlier")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DDoutlier" version))
       (sha256
        (base32 "1az5zq0l3kj959572mlpc4zl73f16iag0yrs217fa9m8xpd3c2sd"))))
    (properties `((upstream-name . "DDoutlier")))
    (build-system r-build-system)
    (propagated-inputs (list r-proxy r-pracma r-dbscan))
    (home-page "https://github.com/jhmadsen/DDoutlier")
    (synopsis "Distance & Density-Based Outlier Detection")
    (description
     "Outlier detection in multidimensional domains.  Implementation of notable
distance and density-based outlier algorithms.  Allows users to identify local
outliers by comparing observations to their nearest neighbors, reverse nearest
neighbors, shared neighbors or natural neighbors.  For distance-based
approaches, see Knorr, M., & Ng, R. T. (1997) <doi:10.1145/782010.782021>,
Angiulli, F., & Pizzuti, C. (2002) <doi:10.1007/3-540-45681-3_2>, Hautamaki, V.,
& Ismo, K. (2004) <doi:10.1109/ICPR.2004.1334558> and Zhang, K., Hutter, M. &
Jin, H. (2009) <doi:10.1007/978-3-642-01307-2_84>.  For density-based
approaches, see Tang, J., Chen, Z., Fu, A. W. C., & Cheung, D. W. (2002)
<doi:10.1007/3-540-47887-6_53>, Jin, W., Tung, A. K. H., Han, J., & Wang, W.
(2006) <doi:10.1007/11731139_68>, Schubert, E., Zimek, A. & Kriegel, H-P. (2014)
<doi:10.1137/1.9781611973440.63>, Latecki, L., Lazarevic, A. & Prokrajac, D.
(2007) <doi:10.1007/978-3-540-73499-4_6>, Papadimitriou, S., Gibbons, P. B., &
Faloutsos, C. (2003) <doi:10.1109/ICDE.2003.1260802>, Breunig, M. M., Kriegel,
H.-P., Ng, R. T., & Sander, J. (2000) <doi:10.1145/342009.335388>, Kriegel,
H.-P., KrÃ¶ger, P., Schubert, E., & Zimek, A. (2009)
<doi:10.1145/1645953.1646195>, Zhu, Q., Feng, Ji. & Huang, J. (2016)
<doi:10.1016/j.patrec.2016.05.007>, Huang, J., Zhu, Q., Yang, L. & Feng, J.
(2015) <doi:10.1016/j.knosys.2015.10.014>, Tang, B. & Haibo, He. (2017)
<doi:10.1016/j.neucom.2017.02.039> and Gao, J., Hu, W., Zhang, X. & Wu, Ou.
(2011) <doi:10.1007/978-3-642-20847-8_23>.")
    (license license:expat)))

(define-public r-ddml
  (package
    (name "r-ddml")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ddml" version))
       (sha256
        (base32 "1b0cl31l0zl02mxxqjqakr3q92frjy45qs41im5yb7hky29mkk70"))))
    (properties `((upstream-name . "ddml")))
    (build-system r-build-system)
    (propagated-inputs (list r-xgboost
                             r-ranger
                             r-quadprog
                             r-nnls
                             r-matrix
                             r-mass
                             r-glmnet
                             r-aer))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/thomaswiemann/ddml")
    (synopsis "Double/Debiased Machine Learning")
    (description
     "Estimate common causal parameters using double/debiased machine learning as
proposed by Chernozhukov et al. (2018) <doi:10.1111/ectj.12097>.  ddml
simplifies estimation based on (short-)stacking as discussed in Ahrens et al.
(2024) <doi:10.1177/1536867X241233641>, which leverages multiple base learners
to increase robustness to the underlying data generating process.")
    (license license:gpl3+)))

(define-public r-ddm
  (package
    (name "r-ddm")
    (version "1.0-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DDM" version))
       (sha256
        (base32 "19g06qk3lzasj294x9wfij729mlq6ryvjqkn3rgl5xp1w0gx9wi2"))))
    (properties `((upstream-name . "DDM")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DDM")
    (synopsis "Death Registration Coverage Estimation")
    (description
     "This package provides a set of three two-census methods to the estimate the
degree of death registration coverage for a population.  Implemented methods
include the Generalized Growth Balance method (GGB), the Synthetic Extinct
Generation method (SEG), and a hybrid of the two, GGB-SEG. Each method offers
automatic estimation, but users may also specify exact parameters or use a
graphical interface to guess parameters in the traditional way if desired.")
    (license license:gpl2)))

(define-public r-ddl
  (package
    (name "r-ddl")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DDL" version))
       (sha256
        (base32 "1scgg90njn8ahxdzbz1dyhr508hlipgaawk2pll0hk093abnqrlc"))))
    (properties `((upstream-name . "DDL")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-glmnet))
    (home-page "https://cran.r-project.org/package=DDL")
    (synopsis "Doubly Debiased Lasso (DDL)")
    (description
     "Statistical inference for the regression coefficients in high-dimensional linear
models with hidden confounders.  The Doubly Debiased Lasso method was proposed
in <@code{arXiv:2004.03758>}.")
    (license license:expat)))

(define-public r-ddiwr
  (package
    (name "r-ddiwr")
    (version "0.18")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DDIwR" version))
       (sha256
        (base32 "1gwyp4pwy6hs4hwpl5w106mrk0f9sfl8lgcqxr8f3l1hl9hc31sl"))))
    (properties `((upstream-name . "DDIwR")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-writexl
                             r-readxl
                             r-haven
                             r-digest
                             r-declared
                             r-base64enc
                             r-admisc))
    (home-page "https://github.com/dusadrian/DDIwR")
    (synopsis "DDI with R")
    (description
     "Useful functions for various DDI (Data Documentation Initiative) related inputs
and outputs.  Converts data files to and from DDI, SPSS, Stata, SAS, R and
Excel, including user declared missing values.")
    (license license:gpl3+)))

(define-public r-ddiv
  (package
    (name "r-ddiv")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ddiv" version))
       (sha256
        (base32 "0xsn74z78znrm3rnnvdphp89sb0lik564ha3wv6n3ldrfh1van8y"))))
    (properties `((upstream-name . "ddiv")))
    (build-system r-build-system)
    (propagated-inputs (list r-segmented r-qpdf r-mass))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ddiv")
    (synopsis "Data Driven I-v Feature Extraction")
    (description
     "The Data Driven I-V Feature Extraction is used to extract Current-Voltage (I-V)
features from I-V curves.  I-V curves indicate the relationship between current
and voltage for a solar cell or Photovoltaic (PV) modules.  The I-V features
such as maximum power point (Pmp), shunt resistance (Rsh), series resistance
(Rs),short circuit current (Isc), open circuit voltage (Voc), fill factor (FF),
current at maximum power (Imp) and voltage at maximum power(Vmp) contain
important information of the performance for PV modules.  The traditional method
uses the single diode model to model I-V curves and extract I-V features.  This
package does not use the diode model, but uses data-driven a method which select
different linear parts of the I-V curves to extract I-V features.  This method
also uses a sampling method to calculate uncertainties when extracting I-V
features.  Also, because of the partially shaded array, \"steps\" occurs in I-V
curves.  The \"Segmented Regression\" method is used to identify steps in I-V
curves.  This material is based upon work supported by the U.S. Department of
Energyâs Office of Energy Efficiency and Renewable Energy (EERE) under Solar
Energy Technologies Office (SETO) Agreement Number DE-EE0007140.  Further
information can be found in the following paper. [1] Ma, X. et al, 2019.
<doi:10.1109/JPHOTOV.2019.2928477>.")
    (license license:gpl2+)))

(define-public r-ddi
  (package
    (name "r-ddi")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ddi" version))
       (sha256
        (base32 "0pnkylz7l6brx6i73wys637w811psxhnr39lcmkag41s6jcgabd5"))))
    (properties `((upstream-name . "ddi")))
    (build-system r-build-system)
    (home-page "https://github.com/kuriwaki/ddi")
    (synopsis "The Data Defect Index for Samples that May not be IID")
    (description
     "This package implements Meng's data defect index (ddi), which represents the
degree of sample bias relative to an iid sample.  The data defect correlation
(ddc) represents the correlation between the outcome of interest and the
selection into the sample; when the sample selection is independent across the
population, the ddc is zero.  Details are in Meng (2018)
<doi:10.1214/18-AOAS1161SF>, \"Statistical Paradises and Paradoxes in Big Data
(I): Law of Large Populations, Big Data Paradox, and the 2016 US Presidential
Election.\" Survey estimates from the Cooperative Congressional Election Study
(CCES) is included to replicate the article's results.")
    (license license:gpl2+)))

(define-public r-ddhfm
  (package
    (name "r-ddhfm")
    (version "1.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DDHFm" version))
       (sha256
        (base32 "0cjwig5hr2y59csfwcmlinpp2qfvngwbb5anj7iyydp4j0ywdgqk"))))
    (properties `((upstream-name . "DDHFm")))
    (build-system r-build-system)
    (propagated-inputs (list r-wavethresh r-lokern))
    (home-page "https://cran.r-project.org/package=DDHFm")
    (synopsis
     "Variance Stabilization by Data-Driven Haar-Fisz (for Microarrays)")
    (description
     "This package contains the normalizing and variance stabilizing Data-Driven
Haar-Fisz algorithm.  Also contains related algorithms for simulating from
certain microarray gene intensity models and evaluation of certain
transformations.  Contains @code{cDNA} and shipping credit flow data.")
    (license license:gpl2)))

(define-public r-ddecompose
  (package
    (name "r-ddecompose")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ddecompose" version))
       (sha256
        (base32 "1n0s2q6qb09jnhxismaabn00pzjjjy0dwdhz8hyacmby468y266z"))))
    (properties `((upstream-name . "ddecompose")))
    (build-system r-build-system)
    (propagated-inputs (list r-sandwich
                             r-rifreg
                             r-ranger
                             r-pbapply
                             r-hmisc
                             r-ggplot2
                             r-formula
                             r-fastglm))
    (home-page "https://cran.r-project.org/package=ddecompose")
    (synopsis "Detailed Distributional Decomposition")
    (description
     "This package implements the Oaxaca-Blinder decomposition method and
generalizations of it that decompose differences in distributional statistics
beyond the mean.  The function ob_decompose() decomposes differences in the mean
outcome between two groups into one part explained by different covariates
(composition effect) and into another part due to differences in the way
covariates are linked to the outcome variable (structure effect).  The function
further divides the two effects into the contribution of each covariate and
allows for weighted doubly robust decompositions.  For distributional statistics
beyond the mean, the function performs the recentered influence function (RIF)
decomposition proposed by Firpo, Fortin, and Lemieux (2018).  The function
dfl_decompose() divides differences in distributional statistics into an
composition effect and a structure effect using inverse probability weighting as
introduced by @code{DiNardo}, Fortin, and Lemieux (1996).  The function also
allows to sequentially decompose the composition effect into the contribution of
single covariates.  References: Firpo, Sergio, Nicole M. Fortin, and Thomas
Lemieux. (2018) <doi:10.3390/econometrics6020028>. \"Decomposing Wage
Distributions Using Recentered Influence Function Regressions.\" Fortin, Nicole
M., Thomas Lemieux, and Sergio Firpo. (2011) <doi:10.3386/w16045>.
\"Decomposition Methods in Economics.\" @code{DiNardo}, John, Nicole M. Fortin,
and Thomas Lemieux. (1996) <doi:10.2307/2171954>. \"Labor Market Institutions and
the Distribution of Wages, 1973-1992: A Semiparametric Approach.\" Oaxaca,
Ronald. (1973) <doi:10.2307/2525981>. \"Male-Female Wage Differentials in Urban
Labor Markets.\" Blinder, Alan S. (1973) <doi:10.2307/144855>. \"Wage
Discrimination: Reduced Form and Structural Estimates.\".")
    (license license:gpl3+)))

(define-public r-dde
  (package
    (name "r-dde")
    (version "1.0.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dde" version))
       (sha256
        (base32 "1lvv4avajd14ph5kr7fhagigfjdyvx6077gaks9l24dwgqh6gpj2"))))
    (properties `((upstream-name . "dde")))
    (build-system r-build-system)
    (propagated-inputs (list r-ring))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mrc-ide/dde")
    (synopsis "Solve Delay Differential Equations")
    (description
     "Solves ordinary and delay differential equations, where the objective function
is written in either R or C. Suitable only for non-stiff equations, the solver
uses a Dormand-Prince method that allows interpolation of the solution at any
point.  This approach is as described by Hairer, Norsett and Wanner (1993)
<ISBN:3540604529>.  Support is also included for iterating difference equations.")
    (license license:expat)))

(define-public r-ddd
  (package
    (name "r-ddd")
    (version "5.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DDD" version))
       (sha256
        (base32 "178b4j67vvn3g22s45gx9aqch24fij34yywbpvign2dkhzahnqkn"))))
    (properties `((upstream-name . "DDD")))
    (build-system r-build-system)
    (propagated-inputs (list r-subplex
                             r-sparsem
                             r-rcppeigen
                             r-rcpp
                             r-phytools
                             r-matrix
                             r-expm
                             r-desolve
                             r-deoptim
                             r-bh
                             r-ape))
    (home-page "https://cran.r-project.org/package=DDD")
    (synopsis "Diversity-Dependent Diversification")
    (description
     "This package implements maximum likelihood and bootstrap methods based on the
diversity-dependent birth-death process to test whether speciation or extinction
are diversity-dependent, under various models including various types of key
innovations.  See Etienne et al.  2012, Proc.  Roy.  Soc.  B 279: 1300-1309,
<DOI:10.1098/rspb.2011.1439>, Etienne & Haegeman 2012, Am.  Nat.  180: E75-E89,
<DOI:10.1086/667574>, Etienne et al.  2016.  Meth.  Ecol.  Evol.  7: 1092-1099,
<DOI:10.1111/2041-210X.12565> and Laudanno et al.  2021.  Syst.  Biol.  70:
389â407, <DOI:10.1093/sysbio/syaa048>.  Also contains functions to simulate
the diversity-dependent process.")
    (license license:gpl3)))

(define-public r-ddc
  (package
    (name "r-ddc")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ddc" version))
       (sha256
        (base32 "1l5ljfhhyqcj4s4247vndqrz6qfcygi014l59d4gpxym810iqr26"))))
    (properties `((upstream-name . "ddc")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-dtwclust r-dtw))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ddc")
    (synopsis "Distance Density Clustering Algorithm")
    (description
     "This package provides a distance density clustering (DDC) algorithm in R. DDC
uses dynamic time warping (DTW) to compute a similarity matrix, based on which
cluster centers and cluster assignments are found.  DDC inherits dynamic time
warping (DTW) arguments and constraints.  The cluster centers are centroid
points that are calculated using the DTW Barycenter Averaging (DBA) algorithm.
The clustering process is divisive.  At each iteration, cluster centers are
updated and data is reassigned to cluster centers.  Early stopping is possible.
The output includes cluster centers and clustering assignment, as described in
the paper (Ma et al (2017) <doi:10.1109/ICDMW.2017.11>).")
    (license license:gpl2+)))

(define-public r-dcurves
  (package
    (name "r-dcurves")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dcurves" version))
       (sha256
        (base32 "01w20d7j9f667spmg28pp6mj5f4sxdx9z6waz2yaijgyif14drak"))))
    (properties `((upstream-name . "dcurves")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-survival
                             r-scales
                             r-rlang
                             r-purrr
                             r-glue
                             r-ggplot2
                             r-dplyr
                             r-broom))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ddsjoberg/dcurves")
    (synopsis "Decision Curve Analysis for Model Evaluation")
    (description
     "Diagnostic and prognostic models are typically evaluated with measures of
accuracy that do not address clinical consequences.  Decision-analytic
techniques allow assessment of clinical outcomes, but often require collection
of additional information may be cumbersome to apply to models that yield a
continuous result.  Decision curve analysis is a method for evaluating and
comparing prediction models that incorporates clinical consequences, requires
only the data set on which the models are tested, and can be applied to models
that have either continuous or dichotomous results.  See the following
references for details on the methods: Vickers (2006)
<doi:10.1177/0272989X06295361>, Vickers (2008) <doi:10.1186/1472-6947-8-53>, and
Pfeiffer (2020) <doi:10.1002/bimj.201800240>.")
    (license license:expat)))

(define-public r-dcurver
  (package
    (name "r-dcurver")
    (version "0.9.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dcurver" version))
       (sha256
        (base32 "1v4h480lff1cyjjwb80dksiffh0y4b3s07lq2l2r21rn1l4mav6c"))))
    (properties `((upstream-name . "dcurver")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "https://github.com/oguzhanogreden/dcurver")
    (synopsis "Utility Functions for Davidian Curves")
    (description
     "This package provides a Davidian curve defines a seminonparametric density,
whose shape and flexibility can be tuned by easy to estimate parameters.  Since
a special case of a Davidian curve is the standard normal density, Davidian
curves can be used for relaxing normality assumption in statistical applications
(Zhang & Davidian, 2001) <doi:10.1111/j.0006-341X.2001.00795.x>.  This package
provides the density function, the gradient of the loglikelihood and a random
generator for Davidian curves.")
    (license license:gpl3)))

(define-public r-dcur
  (package
    (name "r-dcur")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dCUR" version))
       (sha256
        (base32 "1blrxgf911b1y2pcp3hsv6cigpnclscjadlf5656kldblzj5w5m1"))))
    (properties `((upstream-name . "dCUR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack
                             r-ppcor
                             r-mclust
                             r-mass
                             r-magrittr
                             r-ggplot2
                             r-dplyr))
    (home-page "https://www.cesargamboasanabria.com")
    (synopsis "Dimension Reduction with Dynamic CUR")
    (description
     "Dynamic CUR (@code{dCUR}) boosts the CUR decomposition (Mahoney MW., Drineas P.
(2009) <doi:10.1073/pnas.0803205106>) varying the k, the number of columns and
rows used, and its final purposes to help find the stage, which minimizes the
relative error to reduce matrix dimension.  The goal of CUR Decomposition is to
give a better interpretation of the matrix decomposition employing proper
variable selection in the data matrix, in a way that yields a simplified
structure.  Its origins come from analysis in genetics.  The goal of this
package is to show an alternative to variable selection (columns) or individuals
(rows).  The idea proposed consists of adjusting the probability distributions
to the leverage scores and selecting the best columns and rows that minimize the
reconstruction error of the matrix approximation ||A-CUR||.  It also includes a
method that recalibrates the relative importance of the leverage scores
according to an external variable of the user's interest.")
    (license license:gpl3)))

(define-public r-dctensor
  (package
    (name "r-dctensor")
    (version "1.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dcTensor" version))
       (sha256
        (base32 "1z62kz9558fj5nwp2nq6vh7ikbxbg8nm0w08y5p5dc0nzhcd4kxn"))))
    (properties `((upstream-name . "dcTensor")))
    (build-system r-build-system)
    (propagated-inputs (list r-rtensor r-nntensor r-mass r-fields))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/rikenbit/dcTensor")
    (synopsis "Discrete Matrix/Tensor Decomposition")
    (description
     "Semi-Binary and Semi-Ternary Matrix Decomposition are performed based on
Non-negative Matrix Factorization (NMF) and Singular Value Decomposition (SVD).
For the details of the methods, see the reference section of @code{GitHub}
README.md <https://github.com/rikenbit/@code{dcTensor>}.")
    (license license:expat)))

(define-public r-dcsmooth
  (package
    (name "r-dcsmooth")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DCSmooth" version))
       (sha256
        (base32 "19pkj8z9wm4g8kxz1j3jw2n0bwldsyakipxvqpwnmlg2g5j8f5b1"))))
    (properties `((upstream-name . "DCSmooth")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo
                             r-rcpp
                             r-plotly
                             r-fracdiff
                             r-foreach
                             r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DCSmooth")
    (synopsis
     "Nonparametric Regression and Bandwidth Selection for Spatial Models")
    (description
     "Nonparametric smoothing techniques for data on a lattice and functional time
series.  Smoothing is done via kernel regression or local polynomial regression,
a bandwidth selection procedure based on an iterative plug-in algorithm is
implemented.  This package allows for modeling a dependency structure of the
error terms of the nonparametric regression model.  Methods used in this paper
are described in Feng/Schaefer (2021)
<https://ideas.repec.org/p/pdn/ciepap/144.html>, Schaefer/Feng (2021)
<https://ideas.repec.org/p/pdn/ciepap/143.html>.")
    (license license:gpl3)))

(define-public r-dcpo
  (package
    (name "r-dcpo")
    (version "0.5.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DCPO" version))
       (sha256
        (base32 "1h14xnii6kv6sc7pfxalif3bj0mifnxg46x4lwbixx9vzxxz96sq"))))
    (properties `((upstream-name . "DCPO")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stanheaders
                             r-rstantools
                             r-rstan
                             r-rcppeigen
                             r-rcpp
                             r-purrr
                             r-janitor
                             r-forcats
                             r-dplyr
                             r-bh
                             r-beepr))
    (home-page "https://cran.r-project.org/package=DCPO")
    (synopsis "Dynamic Comparative Public Opinion")
    (description
     "Estimates latent variables of public opinion cross-nationally and over time from
sparse and incomparable survey data.  DCPO uses a population-level graded
response model with country-specific item bias terms.  Sampling is conducted
with Stan'.  References: Solt (2020) <doi:10.31235/osf.io/d5n9p>.")
    (license license:gpl3+)))

(define-public r-dcovts
  (package
    (name "r-dcovts")
    (version "1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dCovTS" version))
       (sha256
        (base32 "0rwbs1z9pf8f6hpp3df584c0k5g4frbzcwr288inh1cg51maphq4"))))
    (properties `((upstream-name . "dCovTS")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfast2 r-rfast r-foreach r-doparallel r-dcov))
    (home-page "https://cran.r-project.org/package=dCovTS")
    (synopsis "Distance Covariance and Correlation for Time Series Analysis")
    (description
     "Computing and plotting the distance covariance and correlation function of a
univariate or a multivariate time series.  Both versions of biased and unbiased
estimators of distance covariance and correlation are provided.  Test statistics
for testing pairwise independence are also implemented.  Some data sets are also
included.  References include: a) Edelmann Dominic, Fokianos Konstantinos and
Pitsillou Maria (2019).  An Updated Literature Review of Distance Correlation
and Its Applications to Time Series'.  International Statistical Review, 87(2):
237--262. <doi:10.1111/insr.12294>.  b) Fokianos Konstantinos and Pitsillou
Maria (2018).  Testing independence for multivariate time series via the
auto-distance correlation matrix'.  Biometrika, 105(2): 337--352.
<doi:10.1093/biomet/asx082>.  c) Fokianos Konstantinos and Pitsillou Maria
(2017).  Consistent testing for pairwise dependence in time series'.
Technometrics, 59(2): 262--270. <doi:10.1080/00401706.2016.1156024>.  d)
Pitsillou Maria and Fokianos Konstantinos (2016). @code{dCovTS}: Distance
Covariance/Correlation for Time Series'.  R Journal, 8(2):324-340.
<doi:10.32614/RJ-2016-049>.")
    (license license:gpl2+)))

(define-public r-dcov
  (package
    (name "r-dcov")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dcov" version))
       (sha256
        (base32 "0c3a5dzpizsxlsh723pcd0d7n0mgfc9y35vrfhmskp3c1x639mh3"))))
    (properties `((upstream-name . "dcov")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "https://cran.r-project.org/package=dcov")
    (synopsis "Fast Implementation of Distance Covariance")
    (description
     "Efficient methods for computing distance covariance and relevant statistics.
See SzÃ©kely et al.(2007) <doi:10.1214/009053607000000505>; SzÃ©kely and Rizzo
(2013) <doi:10.1016/j.jmva.2013.02.012>; SzÃ©kely and Rizzo (2014)
<doi:10.1214/14-AOS1255>; Huo and SzÃ©kely (2016)
<doi:10.1080/00401706.2015.1054435>.")
    (license license:gpl2)))

(define-public r-dcorvs
  (package
    (name "r-dcorvs")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dcorVS" version))
       (sha256
        (base32 "1gawk22mv5ppbiqqm4k2pjjknsp7zxnnr0lk24l6phrvnszfaxlw"))))
    (properties `((upstream-name . "dcorVS")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfast r-dcov))
    (home-page "https://cran.r-project.org/package=dcorVS")
    (synopsis "Variable Selection Algorithms Using the Distance Correlation")
    (description
     "The FBED and mmpc variable selection algorithms have been implemented using the
distance correlation.  The references include: Tsamardinos I., Aliferis C. F.
and Statnikov A. (2003). \"Time and sample efficient discovery of Markovblankets
and direct causal relations\".  In Proceedings of the ninth ACM SIGKDD
international Conference. <doi:10.1145/956750.956838>.  Borboudakis G. and
Tsamardinos I. (2019). \"Forward-backward selection with early dropping\".
Journal of Machine Learning Research, 20(8): 1--39.
<doi:10.48550/@code{arXiv.1705.10770>}.  Huo X. and Szekely G.J. (2016). \"Fast
computing for distance covariance\".  Technometrics, 58(4): 435--447.
<doi:10.1080/00401706.2015.1054435>.")
    (license license:gpl2+)))

(define-public r-dcortools
  (package
    (name "r-dcortools")
    (version "0.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dcortools" version))
       (sha256
        (base32 "1qcblwcv2rwrl502hiv0l0r137sa4k0kx892k2w1chm40y5vri3b"))))
    (properties `((upstream-name . "dcortools")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfast
                             r-rdpack
                             r-rcppeigen
                             r-rcpparmadillo
                             r-rcpp
                             r-pheatmap
                             r-hmisc
                             r-ggplot2))
    (home-page "https://cran.r-project.org/package=dcortools")
    (synopsis
     "Providing Fast and Flexible Functions for Distance Correlation Analysis")
    (description
     "This package provides methods for distance covariance and distance correlation
(Szekely, et al. (2007) <doi:10.1214/009053607000000505>), generalized version
thereof (Sejdinovic, et al. (2013) <doi:10.1214/13-AOS1140>) and corresponding
tests (Berschneider, Bottcher (2018) <@code{arXiv:1808.07280>}.  Distance
standard deviation methods (Edelmann, et al. (2020) <doi:10.1214/19-AOS1935>)
and distance correlation methods for survival endpoints (Edelmann, et al. (2021)
<doi:10.1111/biom.13470>) are also included.")
    (license license:gpl3)))

(define-public r-dcode
  (package
    (name "r-dcode")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DCODE" version))
       (sha256
        (base32 "19dwms88q0ylxd92l3ivig8p8jjyhk8mhgz0l36m9pcq11gyjc0n"))))
    (properties `((upstream-name . "DCODE")))
    (build-system r-build-system)
    (propagated-inputs (list r-seqinr))
    (home-page "https://cran.r-project.org/package=DCODE")
    (synopsis
     "List Linear n-Peptide Constraints for Overlapping Protein Regions")
    (description
     "Traversal graph algorithm for listing linear n-peptide constraints for
overlapping protein regions. (Lebre and Gascuel, The combinatorics of
overlapping genes, freely available from @code{arXiv} at :
http://arxiv.org/abs/1602.04971).")
    (license license:gpl2+)))

(define-public r-dcmodify
  (package
    (name "r-dcmodify")
    (version "0.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dcmodify" version))
       (sha256
        (base32 "080adcvlvpiha4vlxwnxsf657i0yjmpby5iyhabbqc5hzmwm3ar5"))))
    (properties `((upstream-name . "dcmodify")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml r-validate r-settings r-lumberjack))
    (native-inputs (list r-simplermarkdown))
    (home-page "https://github.com/data-cleaning/dcmodify")
    (synopsis "Modify Data Using Externally Defined Modification Rules")
    (description
     "Data cleaning scripts typically contain a lot of if this change that type of
statements.  Such statements are typically condensed expert knowledge.  With
this package, such data modifying rules are taken out of the code and become in
stead parameters to the work flow.  This allows one to maintain, document, and
reason about data modification rules as separate entities.")
    (license license:gpl3)))

(define-public r-dcmle
  (package
    (name "r-dcmle")
    (version "0.4-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dcmle" version))
       (sha256
        (base32 "1zh243ya02232z56i0y05l891685my6g9v6wal6z5c92s179g85p"))))
    (properties `((upstream-name . "dcmle")))
    (build-system r-build-system)
    (inputs (list jags))
    (propagated-inputs (list r-lattice r-dclone r-coda))
    (home-page "https://groups.google.com/forum/#!forum/dclone-users")
    (synopsis "Hierarchical Models Made Easy with Data Cloning")
    (description
     "S4 classes around infrastructure provided by the coda and dclone packages to
make package development easy as a breeze with data cloning for hierarchical
models.")
    (license license:gpl2)))

(define-public r-dcm2
  (package
    (name "r-dcm2")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dcm2" version))
       (sha256
        (base32 "1dxymql66sy0nfxqfh106cvz5r93ajpjr1w8amn03w0ciz4v5nqs"))))
    (properties `((upstream-name . "dcm2")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-rcpparmadillo
                             r-rcpp
                             r-purrr
                             r-modelr
                             r-magrittr
                             r-glue
                             r-dplyr))
    (home-page "https://github.com/atlas-aai/dcm2")
    (synopsis
     "Calculating the M2 Model Fit Statistic for Diagnostic Classification Models")
    (description
     "This package provides a collection of functions for calculating the M2 model fit
statistic for diagnostic classification models as described by Liu et al. (2016)
<DOI:10.3102/1076998615621293>.  These functions provide multiple sources of
information for model fit according to the M2 statistic, including the M2
statistic, the *p* value for that M2 statistic, and the Root Mean Square Error
of Approximation based on the M2 statistic.")
    (license license:gpl3)))

(define-public r-dclusterm
  (package
    (name "r-dclusterm")
    (version "1.0-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DClusterm" version))
       (sha256
        (base32 "04i9fyph2k3ffds0nv49371p8lw6dkzcf27pc98f99x0l6c8k5iq"))))
    (properties `((upstream-name . "DClusterm")))
    (build-system r-build-system)
    (propagated-inputs (list r-xts r-spacetime r-sp r-lme4 r-dcluster))
    (home-page "https://cran.r-project.org/package=DClusterm")
    (synopsis "Model-Based Detection of Disease Clusters")
    (description
     "Model-based methods for the detection of disease clusters using GLMs, GLMMs and
zero-inflated models.  These methods are described in V. GÃ³mez-Rubio et al.
(2019) <doi:10.18637/jss.v090.i14> and V. GÃ³mez-Rubio et al. (2018)
<doi:10.1007/978-3-030-01584-8_1>.")
    (license license:gpl3)))

(define-public r-dcluster
  (package
    (name "r-dcluster")
    (version "0.2-10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DCluster" version))
       (sha256
        (base32 "01m41vaw26nlsisbwp627hmfxs823wcnzrmchxnp3rx4n40j82di"))))
    (properties `((upstream-name . "DCluster")))
    (build-system r-build-system)
    (propagated-inputs (list r-spdep r-mass r-boot))
    (home-page "https://cran.r-project.org/package=DCluster")
    (synopsis "Functions for the Detection of Spatial Clusters of Diseases")
    (description
     "This package provides a set of functions for the detection of spatial clusters
of disease using count data.  Bootstrap is used to estimate sampling
distributions of statistics.")
    (license license:gpl2+)))

(define-public r-dclust
  (package
    (name "r-dclust")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dclust" version))
       (sha256
        (base32 "1icfx52v3g7kkkc11pw0xlrc8dlx5q3n2zbrd3fccmw17jzxqbg7"))))
    (properties `((upstream-name . "dclust")))
    (build-system r-build-system)
    (propagated-inputs (list r-phylogram r-openssl))
    (home-page "http://github.com/shaunpwilkinson/dclust")
    (synopsis "Divisive Hierarchical Clustering")
    (description
     "This package contains a single function dclust() for divisive hierarchical
clustering based on recursive k-means partitioning (k = 2).  Useful for
clustering large datasets where computation of a n x n distance matrix is not
feasible (e.g. n > 10,000 records).  For further information see Steinbach,
Karypis and Kumar (2000)
<http://glaros.dtc.umn.edu/gkhome/fetch/papers/@code{docclusterKDDTMW00.pdf>}.")
    (license license:gpl3)))

(define-public r-dclone
  (package
    (name "r-dclone")
    (version "2.3-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dclone" version))
       (sha256
        (base32 "1x0fx24fxb7zp9g9lrdb1hbljgmi9szrsh751jidm52fin863qz0"))))
    (properties `((upstream-name . "dclone")))
    (build-system r-build-system)
    (inputs (list))
    (propagated-inputs (list r-rstan r-rjags r-r2openbugs r-matrix r-coda))
    (home-page "https://groups.google.com/forum/#!forum/dclone-users")
    (synopsis "Data Cloning and MCMC Tools for Maximum Likelihood Methods")
    (description
     "Low level functions for implementing maximum likelihood estimating procedures
for complex models using data cloning and Bayesian Markov chain Monte Carlo
methods as described in Solymos 2010 <doi:10.32614/RJ-2010-011>.  Sequential and
parallel MCMC support for JAGS', @code{WinBUGS}', @code{OpenBUGS}', and Stan'.")
    (license license:gpl2)))

(define-public r-dclear
  (package
    (name "r-dclear")
    (version "1.0.13")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DCLEAR" version))
       (sha256
        (base32 "0f8q0avzl3jpjly1jsg02lz8h38208j25nfdf1v79qcp4ia7m3pp"))))
    (properties `((upstream-name . "DCLEAR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tensorflow
                             r-stringr
                             r-rlang
                             r-rcpparmadillo
                             r-rcpp
                             r-rbayesianoptimization
                             r-purrr
                             r-phangorn
                             r-matrixstats
                             r-matrix
                             r-igraph
                             r-dplyr
                             r-biocparallel
                             r-biocgenerics
                             r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ikwak2/DCLEAR")
    (synopsis "Distance Based Cell Lineage Reconstruction")
    (description
     "R codes for distance based cell lineage reconstruction.  Our methods won both
sub-challenges 2 and 3 of the Allen Institute Cell Lineage Reconstruction DREAM
Challenge in 2020.  References: Gong et al. (2021)
<doi:10.1016/j.cels.2021.05.008>, Gong et al. (2022)
<doi:10.1186/s12859-022-04633-x>.")
    (license license:gpl3)))

(define-public r-dcl
  (package
    (name "r-dcl")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DCL" version))
       (sha256
        (base32 "0r9zigbxaa9w8501mishydyp47rpzfrx717m0ysly6nkxfm6g6d6"))))
    (properties `((upstream-name . "DCL")))
    (build-system r-build-system)
    (propagated-inputs (list r-latticeextra r-lattice))
    (home-page "https://cran.r-project.org/package=DCL")
    (synopsis "Claims Reserving under the Double Chain Ladder Model")
    (description
     "Statistical modelling and forecasting in claims reserving in non-life insurance
under the Double Chain Ladder framework by Martinez-Miranda, Nielsen and Verrall
(2012).")
    (license license:gpl2)))

(define-public r-dcifer
  (package
    (name "r-dcifer")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dcifer" version))
       (sha256
        (base32 "1pibkybr2v1qci2vqbz1sms01y81x0i4r2sq23c5xkgwnwccfy9r"))))
    (properties `((upstream-name . "dcifer")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/EPPIcenter/dcifer")
    (synopsis "Genetic Relatedness Between Polyclonal Infections")
    (description
     "An implementation of Dcifer (Distance for complex infections: fast estimation of
relatedness), an identity by descent (IBD) based method to calculate genetic
relatedness between polyclonal infections from biallelic and multiallelic data.
The package includes functions that format and preprocess the data, implement
the method, and visualize the results.  Gerlovina et al. (2022)
<doi:10.1093/genetics/iyac126>.")
    (license license:expat)))

(define-public r-dchipio
  (package
    (name "r-dchipio")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dChipIO" version))
       (sha256
        (base32 "1xrafw5h071d8rfqaic3gifc80jpiddjz5x6l2cr8kgjvph60gqh"))))
    (properties `((upstream-name . "dChipIO")))
    (build-system r-build-system)
    (home-page "https://github.com/HenrikBengtsson/dChipIO")
    (synopsis "Methods for Reading dChip Files")
    (description
     "This package provides functions for reading DCP and CDF.bin files generated by
the @code{dChip} software.")
    (license license:lgpl2.1+)))

(define-public r-dchaos
  (package
    (name "r-dchaos")
    (version "0.1-7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DChaos" version))
       (sha256
        (base32 "1xnsc8p8nn72m081hsfnjzsd060y79ah6b7axxsslb2a4zdyhh2g"))))
    (properties `((upstream-name . "DChaos")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-xts r-sandwich r-pracma r-nnet))
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=DChaos")
    (synopsis "Chaotic Time Series Analysis")
    (description
     "Chaos theory has been hailed as a revolution of thoughts and attracting ever
increasing attention of many scientists from diverse disciplines.  Chaotic
systems are nonlinear deterministic dynamic systems which can behave like an
erratic and apparently random motion.  A relevant field inside chaos theory and
nonlinear time series analysis is the detection of a chaotic behaviour from
empirical time series data.  One of the main features of chaos is the well known
initial value sensitivity property.  Methods and techniques related to test the
hypothesis of chaos try to quantify the initial value sensitive property
estimating the Lyapunov exponents.  The DChaos package provides different useful
tools and efficient algorithms which test robustly the hypothesis of chaos based
on the Lyapunov exponent in order to know if the data generating process behind
time series behave chaotically or not.")
    (license license:gpl2+)))

(define-public r-dcg
  (package
    (name "r-dcg")
    (version "0.9.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DCG" version))
       (sha256
        (base32 "08718x6v3g7kpfv0gpgm19cn3d3ynj7yagzs0jic1j5rwvn04pfb"))))
    (properties `((upstream-name . "DCG")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DCG")
    (synopsis
     "Data Cloud Geometry (DCG): Using Random Walks to Find Community Structure in Social Network Analysis")
    (description
     "Data cloud geometry (DCG) applies random walks in finding community structures
for social networks.  Fushing, @code{VanderWaal}, @code{McCowan}, & Koehl (2013)
(<doi:10.1371/journal.pone.0056259>).")
    (license license:gpl2+)))

(define-public r-dcetool
  (package
    (name "r-dcetool")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DCEtool" version))
       (sha256
        (base32 "18x0fk71is77cc5ldm890asqrm1dz45m14z2ic9df89fm0wpwrvg"))))
    (properties `((upstream-name . "DCEtool")))
    (build-system r-build-system)
    (propagated-inputs (list r-writexl
                             r-tidyr
                             r-survival
                             r-shinywidgets
                             r-shinycssloaders
                             r-shinybs
                             r-shiny
                             r-rlist
                             r-remotes
                             r-readxl
                             r-mvtnorm
                             r-mlogit
                             r-mass
                             r-magrittr
                             r-knitr
                             r-idefix
                             r-htmltools
                             r-ggplot2
                             r-dt
                             r-dfidx
                             r-adjustedcranlogs))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DCEtool")
    (synopsis "Efficient and Accessible Discrete Choice Experiments")
    (description
     "Design, conduct and analyze DCEs from a virtual interface in shiny.  Reference:
Perez-Troncoso, D. (2022) <https://github.com/danielpereztr/DCEtool>.")
    (license license:gpl3)))

(define-public r-dcemgmt
  (package
    (name "r-dcemgmt")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DCEmgmt" version))
       (sha256
        (base32 "1vv212baycn0xkk2caj1f00ps1512261h21akmyqjhij3q4lxikx"))))
    (properties `((upstream-name . "DCEmgmt")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-mlogit))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DCEmgmt")
    (synopsis "DCE Data Reshaping and Processing")
    (description
     "Prepare the results of a DCE to be analysed through choice models.'DCEmgmt
reshapes DCE data from wide to long format considering the special
characteristics of a DCE. DCEmgmt includes the function DCEestm which estimates
choice models once the database has been reshaped with DCEmgmt'.")
    (license license:gpl3)))

(define-public r-dcem
  (package
    (name "r-dcem")
    (version "2.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DCEM" version))
       (sha256
        (base32 "04z0lya1dbkdzjbgn8g6p16969kc6s4zrk87wy0i42h2hx0yx1zv"))))
    (properties `((upstream-name . "DCEM")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-mvtnorm r-matrixcalc r-mass))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/parichit/DCEM")
    (synopsis
     "Clustering Big Data using Expectation Maximization Star (EM*) Algorithm")
    (description
     "This package implements the Improved Expectation Maximisation EM* and the
traditional EM algorithm for clustering big data (gaussian mixture models for
both multivariate and univariate datasets).  This version implements the faster
alternative-EM* that expedites convergence via structure based data segregation.
 The implementation supports both random and K-means++ based initialization.
Reference: Parichit Sharma, Hasan Kurban, Mehmet Dalkilic (2022)
<doi:10.1016/j.softx.2021.100944>.  Hasan Kurban, Mark Jenne, Mehmet Dalkilic
(2016) <doi:10.1007/s41060-017-0062-1>.")
    (license license:gpl3)))

(define-public r-dccpp
  (package
    (name "r-dccpp")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dccpp" version))
       (sha256
        (base32 "1j17rv9wklmxbxa6ri9vhl370jzhi00h7h8hz1ajzqf6v3b2lkvc"))))
    (properties `((upstream-name . "dccpp")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "https://dccpp.berrisch.biz/")
    (synopsis "Fast Computation of Distance Correlations")
    (description
     "Fast computation of the distance covariance dcov and distance correlation dcor'.
 The computation cost is only O(n log(n)) for the distance correlation (see
Chaudhuri, Hu (2019) <@code{arXiv:1810.11332>}
<doi:10.1016/j.csda.2019.01.016>).  The functions are written entirely in C++ to
speed up the computation.")
    (license license:gpl3+)))

(define-public r-dccmidas
  (package
    (name "r-dccmidas")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dccmidas" version))
       (sha256
        (base32 "0ws853yb669hki7wrfwnj7bd75xvcb63njn1iza8q58sa6bmg6vc"))))
    (properties `((upstream-name . "dccmidas")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-xts
                             r-rumidas
                             r-rugarch
                             r-roll
                             r-rdpack
                             r-rcpparmadillo
                             r-rcpp
                             r-maxlik))
    (home-page "https://cran.r-project.org/package=dccmidas")
    (synopsis
     "DCC Models with GARCH and GARCH-MIDAS Specifications in the Univariate Step, RiskMetrics, Moving Covariance and Scalar and Diagonal BEKK Models")
    (description
     "Estimates a variety of Dynamic Conditional Correlation (DCC) models.  More in
detail, the dccmidas package allows the estimation of the corrected DCC
(@code{cDCC}) of Aielli (2013) <doi:10.1080/07350015.2013.771027>, the DCC-MIDAS
of Colacito et al. (2011) <doi:10.1016/j.jeconom.2011.02.013>, the Asymmetric
DCC of Cappiello et al. <doi:10.1093/jjfinec/nbl005>, and the Dynamic
Equicorrelation (DECO) of Engle and Kelly (2012)
<doi:10.1080/07350015.2011.652048>.  dccmidas offers the possibility of
including standard GARCH <doi:10.1016/0304-4076(86)90063-1>, GARCH-MIDAS
<doi:10.1162/REST_a_00300> and Double Asymmetric GARCH-MIDAS
<doi:10.1016/j.econmod.2018.07.025> models in the univariate estimation.
Moreover, also the scalar and diagonal BEKK <doi:10.1017/S0266466600009063>
models can be estimated.  Finally, the package calculates also the var-cov
matrix under two non-parametric models: the Moving Covariance and the
@code{RiskMetrics} specifications.")
    (license license:gpl3)))

(define-public r-dcchoice
  (package
    (name "r-dcchoice")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DCchoice" version))
       (sha256
        (base32 "0mkssdybfychg0jpx7542sdbhxv275lz82qhnag5r8qn0zsj7mx9"))))
    (properties `((upstream-name . "DCchoice")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-interval r-formula))
    (home-page "http://www.agr.hokudai.ac.jp/spmur/")
    (synopsis "Analyzing Dichotomous Choice Contingent Valuation Data")
    (description
     "This package provides functions for analyzing dichotomous choice contingent
valuation (CV) data.  It provides functions for estimating parametric and
nonparametric models for single-, one-and-one-half-, and double-bounded CV data.
 For details, see Aizaki et al. (2022) <doi:10.1007/s42081-022-00171-1>.")
    (license license:gpl2+)))

(define-public r-dcca
  (package
    (name "r-dcca")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DCCA" version))
       (sha256
        (base32 "06xdx79r7dr14dlk5vgcyd8ar4sc72imlyk66bnia1kvlynvdy69"))))
    (properties `((upstream-name . "DCCA")))
    (build-system r-build-system)
    (propagated-inputs (list r-checkmate))
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=DCCA")
    (synopsis "Detrended Fluctuation and Detrended Cross-Correlation Analysis")
    (description
     "This package provides a collection of functions to perform Detrended Fluctuation
Analysis (DFA) and Detrended Cross-Correlation Analysis (DCCA).  This package
implements the results presented in Prass, T.S. and Pumi, G. (2019). \"On the
behavior of the DFA and DCCA in trend-stationary processes\"
<@code{arXiv:1910.10589>}.")
    (license license:gpl3+)))

(define-public r-dc3net
  (package
    (name "r-dc3net")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dc3net" version))
       (sha256
        (base32 "19ibsvbnq6y88vqvgkm31zrqwjhpml59d792bz0zkk50r1q5bnyr"))))
    (properties `((upstream-name . "dc3net")))
    (build-system r-build-system)
    (propagated-inputs (list r-igraph r-c3net))
    (home-page "https://cran.r-project.org/package=dc3net")
    (synopsis
     "Inferring Condition-Specific Networks via Differential Network Inference")
    (description
     "This package performs differential network analysis to infer disease specific
gene networks.")
    (license license:gpl3+)))

(define-public r-dbx
  (package
    (name "r-dbx")
    (version "0.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbx" version))
       (sha256
        (base32 "0d5ha0syhrgfx157hkmyfdsxf57crjj28afdb2xxyindakplgp29"))))
    (properties `((upstream-name . "dbx")))
    (build-system r-build-system)
    (propagated-inputs (list r-dbi))
    (home-page "https://github.com/ankane/dbx")
    (synopsis "Fast, Easy-to-Use Database Interface")
    (description
     "This package provides select, insert, update, upsert, and delete database
operations.  Supports @code{PostgreSQL}', @code{MySQL}', SQLite', and more, and
plays nicely with the DBI package.")
    (license license:expat)))

(define-public r-dbwebforms
  (package
    (name "r-dbwebforms")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbWebForms" version))
       (sha256
        (base32 "0diz5mh4fhwrwqa7jr70vzj2jks7h2n91v2hr1mvvlbc7rzd9yki"))))
    (properties `((upstream-name . "dbWebForms")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi r-html5 r-dbi r-data-table))
    (home-page "https://cran.r-project.org/package=dbWebForms")
    (synopsis
     "Produce R Functions to Create HTML Forms Based on SQL Meta Data")
    (description
     "Offers meta programming style tools to generate configurable R functions that
produce HTML forms based on table input and SQL meta data.  Also generates
functions for collecting the parameters of those HTML forms after they are
submitted.  Useful for quickly generating HTML forms based on existing SQL
tables.  To use the resultant functions, the output files containing those
functions must be read into the R environment (perhaps using base::source()).")
    (license license:gpl2+)))

(define-public r-dbw
  (package
    (name "r-dbw")
    (version "1.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbw" version))
       (sha256
        (base32 "0sz8wcknmxaqgwqliahvh5vf3j7h9iayjm8kwqgn4qpkm4b4hni3"))))
    (properties `((upstream-name . "dbw")))
    (build-system r-build-system)
    (home-page "https://github.com/hirotokatsumata/dbw")
    (synopsis "Doubly Robust Distribution Balancing Weighting Estimation")
    (description
     "This package implements the doubly robust distribution balancing weighting
proposed by Katsumata (2024) <doi:10.1017/psrm.2024.23>, which improves the
augmented inverse probability weighting (AIPW) by estimating propensity scores
with estimating equations suitable for the pre-specified parameter of interest
(e.g., the average treatment effects or the average treatment effects on the
treated) and estimating outcome models with the estimated inverse probability
weights.  It also implements the covariate balancing propensity score proposed
by Imai and Ratkovic (2014) <doi:10.1111/rssb.12027> and the entropy balancing
weighting proposed by Hainmueller (2012) <doi:10.1093/pan/mpr025>, both of which
use covariate balancing conditions in propensity score estimation.  The point
estimate of the parameter of interest and its uncertainty as well as
coefficients for propensity score estimation and outcome regression are produced
using the M-estimation.  The same functions can be used to estimate average
outcomes in missing outcome cases.")
    (license license:expat)))

(define-public r-dbtcshiny
  (package
    (name "r-dbtcshiny")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DBTCShiny" version))
       (sha256
        (base32 "0rk9f4wbpmibydbmq17bjfgdznpl67xfd5f1srkpnai459c5ni6y"))))
    (properties `((upstream-name . "DBTCShiny")))
    (build-system r-build-system)
    (propagated-inputs (list r-shinywidgets
                             r-shinyjs
                             r-shinyfiles
                             r-shinydashboard
                             r-shinycssloaders
                             r-shiny
                             r-magrittr
                             r-leaflet-extras
                             r-leaflet
                             r-ggplot2
                             r-dt
                             r-dbtc))
    (home-page "<https://github.com/rgyoung6/DBTCShiny>")
    (synopsis
     "Dada-BLAST-Taxon Assign-Condense Metabarcode Analysis 'shiny' Application")
    (description
     "Metabarcoding analysis using the DBTC package is implemented here using shiny in
an interactive graphical user interface to conduct Metabarcode analyses and
visualize and filter results.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-dbtc
  (package
    (name "r-dbtc")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DBTC" version))
       (sha256
        (base32 "1w4sm78nvzmc7hjdpjxsj4qncwnymdqni5jkllircglsjimps75y"))))
    (properties `((upstream-name . "DBTC")))
    (build-system r-build-system)
    (propagated-inputs (list r-taxonomizr
                             r-shortread
                             r-plyr
                             r-pbapply
                             r-ggplot2
                             r-dada2))
    (home-page "<https://github.com/rgyoung6/DBTC>")
    (synopsis "Dada-BLAST-Taxon Assign-Condense Metabarcode Analysis")
    (description
     "First using dada2 R tools to analyse metabarcode data, the DBTC package then
uses the BLAST algorithm to search unknown sequences against local databases,
and then takes reduced matched results and provides best taxonomic assignments.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-dbstats
  (package
    (name "r-dbstats")
    (version "2.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbstats" version))
       (sha256
        (base32 "1rnjgzil98rys9fa0jkamfqrkski3vd7wi59mqg8xk26xw0v5c96"))))
    (properties `((upstream-name . "dbstats")))
    (build-system r-build-system)
    (propagated-inputs (list r-pls r-cluster))
    (home-page "https://cran.r-project.org/package=dbstats")
    (synopsis "Distance-Based Statistics")
    (description
     "Prediction methods where explanatory information is coded as a matrix of
distances between individuals.  Distances can either be directly input as a
distances matrix, a squared distances matrix, an inner-products matrix or
computed from observed predictors.")
    (license license:gpl2)))

(define-public r-dbr
  (package
    (name "r-dbr")
    (version "1.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DBR" version))
       (sha256
        (base32 "1gs9d1qmv4mcmryzzvmwbz6ycinhnxnkiv56l31mbqy50qjn9bi4"))))
    (properties `((upstream-name . "DBR")))
    (build-system r-build-system)
    (propagated-inputs (list r-mfusampler r-coda))
    (home-page "https://cran.r-project.org/package=DBR")
    (synopsis "Discrete Beta Regression")
    (description
     "Bayesian Beta Regression, adapted for bounded discrete responses, commonly seen
in survey responses.  Estimation is done via Markov Chain Monte Carlo sampling,
using a Gibbs wrapper around univariate slice sampler (Neal (2003)
<DOI:10.1214/aos/1056562461>), as implemented in the R package @code{MfUSampler}
(Mahani and Sharabiani (2017) <DOI: 10.18637/jss.v078.c01>).")
    (license license:gpl2+)))

(define-public r-dbpower
  (package
    (name "r-dbpower")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DBpower" version))
       (sha256
        (base32 "04wwhzlc9g6il478ax5yvh74bbb6hs29jyslkiz3k1hi25hlpkrn"))))
    (properties `((upstream-name . "DBpower")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm
                             r-magrittr
                             r-kit
                             r-gbj
                             r-dplyr
                             r-combinat))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DBpower")
    (synopsis "Finite Sample Power Calculations for Detection Boundary Tests")
    (description
     "Calculates lower bound on power, upper bound on power, and exact power (small
sets only) for detection boundary tests (e.g. Berk-Jones, Generalized
Berk-Jones, innovated Berk-Jones) used in set-based inference studies.  These
detection boundary tests are described in Sun et al., (2019)
<doi:10.1080/01621459.2019.1660170>.")
    (license license:gpl3)))

(define-public r-dbplot
  (package
    (name "r-dbplot")
    (version "0.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbplot" version))
       (sha256
        (base32 "1svizj9hcd417yii8ll9s3mnvdqpa5awy9xl71kbwpfcnpdzqf1r"))))
    (properties `((upstream-name . "dbplot")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-purrr r-magrittr r-ggplot2 r-dplyr))
    (home-page "https://github.com/edgararuiz/dbplot")
    (synopsis "Simplifies Plotting Data Inside Databases")
    (description
     "Leverages dplyr to process the calculations of a plot inside a database.  This
package provides helper functions that abstract the work at three levels:
outputs a ggplot', outputs the calculations, outputs the formula needed to
calculate bins.")
    (license license:gpl3)))

(define-public r-dbparser
  (package
    (name "r-dbparser")
    (version "2.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbparser" version))
       (sha256
        (base32 "1v0yp81bgq9ihgjrx336zyscrhk84sc8rpmbj35sphyc0c0isncs"))))
    (properties `((upstream-name . "dbparser")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml r-tibble r-purrr r-progress r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/dbparser/")
    (synopsis "Drugs Databases Parser")
    (description
     "This tool is for parsing public drug databases such as @code{DrugBank} XML
database <https://go.drugbank.com/>.  The parsed data are then returned in a
proper R object called dvobject'.")
    (license license:expat)))

(define-public r-dbnr
  (package
    (name "r-dbnr")
    (version "0.7.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbnR" version))
       (sha256
        (base32 "14jdmld8d1laj7xcad5694inxb8qglhnzghab64h3n0r2x35z6lw"))))
    (properties `((upstream-name . "dbnR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp
                             r-r6
                             r-mass
                             r-magrittr
                             r-data-table
                             r-bnlearn))
    (home-page "https://github.com/dkesada/dbnR")
    (synopsis "Dynamic Bayesian Network Learning and Inference")
    (description
     "Learning and inference over dynamic Bayesian networks of arbitrary Markovian
order.  Extends some of the functionality offered by the bnlearn package to
learn the networks from data and perform exact inference.  It offers three
structure learning algorithms for dynamic Bayesian networks: Trabelsi G. (2013)
<doi:10.1007/978-3-642-41398-8_34>, Santos F.P. and Maciel C.D. (2014)
<doi:10.1109/BRC.2014.6880957>, Quesada D., Bielza C. and LarraÃ±aga P. (2021)
<doi:10.1007/978-3-030-86271-8_14>.  It also offers the possibility to perform
forecasts of arbitrary length.  A tool for visualizing the structure of the net
is also provided via the @code{visNetwork} package.")
    (license license:gpl3)))

(define-public r-dbnmfrank
  (package
    (name "r-dbnmfrank")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DBNMFrank" version))
       (sha256
        (base32 "1snnyc9dvlkxydx3n6mims1avbibkkmaf5z440s28ibf9a9l91wj"))))
    (properties `((upstream-name . "DBNMFrank")))
    (build-system r-build-system)
    (propagated-inputs (list r-pmledecon r-nmf))
    (home-page "https://cran.r-project.org/package=DBNMFrank")
    (synopsis "Rank Selection for Non-Negative Matrix Factorization")
    (description
     "Given the non-negative data and its distribution, the package estimates the rank
parameter for Non-negative Matrix Factorization.  The method is based on
hypothesis testing, using a deconvolved bootstrap distribution to assess the
significance level accurately despite the large amount of optimization error.
The distribution of the non-negative data can be either Normal distributed or
Poisson distributed.")
    (license license:gpl3+)))

(define-public r-dbnlearn
  (package
    (name "r-dbnlearn")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbnlearn" version))
       (sha256
        (base32 "0kmyiad7v96mnfi24d2pn3dqmk3g82sx348m1vhhqwijfnj53brb"))))
    (properties `((upstream-name . "dbnlearn")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2 r-bnviewer r-bnlearn))
    (home-page "https://cran.r-project.org/package=dbnlearn")
    (synopsis
     "Dynamic Bayesian Network Structure Learning, Parameter Learning and Forecasting")
    (description
     "It allows to learn the structure of univariate time series, learning parameters
and forecasting.  Implements a model of Dynamic Bayesian Networks with temporal
windows, with collections of linear regressors for Gaussian nodes, based on the
introductory texts of Korb and Nicholson (2010) <doi:10.1201/b10391> and
Nagarajan, Scutari and LÃ¨bre (2013) <doi:10.1007/978-1-4614-6446-4>.")
    (license license:expat)))

(define-public r-dbmss
  (package
    (name "r-dbmss")
    (version "2.9-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbmss" version))
       (sha256
        (base32 "1131lfli0fna2yvq383f710sr87fwfg5gngiawrhdx8b14zn796p"))))
    (properties `((upstream-name . "dbmss")))
    (build-system r-build-system)
    (inputs (list pandoc))
    (propagated-inputs (list r-tibble
                             r-spatstat-utils
                             r-spatstat-random
                             r-spatstat-geom
                             r-spatstat-explore
                             r-rlang
                             r-reshape2
                             r-rcppparallel
                             r-rcpp
                             r-ggplot2
                             r-cubature))
    (native-inputs (list r-knitr))
    (home-page "https://ericmarcon.github.io/dbmss/")
    (synopsis "Distance-Based Measures of Spatial Structures")
    (description
     "Simple computation of spatial statistic functions of distance to characterize
the spatial structures of mapped objects, following Marcon, Traissac, Puech, and
Lang (2015) <doi:10.18637/jss.v067.c03>.  Includes classical functions (Ripley's
K and others) and more recent ones used by spatial economists (Duranton and
Overman's Kd, Marcon and Puech's M).  Relies on spatstat for some core
calculation.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-dbmodelselect
  (package
    (name "r-dbmodelselect")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DBModelSelect" version))
       (sha256
        (base32 "1cbnypvcglbvlxdpr95yd65qfd56fhfx14gd0mr71jkkqhgmj0pk"))))
    (properties `((upstream-name . "DBModelSelect")))
    (build-system r-build-system)
    (home-page "https://github.com/shkoeneman/DBModelSelect")
    (synopsis "Distribution-Based Model Selection")
    (description
     "Perform model selection using distribution and probability-based methods,
including standardized AIC, BIC, and AICc.  These standardized information
criteria allow one to perform model selection in a way similar to the prevalent
\"Rule of 2\" method, but formalize the method to rely on probability theory.  A
novel goodness-of-fit procedure for assessing linear regression models is also
available.  This test relies on theoretical properties of the estimated error
variance for a normal linear regression model, and employs a bootstrap procedure
to assess the null hypothesis that the fitted model shows no lack of fit.  For
more information, see Koeneman and Cavanaugh (2023) <@code{arXiv:2309.10614>}.
Functionality to perform all subsets linear or generalized linear regression is
also available.")
    (license license:gpl3)))

(define-public r-dbmc
  (package
    (name "r-dbmc")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbMC" version))
       (sha256
        (base32 "0gcgn3m10sx0naim206jkw7szl0mr7vbnkn25avvv9f8iy3y9vcv"))))
    (properties `((upstream-name . "dbMC")))
    (build-system r-build-system)
    (propagated-inputs (list r-softimpute))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dbMC")
    (synopsis
     "Confidence Interval for Matrix Completion via De-Biased Estimator")
    (description
     "This package implements the de-biased estimator for low-rank matrix completion
and provides confidence intervals for entries of interest.  See: by Chen et al.
(2019) <doi:10.1073/pnas.1910053116>, Mai (2021) <@code{arXiv:2103.11749>}.")
    (license license:gpl2)))

(define-public r-dblr
  (package
    (name "r-dblr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dblr" version))
       (sha256
        (base32 "0wzmhmp706mw0pkh81nsb7qzclwyhm6f2mjvpvz043ng5xrxwvvw"))))
    (properties `((upstream-name . "dblr")))
    (build-system r-build-system)
    (propagated-inputs (list r-xgboost r-metrics r-data-table r-catencoders))
    (home-page "https://cran.r-project.org/package=dblr")
    (synopsis "Discrete Boosting Logistic Regression")
    (description
     "Trains logistic regression model by discretizing continuous variables via
gradient boosting approach.  The proposed method tries to achieve a tradeoff
between interpretation and prediction accuracy for logistic regression by
discretizing the continuous variables.  The variable binning is accomplished in
a supervised fashion.  The model trained by this package is still a single
logistic regression model, but not a sequence of logistic regression models.
The fitted model object returned from the model training consists of two tables.
 One table is used to give the boundaries of bins for each continuous variable
as well as the corresponding coefficients, and the other one is used for
discrete variables.  This package can also be used for binning continuous
variables for other statistical analysis.")
    (license license:gpl3)))

(define-public r-dblockmodeling
  (package
    (name "r-dblockmodeling")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dBlockmodeling" version))
       (sha256
        (base32 "18y6pkp273q15nkgqywzknsq1mnbiaw8jlzsaa76zadxf7xhsxls"))))
    (properties `((upstream-name . "dBlockmodeling")))
    (build-system r-build-system)
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=dBlockmodeling")
    (synopsis
     "Deterministic Blockmodeling of Signed, One-Mode and Two-Mode Networks")
    (description
     "It contains functions to apply blockmodeling of signed (positive and negative
weights are assigned to the links), one-mode and valued one-mode and two-mode
(two sets of nodes are considered, e.g. employees and organizations) networks
(Brusco et al. (2019) <doi:10.1111/bmsp.12192>).")
    (license license:gpl2+)))

(define-public r-dblcens
  (package
    (name "r-dblcens")
    (version "1.1.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dblcens" version))
       (sha256
        (base32 "1m5v8hx9n5rh5f230m8f0iss6s29qjbg4wp1mjihckw8df5qf1aj"))))
    (properties `((upstream-name . "dblcens")))
    (build-system r-build-system)
    (home-page "https://github.com/yfyang86/dblcens/")
    (synopsis
     "Compute the NPMLE of Distribution Function from Doubly Censored Data, Plus the Empirical Likelihood Ratio for F(T)")
    (description
     "Doubly censored data, as described in Chang and Yang (1987) <doi:
10.1214/aos/1176350608>), are commonly seen in many fields.  We use EM algorithm
to compute the non-parametric MLE (NPMLE) of the cummulative probability
function/survival function and the two censoring distributions.  One can also
specify a constraint F(T)=C, it will return the constrained NPMLE and the -2 log
empirical likelihood ratio for this constraint.  This can be used to test the
hypothesis about the constraint and, by inverting the test, find confidence
intervals for probability or quantile via empirical likelihood ratio theorem.
Influence functions of hat F may also be calculated, but currently, the it may
be slow.")
    (license license:gpl2+)))

(define-public r-dbitest
  (package
    (name "r-dbitest")
    (version "1.8.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DBItest" version))
       (sha256
        (base32 "0vj7989s9qip3mxjzffrm7prh0xxpp467y9m4ls7dz7m3b7inpxl"))))
    (properties `((upstream-name . "DBItest")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr
                             r-testthat
                             r-rlang
                             r-palmerpenguins
                             r-nanoarrow
                             r-magrittr
                             r-lubridate
                             r-hms
                             r-desc
                             r-dbi
                             r-callr
                             r-blob))
    (native-inputs (list r-knitr))
    (home-page "https://dbitest.r-dbi.org")
    (synopsis "Testing DBI Backends")
    (description
     "This package provides a helper that tests DBI back ends for conformity to the
interface.")
    (license license:lgpl2.1+)))

(define-public r-dbhydror
  (package
    (name "r-dbhydror")
    (version "0.2-8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbhydroR" version))
       (sha256
        (base32 "1gd3n6i47qbxp6d3y5sjvgmxc5p3afy2lhkg9020ws1xm0bk9q7d"))))
    (properties `((upstream-name . "dbhydroR")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml r-reshape2 r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ropensci/dbhydroR")
    (synopsis "'DBHYDRO' Hydrologic and Water Quality Data")
    (description
     "Client for programmatic access to the South Florida Water Management District's
DBHYDRO database at <https://www.sfwmd.gov/science-data/dbhydro>, with functions
for accessing hydrologic and water quality data.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-dbhc
  (package
    (name "r-dbhc")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DBHC" version))
       (sha256
        (base32 "0r9c2vjnrahi3kbg7gz3z9k1i8vdqc44rc6nq7xk1j2xs1s6wsxp"))))
    (properties `((upstream-name . "DBHC")))
    (build-system r-build-system)
    (propagated-inputs (list r-traminer r-seqhmm r-reshape2 r-ggplot2))
    (home-page "https://github.com/gabybudel/DBHC")
    (synopsis "Sequence Clustering with Discrete-Output HMMs")
    (description
     "This package provides an implementation of a mixture of hidden Markov models
(HMMs) for discrete sequence data in the Discrete Bayesian HMM Clustering (DBHC)
algorithm.  The DBHC algorithm is an HMM Clustering algorithm that finds a
mixture of discrete-output HMMs while using heuristics based on Bayesian
Information Criterion (BIC) to search for the optimal number of HMM states and
the optimal number of clusters.")
    (license license:gpl3+)))

(define-public r-dbglm
  (package
    (name "r-dbglm")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbglm" version))
       (sha256
        (base32 "1ljfi31n8d1mh1lr4q00klp74fz0c0jy9wdy2svhlzaszbrg76ky"))))
    (properties `((upstream-name . "dbglm")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-tidyverse
                             r-tidyr
                             r-tidypredict
                             r-tibble
                             r-stringr
                             r-rlang
                             r-purrr
                             r-knitr
                             r-dplyr
                             r-dbplyr
                             r-dbi))
    (home-page "https://cran.r-project.org/package=dbglm")
    (synopsis
     "Generalised Linear Models by Subsampling and One-Step Polishing")
    (description
     "Fast fitting of generalised linear models on moderately large datasets, by
taking an initial sample, fitting in memory, then evaluating the score function
for the full data in the database.  Thomas Lumley
<doi:10.1080/10618600.2019.1610312>.")
    (license license:expat)))

(define-public r-dbgapcheckup
  (package
    (name "r-dbgapcheckup")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbGaPCheckup" version))
       (sha256
        (base32 "1q1gx73fl016kpk6p9cfwx580kwnq9fvhpi96iyrr40rf27m39dv"))))
    (properties `((upstream-name . "dbGaPCheckup")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-rmarkdown
                             r-rlang
                             r-readxl
                             r-questionr
                             r-purrr
                             r-pander
                             r-naniar
                             r-magrittr
                             r-labelled
                             r-ggplot2
                             r-formatr
                             r-dplyr))
    (native-inputs (list r-rmarkdown r-knitr r-formatr))
    (home-page "https://lwheinsberg.github.io/dbGaPCheckup/")
    (synopsis "dbGaP Checkup")
    (description
     "This package contains functions that check for formatting of the Subject
Phenotype data set and data dictionary as specified by the National Center for
Biotechnology Information (NCBI) Database of Genotypes and Phenotypes
(@code{dbGaP}) <https://www.ncbi.nlm.nih.gov/gap/docs/submissionguide/>.")
    (license license:gpl2)))

(define-public r-dbflobr
  (package
    (name "r-dbflobr")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbflobr" version))
       (sha256
        (base32 "04gh0xfdp077f3ppf8i101q17n2r711y47qnxb9nq5ksnf37s5jp"))))
    (properties `((upstream-name . "dbflobr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rsqlite
                             r-rlang
                             r-glue
                             r-flobr
                             r-dbi
                             r-crayon
                             r-clisymbols
                             r-chk
                             r-blob))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/poissonconsulting/dbflobr")
    (synopsis "Read and Write Files to SQLite Databases")
    (description
     "Reads and writes files to SQLite databases <https://www.sqlite.org/index.html>
as flobs (a flob is a blob that preserves the file extension).")
    (license license:expat)))

(define-public r-dbfit
  (package
    (name "r-dbfit")
    (version "2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DBfit" version))
       (sha256
        (base32 "1b5fy4xya5k31937ccjsq1gj9y39lh1vb48jfc0sr56isrx0c496"))))
    (properties `((upstream-name . "DBfit")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfit))
    (home-page "https://cran.r-project.org/package=DBfit")
    (synopsis
     "Double Bootstrap Method for Analyzing Linear Models with Autoregressive Errors")
    (description
     "Computes the double bootstrap as discussed in @code{McKnight}, @code{McKean},
and Huitema (2000) <doi:10.1037/1082-989X.5.1.87>.  The double bootstrap method
provides a better fit for a linear model with autoregressive errors than ARIMA
when the sample size is small.")
    (license license:gpl2+)))

(define-public r-dbest
  (package
    (name "r-dbest")
    (version "1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DBEST" version))
       (sha256
        (base32 "1a598g02hpfgv572gchllqkppynnsp4lx764jg0g66w3b66k0kdy"))))
    (properties `((upstream-name . "DBEST")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo))
    (home-page "https://cran.r-project.org/package=DBEST")
    (synopsis "Detecting Breakpoints and Estimating Segments in Trend")
    (description
     "This package provides a program for analyzing vegetation time series, with two
algorithms: 1) change detection algorithm that detects trend changes, determines
their type (abrupt or non-abrupt), and estimates their timing, magnitude,
number, and direction; 2) generalization algorithm that simplifies the temporal
trend into main features.  The user can set the number of major breakpoints or
magnitude of greatest changes of interest for detection, and can control the
generalization process by setting an additional parameter of
generalization-percentage.")
    (license license:gpl2)))

(define-public r-dbd
  (package
    (name "r-dbd")
    (version "0.0-22")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbd" version))
       (sha256
        (base32 "13qdm0y5dvc107xnv6663gbvmkw77150r073lp1jppf3gs8s587b"))))
    (properties `((upstream-name . "dbd")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dbd")
    (synopsis "Discretised Beta Distribution")
    (description
     "This package provides tools for working with a new versatile discrete
distribution, the db (\"discretised Beta\") distribution.  This package provides
density (probability), distribution, inverse distribution (quantile) and random
data generation functions for the db family.  It provides functions to effect
conveniently maximum likelihood estimation of parameters, and a variety of
useful plotting functions.  It provides goodness of fit tests and functions to
calculate the Fisher information, different estimates of the hessian of the log
likelihood and Monte Carlo estimation of the covariance matrix of the maximum
likelihood parameter estimates.  In addition it provides analogous tools for
working with the beta-binomial distribution which has been proposed as a
competitor to the db distribution.")
    (license license:gpl2+)))

(define-public r-dbcsp
  (package
    (name "r-dbcsp")
    (version "0.0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbcsp" version))
       (sha256
        (base32 "0faq63aqj4ddlfc5dpi8g3ngqidca6czicgvkzdyg4bj87s0kism"))))
    (properties `((upstream-name . "dbcsp")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-tsdist
                             r-plyr
                             r-paralleldist
                             r-matrix
                             r-mass
                             r-ggplot2
                             r-geigen
                             r-caret))
    (home-page "https://cran.r-project.org/package=dbcsp")
    (synopsis "Distance-Based Common Spatial Patterns")
    (description
     "This package provides a way to apply Distance-Based Common Spatial Patterns
(DB-CSP) techniques in different fields, both classical Common Spatial Patterns
(CSP) as well as DB-CSP. The method is composed of two phases: applying the
DB-CSP algorithm and performing a classification.  The main idea behind the CSP
is to use a linear transform to project data into low-dimensional subspace with
a projection matrix, in such a way that each row consists of weights for
signals.  This transformation maximizes the variance of two-class signal
matrices.The dbcsp object is created to compute the projection vectors.  For
exploratory and descriptive purpose, plot and boxplot functions can be used.
Functions train, predict and @code{selectQ} are implemented for the
classification step.")
    (license license:gpl2+)))

(define-public r-dbarts
  (package
    (name "r-dbarts")
    (version "0.9-28")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbarts" version))
       (sha256
        (base32 "0f01mk39rb7afnymi9fbaikv7hbpx2jwbzp3dd87q7hr3kpb9r6j"))))
    (properties `((upstream-name . "dbarts")))
    (build-system r-build-system)
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://github.com/vdorie/dbarts")
    (synopsis "Discrete Bayesian Additive Regression Trees Sampler")
    (description
     "Fits Bayesian additive regression trees (BART; Chipman, George, and
@code{McCulloch} (2010) <doi:10.1214/09-AOAS285>) while allowing the updating of
predictors or response so that BART can be incorporated as a conditional model
in a Gibbs/Metropolis-Hastings sampler.  Also serves as a drop-in replacement
for package @code{BayesTree}'.")
    (license license:gpl2+)))

(define-public r-dbacf
  (package
    (name "r-dbacf")
    (version "0.2.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dbacf" version))
       (sha256
        (base32 "03nrd7x2sxkyah8lpi5zawap7yhg6h2gdy0jws1jysw937l1kc50"))))
    (properties `((upstream-name . "dbacf")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix))
    (home-page "https://cran.r-project.org/package=dbacf")
    (synopsis "Autocovariance Estimation via Difference-Based Methods")
    (description
     "This package provides methods for (auto)covariance/correlation function
estimation in change point regression with stationary errors circumventing the
pre-estimation of the underlying signal of the observations.  Generic,
first-order, (m+1)-gapped, difference-based autocovariance function estimator is
based on M. Levine and I. Tecuapetla-GÃ³mez (2023)
<doi:10.48550/@code{arXiv.1905.04578>}.  Bias-reducing, second-order,
(m+1)-gapped, difference-based estimator is based on I. Tecuapetla-GÃ³mez and A.
Munk (2017) <doi:10.1111/sjos.12256>.  Robust autocovariance estimator for
change point regression with autoregressive errors is based on S. Chakar et al.
(2017) <doi:10.3150/15-BEJ782>.  It also includes a general projection-based
method for covariance matrix estimation.")
    (license license:gpl2+)))

(define-public r-daysupply
  (package
    (name "r-daysupply")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "daySupply" version))
       (sha256
        (base32 "1317g60cmqlw1wy7n7x5ifh544lzsysif6192s2k16jmgzj6cz2s"))))
    (properties `((upstream-name . "daySupply")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-magrittr r-lme4 r-dplyr))
    (home-page "https://cran.r-project.org/package=daySupply")
    (synopsis "Calculating Days' Supply and Daily Dose of Prescriptions")
    (description
     "Allows clinicians and researchers to compute daily dose (and subsequently days
supply) for prescription refills using the following methods: Fixed window,
fixed tablet, defined daily dose (DDD), and Random Effects Warfarin Days Supply
(RE@code{WarDS}).  Daily dose is the computed dose that the patient takes every
day.  For medications with fixed dosing (e.g. direct oral anticoagulants) this
is known and does not need to be estimated.  For medications with varying dose
such as warfarin, however, the daily dose should be assumed or estimated to
allow measurement of drug exposure.  Daysâ supply is the number of days that
patientsâ supply of medication will last after each prescription fill.
Estimating daysâ supply is necessary to calculate drug exposure.  The package
computes daysâ supply and daily dose at both the prescription and patient
levels.  Results at the prescription level are denoted with â-Rx-â and those
at patient level are denoted with â-Pt-â.")
    (license license:gpl3+)))

(define-public r-daymetr
  (package
    (name "r-daymetr")
    (version "1.7.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "daymetr" version))
       (sha256
        (base32 "069s7wxy2yis6x7q4faac0fcr305dxmvan7wc3fzgbix0hianvng"))))
    (properties `((upstream-name . "daymetr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-terra
                             r-sf
                             r-ncdf4
                             r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/bluegreen-labs/daymetr")
    (synopsis "Interface to the 'Daymet' Web Services")
    (description
     "Programmatic interface to the Daymet web services (<http://daymet.ornl.gov>).
Allows for easy downloads of Daymet climate data directly to your R workspace or
your computer.  Routines for both single pixel data downloads and gridded
(@code{netCDF}) data are provided.")
    (license license:agpl3)))

(define-public r-dawai
  (package
    (name "r-dawai")
    (version "1.2.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dawai" version))
       (sha256
        (base32 "0n6wb88i5p84afy2zq52pizmmgxiicm0dmfxcmmdaiq7a0p3gv3y"))))
    (properties `((upstream-name . "dawai")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-boot))
    (native-inputs (list r-r-rsp))
    (home-page "https://cran.r-project.org/package=dawai")
    (synopsis "Discriminant Analysis with Additional Information")
    (description
     "In applications it is usual that some additional information is available.  This
package dawai (an acronym for Discriminant Analysis With Additional Information)
performs linear and quadratic discriminant analysis with additional information
expressed as inequality restrictions among the populations means.  It also
computes several estimations of the true error rate.")
    (license license:gpl2+)))

(define-public r-davies
  (package
    (name "r-davies")
    (version "1.2-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Davies" version))
       (sha256
        (base32 "0n2pqipv0b1w2zjvycms0kyk7h8ps49f5jlzgyxhy9dlyr0ivaml"))))
    (properties `((upstream-name . "Davies")))
    (build-system r-build-system)
    (propagated-inputs (list r-mathjaxr))
    (home-page "https://cran.r-project.org/package=Davies")
    (synopsis "The Davies Quantile Function")
    (description "Various utilities for the Davies distribution.")
    (license license:gpl2)))

(define-public r-dauphin
  (package
    (name "r-dauphin")
    (version "0.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dauphin" version))
       (sha256
        (base32 "1cl0jipwnarkx26bhv9s1bk9q9y6ni2568xqy2w7x5nh5v38rvfx"))))
    (properties `((upstream-name . "dauphin")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dauphin")
    (synopsis "Compact Standard for Australian Phone Numbers")
    (description
     "Phone numbers are often represented as strings because there is no obvious and
suitable native representation for them.  This leads to high memory use and a
lack of standard representation.  The package provides integer representation of
Australian phone numbers with optional raw vector calling code.  The package
name is an extension of au and ph'.")
    (license license:gpl2)))

(define-public r-datrprofile
  (package
    (name "r-datrprofile")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datrProfile" version))
       (sha256
        (base32 "1bhyk3xjgwf92i765z3bkdnzkxg8fshriz9r6m371q1c75xysfil"))))
    (properties `((upstream-name . "datrProfile")))
    (build-system r-build-system)
    (propagated-inputs (list r-rsqlite r-odbc r-dplyr))
    (home-page "https://github.com/avitaliano/datrProfile")
    (synopsis "Column Profile for Tables and Datasets")
    (description
     "Profiles datasets (collecting statistics and informative summaries about that
data) on data frames and ODBC tables: maximum, minimum, mean, standard
deviation, nulls, distinct values, data patterns, data/format frequencies.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-datr
  (package
    (name "r-datr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datr" version))
       (sha256
        (base32 "0sqwhn6zdaq8i45ry207mpbda1djjaxp9mcn13hi5wkry6z0bmlr"))))
    (properties `((upstream-name . "datr")))
    (build-system r-build-system)
    (inputs (list))
    (propagated-inputs (list r-devtools))
    (home-page "https://github.com/libscie/datr")
    (synopsis "'Dat' Protocol Interface")
    (description
     "Interface with the Dat p2p network protocol <https://datproject.org>.  Clone
archives from the network, share your own files, and install packages from the
network.")
    (license license:gpl3)))

(define-public r-datplot
  (package
    (name "r-datplot")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datplot" version))
       (sha256
        (base32 "1m077srzyza7yb2n8v64y2l02kr19zjy8vvpjz7dh3hmd2sq636r"))))
    (properties `((upstream-name . "datplot")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/lsteinmann/datplot")
    (synopsis
     "Preparation of Object Dating Ranges for Density Plots (Aoristic Analysis)")
    (description
     "Converting date ranges into dating steps eases the visualization of changes in
e.g. pottery consumption, style and other variables over time.  This package
provides tools to process and prepare data for visualization and employs the
concept of aoristic analysis.")
    (license license:gpl3+)))

(define-public r-datos
  (package
    (name "r-datos")
    (version "0.5.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datos" version))
       (sha256
        (base32 "0358fshhxyws5i1bblhnhf7k42mrjn76ppy2qrvhj27kkc6i5npn"))))
    (properties `((upstream-name . "datos")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-tidyr
                             r-tibble
                             r-rlang
                             r-palmerpenguins
                             r-nycflights13
                             r-nasaweather
                             r-modeldata
                             r-lahman
                             r-ggplot2
                             r-gapminder
                             r-fueleconomy
                             r-forcats
                             r-dplyr
                             r-babynames))
    (home-page "https://github.com/cienciadedatos/datos")
    (synopsis "Traduce al EspaÃ±ol Varios Conjuntos de Datos de PrÃ¡ctica")
    (description
     "Provee una versiÃ³n traducida de los siguientes conjuntos de datos: airlines',
airports', @code{AwardsManagers}', babynames', Batting', credit_data',
diamonds', faithful', fueleconomy', Fielding', flights', gapminder', gss_cat',
iris', Managers', mpg', mtcars', atmos', palmerpenguins', People, Pitching',
planes', presidential', table1', table2', table3', table4a', table4b', table5',
vehicles', weather', who'.  English: It provides a Spanish translated version of
the datasets listed above.")
    (license license:cc0)))

(define-public r-datoramar
  (package
    (name "r-datoramar")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datoramar" version))
       (sha256
        (base32 "0zq6vhq6dmsyagmqrmb85z6fy9qhwra3s3iasr3jgc4ryr009pml"))))
    (properties `((upstream-name . "datoramar")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-jsonlite r-httr))
    (home-page "https://github.com/beigebrucewayne/datoramar")
    (synopsis "Interface to the 'Datorama' API")
    (description
     "This package provides a thin wrapper around the Datorama API. Ideal for
analyzing marketing data from <https://datorama.com>.")
    (license license:expat)))

(define-public r-dateutils
  (package
    (name "r-dateutils")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dateutils" version))
       (sha256
        (base32 "03xch5wcvv15fy9x70smrki6374lddhf0sfp0inymdsq4g8wp4bc"))))
    (properties `((upstream-name . "dateutils")))
    (build-system r-build-system)
    (propagated-inputs (list r-seasonal r-rcpparmadillo r-rcpp r-data-table))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://github.com/macroeconomicdata/dateutils")
    (synopsis "Date Utils")
    (description
     "Utilities for mixed frequency data.  In particular, use to aggregate and
normalize tabular mixed frequency data, index dates to end of period, and
seasonally adjust tabular data.")
    (license license:expat)))

(define-public r-datetoiso
  (package
    (name "r-datetoiso")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datetoiso" version))
       (sha256
        (base32 "1fg5r7ibdgbk1vbhbv6a2p4acd1mhsyyvrjr79cy37gmn1ka72i3"))))
    (properties `((upstream-name . "datetoiso")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-lubridate))
    (home-page "https://github.com/andzoluk")
    (synopsis
     "Modify Dates to ISO Standard (\"International Organization for Standardization\")")
    (description
     "Transfer any date type to ISO standard.  Package recognizes dates in given data
frame and transform to ISO format.  Only one date format can be applied within
one data frame column.")
    (license license:expat)))

(define-public r-datetimeutils
  (package
    (name "r-datetimeutils")
    (version "0.6-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datetimeutils" version))
       (sha256
        (base32 "0k8zgr3dpba967p12fygrbrcgnbm51ghhnh7cb1w1gd7jqc42nhk"))))
    (properties `((upstream-name . "datetimeutils")))
    (build-system r-build-system)
    (home-page "http://enricoschumann.net/R/packages/datetimeutils/")
    (synopsis "Utilities for Dates and Times")
    (description
     "Utilities for handling dates and times, such as selecting particular days of the
week or month, formatting timestamps as required by RSS feeds, or converting
timestamp representations of other software (such as MATLAB and Excel') to R.
The package is lightweight (no dependencies, pure R implementations) and relies
only on R's standard classes to represent dates and times ('Date and POSIXt');
it aims to provide efficient implementations, through vectorisation and the use
of R's native numeric representations of timestamps where possible.")
    (license license:gpl3)))

(define-public r-datetimerangepicker
  (package
    (name "r-datetimerangepicker")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DateTimeRangePicker" version))
       (sha256
        (base32 "1g5gjbwb1h1407bwg5yzrpal2syk5439l73svsjjzs6y55dpixsg"))))
    (properties `((upstream-name . "DateTimeRangePicker")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-reactr r-lubridate r-htmltools))
    (home-page "https://github.com/stla/DateTimeRangePicker")
    (synopsis "Datetime Range Picker Widget for Usage in 'Shiny' Applications")
    (description
     "This package provides a datetime range picker widget for usage in Shiny'.  It
creates a calendar allowing to select a start date and an end date as well as
two fields allowing to select a start time and an end time.")
    (license license:gpl3)))

(define-public r-datetimeoffset
  (package
    (name "r-datetimeoffset")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datetimeoffset" version))
       (sha256
        (base32 "11xxxfv3g8jf16cwpxjycrymx9baf8gkpd98x69djhbnrn3si0vn"))))
    (properties `((upstream-name . "datetimeoffset")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs r-purrr r-clock))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://trevorldavis.com/R/datetimeoffset/dev/")
    (synopsis
     "Datetimes with Optional UTC Offsets and/or Heterogeneous Time Zones")
    (description
     "Supports import/export for a number of datetime string standards and R datetime
classes often including lossless re-export of any original reduced precision
including ISO 8601 <https://en.wikipedia.org/wiki/ISO_8601> and pdfmark
<https://opensource.adobe.com/dc-acrobat-sdk-docs/library/pdfmark/> datetime
strings.  Supports local/global datetimes with optional UTC offsets and/or
(possibly heterogeneous) time zones with up to nanosecond precision.")
    (license license:expat)))

(define-public r-datetime
  (package
    (name "r-datetime")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datetime" version))
       (sha256
        (base32 "0nn1yxknsn3crmwbkws5kvfjhd65dw0fkfbg67gba0dyaqp1jg37"))))
    (properties `((upstream-name . "datetime")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=datetime")
    (synopsis "Nominal Dates, Times, and Durations")
    (description
     "This package provides methods for working with nominal dates, times, and
durations.  Base R has sophisticated facilities for handling time, but these can
give unexpected results if, for example, timezone is not handled properly.  This
package provides a more casual approach to support cases which do not require
rigorous treatment.  It systematically deconstructs the concepts origin and
timezone, and de-emphasizes the display of seconds.  It also converts among
nominal durations such as seconds, hours, days, and weeks.  See ?datetime and
?duration for examples.  Adapted from metrumrg
<http://r-forge.r-project.org/R/?group_id=1215>.")
    (license license:gpl3)))

(define-public r-daterangepicker
  (package
    (name "r-daterangepicker")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "daterangepicker" version))
       (sha256
        (base32 "03y8r1n31ipapfbbg12myrnqd961ra3fb6r4mjxqfkppxcj9c6mi"))))
    (properties `((upstream-name . "daterangepicker")))
    (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-jsonify r-htmltools))
    (native-inputs (list esbuild))
    (home-page "https://github.com/trafficonese/daterangepicker/")
    (synopsis "Create a Shiny Date-Range Input")
    (description
     "This package provides a Shiny Input for date-ranges, which pops up two calendars
for selecting dates, times, or predefined ranges like \"Last 30 Days\".  It wraps
the @code{JavaScript} library daterangepicker which is available at
<https://www.daterangepicker.com>.")
    (license license:expat)))

(define-public r-datefixr
  (package
    (name "r-datefixr")
    (version "1.7.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datefixR" version))
       (sha256
        (base32 "1nsfi0hjamd83icxqdx4s284jrjxp13nygxbzd9vaknfl2fv3dpi"))))
    (properties `((upstream-name . "datefixR")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-rlang r-rcpp r-lifecycle))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/datefixR/")
    (synopsis "Standardize Dates in Different Formats or with Missing Data")
    (description
     "There are many different formats dates are commonly represented with: the order
of day, month, or year can differ, different separators (\"-\", \"/\", or
whitespace) can be used, months can be numerical, names, or abbreviations and
year given as two digits or four. @code{datefixR} takes dates in all these
different formats and converts them to R's built-in date class.  If
@code{datefixR} cannot standardize a date, such as because it is too malformed,
then the user is told which date cannot be standardized and the corresponding ID
for the row. @code{datefixR} also allows the imputation of missing days and
months with user-controlled behavior.")
    (license license:gpl3+)))

(define-public r-dateback
  (package
    (name "r-dateback")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dateback" version))
       (sha256
        (base32 "0kg066kx3r0kpj10p28xbidjri6x9g7br7bjs8qq6027a3klfxfv"))))
    (properties `((upstream-name . "dateback")))
    (build-system r-build-system)
    (home-page "https://github.com/r-suzuki/dateback")
    (synopsis
     "Collect and Install R Packages on a Specified Date with Dependencies")
    (description
     "Works as a virtual CRAN snapshot for source packages.  It automatically
downloads and installs tar.gz files with dependencies, all of which were
available on a specific day.")
    (license license:expat)))

(define-public r-date
  (package
    (name "r-date")
    (version "1.2-42")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "date" version))
       (sha256
        (base32 "0x6b9dk7llvmcf2bzgdk8g1a28as0l1xxx2xn2fwyw801ab3z4as"))))
    (properties `((upstream-name . "date")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=date")
    (synopsis "Functions for Handling Dates")
    (description "This package provides functions for handling dates.")
    (license license:gpl2)))

(define-public r-datazoom-amazonia
  (package
    (name "r-datazoom-amazonia")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datazoom.amazonia" version))
       (sha256
        (base32 "1c2l42rwj67lr2910i1wdb04sqqwkdv5ycav6bz3snw349j8mycm"))))
    (properties `((upstream-name . "datazoom.amazonia")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-stringi
                             r-sidrar
                             r-sf
                             r-readxl
                             r-readr
                             r-rcpp
                             r-purrr
                             r-magrittr
                             r-janitor
                             r-hmisc
                             r-dplyr
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://www.econ.puc-rio.br/datazoom/")
    (synopsis "Simplify Access to Data from the Amazon Region")
    (description
     "This package provides functions to download and treat data regarding the
Brazilian Amazon region from a variety of official sources.")
    (license license:expat)))

(define-public r-dataviz
  (package
    (name "r-dataviz")
    (version "0.2.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DataViz" version))
       (sha256
        (base32 "1dr5nvdzc63x9ymlysvv5i8b7zcffq13pa39q0ychdwr1s3x7vzw"))))
    (properties `((upstream-name . "DataViz")))
    (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-rcpp))
    (native-inputs (list esbuild))
    (home-page "https://cran.r-project.org/package=DataViz")
    (synopsis "Data Visualisation Using an HTML Page and 'D3.js'")
    (description
     "Gives access to data visualisation methods that are relevant from the
statistician's point of view.  Using D3''s existing data visualisation tools to
empower R language and environment.  The throw chart method is a line chart used
to illustrate paired data sets (such as before-after, male-female).")
    (license license:gpl2+)))

(define-public r-datavisualizations
  (package
    (name "r-datavisualizations")
    (version "1.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DataVisualizations" version))
       (sha256
        (base32 "0y8mwgnh3cjapb97a0i4f16nrdhmkd80f6j7z0ivykgfka7jlbqr"))))
    (properties `((upstream-name . "DataVisualizations")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp
                             r-reshape2
                             r-rcpparmadillo
                             r-rcpp
                             r-pracma
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://www.deepbionics.org/")
    (synopsis "Visualizations of High-Dimensional Data")
    (description
     "Gives access to data visualisation methods that are relevant from the data
scientist's point of view.  The flagship idea of @code{DataVisualizations} is
the mirrored density plot (MD-plot) for either classified or non-classified
multivariate data published in Thrun, M.C. et al.: \"Analyzing the Fine Structure
of Distributions\" (2020), P@code{LoS} ONE, <DOI:10.1371/journal.pone.0238835>.
The MD-plot outperforms the box-and-whisker diagram (box plot), violin plot and
bean plot and geom_violin plot of ggplot2.  Furthermore, a collection of various
visualization methods for univariate data is provided.  In the case of
exploratory data analysis, @code{DataVisualizations} makes it possible to
inspect the distribution of each feature of a dataset visually through a
combination of four methods.  One of these methods is the Pareto density
estimation (PDE) of the probability density function (pdf).  Additionally,
visualizations of the distribution of distances using PDE, the scatter-density
plot using PDE for two variables as well as the Shepard density plot and the
Bland-Altman plot are presented here.  Pertaining to classified high-dimensional
data, a number of visualizations are described, such as f.ex.  the heat map and
silhouette plot.  A political map of the world or Germany can be visualized with
the additional information defined by a classification of countries or regions.
By extending the political map further, an uncomplicated function for a
Choropleth map can be used which is useful for measurements across a geographic
area.  For categorical features, the Pie charts, slope charts and fan plots,
improved by the ABC analysis, become usable.  More detailed explanations are
found in the book by Thrun, M.C.: \"Projection-Based Clustering through
Self-Organization and Swarm Intelligence\" (2018)
<DOI:10.1007/978-3-658-20540-9>.")
    (license license:gpl3)))

(define-public r-dataverse
  (package
    (name "r-dataverse")
    (version "0.3.14")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataverse" version))
       (sha256
        (base32 "0hb7d4rgwjzxg5ixx6jf3vg6s6r2aynw34lkw688f5jd9ysc706l"))))
    (properties `((upstream-name . "dataverse")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2 r-readr r-jsonlite r-httr r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://iqss.github.io/dataverse-client-r/")
    (synopsis "Client for Dataverse 4+ Repositories")
    (description
     "This package provides access to Dataverse APIs <https://dataverse.org/>
(versions 4-5), enabling data search, retrieval, and deposit.  For Dataverse
versions <= 3.0, use the archived dvn package
<https://cran.r-project.org/package=dvn>.")
    (license license:gpl2)))

(define-public r-dataverifyr
  (package
    (name "r-dataverifyr")
    (version "0.1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataverifyr" version))
       (sha256
        (base32 "1jy8hdzld8yhz632rdk3j592szp7xn3qbs2h3g0gax3p33cpcasj"))))
    (properties `((upstream-name . "dataverifyr")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml))
    (home-page "https://github.com/DavZim/dataverifyr")
    (synopsis
     "Lightweight, Flexible, and Fast Data Validation Package that Can Handle All Sizes of Data")
    (description
     "Allows you to define rules which can be used to verify a given dataset.  The
package acts as a thin wrapper around more powerful data packages such as
dplyr', data.table', arrow', and DBI ('SQL'), which do the heavy lifting.")
    (license license:expat)))

(define-public r-datasum
  (package
    (name "r-datasum")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DataSum" version))
       (sha256
        (base32 "0afz60zy1fn34hf2awizv3k0da4k2rchj2z20cy8n2g1k80sspcd"))))
    (properties `((upstream-name . "DataSum")))
    (build-system r-build-system)
    (propagated-inputs (list r-nortest r-moments r-dplyr))
    (home-page "https://github.com/Uzairkhan11w/DataSum")
    (synopsis "Comprehensive Data Summarization for Statistical Analysis")
    (description
     "Summarizing data frames by calculating various statistical measures, including
measures of central tendency, dispersion, skewness(), kurtosis(), and normality
tests.  The package leverages the moments package for calculating statistical
moments and related measures, the dplyr package for data manipulation, and the
nortest package for normality testing. @code{DataSum} includes functions such as
getmode() for finding the mode(s) of a data vector, shapiro_normality_test() for
performing the Shapiro-Wilk test (Shapiro & Wilk 1965
<doi:10.1093/biomet/52.3-4.591>) (or the Anderson-Darling test when the data
length is outside the valid range for the Shapiro-Wilk test) (Stephens 1974
<doi:10.1080/01621459.1974.10480196>), Datum() for generating a comprehensive
summary of a data vector with various statistics (including data type, sample
size, mean, mode, median, variance, standard deviation, maximum, minimum, range,
skewness(), kurtosis(), and normality test result) (Joanes & Gill 1998
<doi:10.1111/1467-9884.00122>), and @code{DataSumm}() for applying the Datum()
function to each column of a data frame.  Emphasizing the importance of
normality testing, the package provides robust tools to validate whether data
follows a normal distribution, a fundamental assumption in many statistical
analyses and models.")
    (license license:gpl3)))

(define-public r-datastudio
  (package
    (name "r-datastudio")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DATAstudio" version))
       (sha256
        (base32 "1gwm53pgab5qn0p46bxs0790n7bbfl7b66i84xsa6bb4zdw5jdzb"))))
    (properties `((upstream-name . "DATAstudio")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales r-ggplot2 r-data-table))
    (home-page "https://www.maths.ed.ac.uk/~mdecarv/")
    (synopsis "The Research Data Warehouse of Miguel de Carvalho")
    (description
     "Pulls together a collection of datasets from Miguel de Carvalho research
articles.  Including, for example: - de Carvalho (2012)
<doi:10.1016/j.jspi.2011.08.016>; - de Carvalho et al (2012)
<doi:10.1080/03610926.2012.709905>; - de Carvalho et al (2012)
<doi:10.1016/j.econlet.2011.09.007>); - de Carvalho and Davison (2014)
<doi:10.1080/01621459.2013.872651>; - de Carvalho and Rua (2017)
<doi:10.1016/j.ijforecast.2015.09.004>.")
    (license license:gpl3+)))

(define-public r-datastreamr
  (package
    (name "r-datastreamr")
    (version "2.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DatastreamR" version))
       (sha256
        (base32 "05dafwxfwyzxxwhyaxfqlhwrgpm4kysnrm1ls3fr4rkqa96z7mwv"))))
    (properties `((upstream-name . "DatastreamR")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-logger r-jsonlite r-ini r-httr))
    (home-page "https://cran.r-project.org/package=DatastreamR")
    (synopsis "Datastream API")
    (description
     "Access Datastream content through
<https://product.datastream.com/dswsclient/Docs/Default.aspx>., our historical
financial database with over 35 million individual instruments or indicators
across all major asset classes, including over 19 million active economic
indicators.  It features 120 years of data, across 175 countries â the
information you need to interpret market trends, economic cycles, and the impact
of world events.  Data spans bond indices, bonds, commodities, convertibles,
credit default swaps, derivatives, economics, energy, equities, equity indices,
ESG, estimates, exchange rates, fixed income, funds, fundamentals, interest
rates, and investment trusts.  Unique content includes I/B/E/S Estimates,
Worldscope Fundamentals, point-in-time data, and Reuters Polls.  Alongside the
content, sit a set of powerful analytical tools for exploring relationships
between different asset types, with a library of customizable analytical
functions.  In-house timeseries can also be uploaded using the package to
comingle with Datastream maintained datasets, use with these analytical tools
and displayed in Datastreamâs flexible charting facilities in Microsoft
Office.")
    (license license:gpl3+)))

(define-public r-datastreamdsws2r
  (package
    (name "r-datastreamdsws2r")
    (version "1.9.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DatastreamDSWS2R" version))
       (sha256
        (base32 "0qyd4mml2j6gk4nsy59lm7317n6g975rb9k2a1h71d7kbbh5801b"))))
    (properties `((upstream-name . "DatastreamDSWS2R")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-xts
                             r-stringr
                             r-stringi
                             r-jsonlite
                             r-httr
                             r-foreach
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=DatastreamDSWS2R")
    (synopsis "Provides a Link Between the 'LSEG Datastream' System and R")
    (description
     "This package provides a set of functions and a class to connect, extract and
upload information from the LSEG Datastream database.  This package uses the
DSWS API and server used by the Datastream DFO addin'.  Details of this API are
available at <https://www.lseg.com/en/data-analytics>.  Please report issues at
<https://github.com/@code{CharlesCara/DatastreamDSWS2R/issues>}.")
    (license license:gpl3)))

(define-public r-datastepr
  (package
    (name "r-datastepr")
    (version "0.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datastepr" version))
       (sha256
        (base32 "039yggdj8jdici7hwmkjwgix45lvwjl7rw5h2rfzsm9xaq6vw1z2"))))
    (properties `((upstream-name . "datastepr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-r6 r-magrittr r-lazyeval r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/bramtayl/datastepr")
    (synopsis "An Implementation of a SAS-Style Data Step")
    (description
     "Based on a SAS data step.  This allows for row-wise dynamic building of data,
iteratively importing slices of existing dataframes, conducting analyses, and
exporting to a results frame.  This is particularly useful for differential or
time-series analyses, which are often not well suited to vector- based
operations.")
    (license license:cc0)))

(define-public r-datassim
  (package
    (name "r-datassim")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DatAssim" version))
       (sha256
        (base32 "120gazyyxda9faydv2lyqgvflhqi2fhih1szq0sy5v1gh4xb0hhy"))))
    (properties `((upstream-name . "DatAssim")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "https://cran.r-project.org/package=DatAssim")
    (synopsis "Data Assimilation")
    (description
     "For estimation of a variable of interest using Kalman filter by incorporating
results from previous assessments, i.e.  through development weighted estimates
where weights are assigned inversely proportional to the variance of existing
and new estimates.  For reference see Ehlers et al. (2017)
<doi:10.20944/preprints201710.0098.v1>.")
    (license license:gpl2+)))

(define-public r-dataspice
  (package
    (name "r-dataspice")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataspice" version))
       (sha256
        (base32 "1pnmb7kdx9wdvi2873rw1a7hc7spsvx4lfvfhfcqwgll46j0f1wm"))))
    (properties `((upstream-name . "dataspice")))
    (build-system r-build-system)
    (propagated-inputs (list r-whisker
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-shiny
                             r-rhandsontable
                             r-readr
                             r-purrr
                             r-magrittr
                             r-jsonlite
                             r-ggplot2
                             r-fs
                             r-eml
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ropensci/dataspice")
    (synopsis "Create Lightweight Schema.org Descriptions of Data")
    (description
     "The goal of dataspice is to make it easier for researchers to create basic,
lightweight, and concise metadata files for their datasets.  These basic files
can then be used to make useful information available during analysis, create a
helpful dataset \"README\" webpage, and produce more complex metadata formats to
aid dataset discovery.  Metadata fields are based on the Schema.org and
Ecological Metadata Language standards.")
    (license license:expat)))

(define-public r-dataspacer
  (package
    (name "r-dataspacer")
    (version "0.7.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DataSpaceR" version))
       (sha256
        (base32 "1asrslqmk4sjj99x8pb01yfrw57p64zc6klrk2ghz4g44fr9d0pq"))))
    (properties `((upstream-name . "DataSpaceR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlabkey
                             r-r6
                             r-jsonlite
                             r-httr
                             r-digest
                             r-data-table
                             r-curl
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/DataSpaceR/")
    (synopsis "Interface to 'the CAVD DataSpace'")
    (description
     "This package provides a convenient API interface to access immunological data
within the CAVD @code{DataSpace'(<https://dataspace.cavd.org>}), a data sharing
and discovery tool that facilitates exploration of HIV immunological data from
pre-clinical and clinical HIV vaccine studies.")
    (license license:gpl3)))

(define-public r-datasetsuni
  (package
    (name "r-datasetsuni")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DataSetsUni" version))
       (sha256
        (base32 "0dbi0jgzh2qxwsid9yp4mdwhrm7mcksx8jvpa91qfnfc26ipdw6n"))))
    (properties `((upstream-name . "DataSetsUni")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DataSetsUni")
    (synopsis "Collection of Univariate Data Sets")
    (description
     "This package provides a collection of widely used univariate data sets of
various applied domains on applications of distribution theory.  The functions
allow researchers and practitioners to quickly, easily, and efficiently access
and use these data sets.  The data are related to different applied domains and
as follows: Bio-medical, survival analysis, medicine, reliability analysis,
hydrology, actuarial science, operational research, meteorology, extreme values,
quality control, engineering, finance, sports and economics.  The total 100 data
sets are documented along with associated references for further details and
uses.")
    (license license:gpl2+)))

(define-public r-datasetsicr
  (package
    (name "r-datasetsicr")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datasetsICR" version))
       (sha256
        (base32 "1iw8am7y6r6j21rp6r6iw1ri4c2yrgza7aw3ams4xbx6mcz3746y"))))
    (properties `((upstream-name . "datasetsICR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=datasetsICR")
    (synopsis
              "Datasets from the Book \"An Introduction to Clustering with R\"")
    (description
     "Companion to the book \"An Introduction to Clustering with R\" by P. Giordani,
M.B. Ferraro and F. Martella (Springer, Singapore, 2020).  The datasets are used
in some case studies throughout the text.")
    (license license:gpl2+)))

(define-public r-datasets-load
  (package
    (name "r-datasets-load")
    (version "2.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datasets.load" version))
       (sha256
        (base32 "1gbc4pc4gq3fgkv1ib83h08s7daim3gnkna07a2yikdsi12w95xw"))))
    (properties `((upstream-name . "datasets.load")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-miniui r-dt))
    (home-page "https://cran.r-project.org/package=datasets.load")
    (synopsis "Graphical Interface for Loading Datasets")
    (description
     "Graphical interface for loading datasets in RStudio from all installed
(including unloaded) packages, also includes command line interfaces.")
    (license license:gpl3)))

(define-public r-datasetjson
  (package
    (name "r-datasetjson")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datasetjson" version))
       (sha256
        (base32 "145al87czagdvqwnxkqi53pj9knfvfrf9a41d8byv9pkz5mz28a4"))))
    (properties `((upstream-name . "datasetjson")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonvalidate r-jsonlite))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/atorus-research/datasetjson")
    (synopsis "Read and Write CDISC Dataset JSON Files")
    (description
     "Read, construct and write CDISC (Clinical Data Interchange Standards Consortium)
Dataset JSON (@code{JavaScript} Object Notation) files, while validating per the
Dataset JSON schema file, as described in CDISC (2023)
<https://www.cdisc.org/dataset-json>.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-dataseries
  (package
    (name "r-dataseries")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataseries" version))
       (sha256
        (base32 "11wc2p5m8qbdmkpbd21lpwl28a1dpab88c3gqyrhsn0298lpnip4"))))
    (properties `((upstream-name . "dataseries")))
    (build-system r-build-system)
    (home-page "http://www.dataseries.org")
    (synopsis "Switzerland's Data Series in One Place")
    (description
     "Download and import time series from <http://www.dataseries.org>, a
comprehensive and up-to-date collection of open data from Switzerland.")
    (license license:gpl3)))

(define-public r-datasda
  (package
    (name "r-datasda")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataSDA" version))
       (sha256
        (base32 "0nf7ssk8srpmq0b2bqzm6kilj3m3dhdk7fz35vhzzkj4d2wn9czr"))))
    (properties `((upstream-name . "dataSDA")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-magrittr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dataSDA")
    (synopsis "Data Sets for Symbolic Data Analysis")
    (description
     "Collects a diverse range of symbolic data and offers a comprehensive set of
functions that facilitate the conversion of traditional data into the symbolic
data format.")
    (license license:gpl2+)))

(define-public r-datasailr
  (package
    (name "r-datasailr")
    (version "0.8.11")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datasailr" version))
       (sha256
        (base32 "0ym1aqrlglha36z883yf92rm0fydg1qsdgdy48z32yk41xbhp5iy"))))
    (properties `((upstream-name . "datasailr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://datasailr.io")
    (synopsis "Row by Row Data Processing Tool, Using 'DataSailr' Script")
    (description
     "This package provides a row by row data processing tool.  You can write data
processing code in @code{DataSailr} script which is specially intended for data
manipulation.  The package uses libsailr (C/C++ library) for its
@code{DataSailr} code parsing and its execution.")
    (license license:gpl3+)))

(define-public r-datarobot
  (package
    (name "r-datarobot")
    (version "2.18.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datarobot" version))
       (sha256
        (base32 "0ac51bs16skj808msgriwidaw3vx7cqjjarr70gy0hly3ppxwfyr"))))
    (properties `((upstream-name . "datarobot")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml r-jsonlite r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=datarobot")
    (synopsis "'DataRobot' Predictive Modeling API")
    (description
     "For working with the @code{DataRobot} predictive modeling platform's API
<https://www.datarobot.com/>.")
    (license license:expat)))

(define-public r-datarium
  (package
    (name "r-datarium")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datarium" version))
       (sha256
        (base32 "1v98yxsxhfqlalz5qy3x5axb7fy067vf3y0qg7ngixphmy9qybym"))))
    (properties `((upstream-name . "datarium")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=datarium")
    (synopsis "Data Bank for Statistical Analysis and Visualization")
    (description
     "This package contains data organized by topics: categorical data, regression
model, means comparisons, independent and repeated measures ANOVA, mixed ANOVA
and ANCOVA.")
    (license license:gpl2)))

(define-public r-dataretrieval
  (package
    (name "r-dataretrieval")
    (version "2.7.16")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataRetrieval" version))
       (sha256
        (base32 "11hwk81vyzn6jx0z3flhh7gfwmfr1irysxghsbb2sgdqdffs6vh1"))))
    (properties `((upstream-name . "dataRetrieval")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-readr
                             r-lubridate
                             r-jsonlite
                             r-httr
                             r-curl))
    (native-inputs (list r-knitr))
    (home-page "https://code.usgs.gov/water/dataRetrieval")
    (synopsis
     "Retrieval Functions for USGS and EPA Hydrology and Water Quality Data")
    (description
     "Collection of functions to help retrieve U.S. Geological Survey and U.S.
Environmental Protection Agency water quality and hydrology data from web
services.  Data are discovered from National Water Information System
<https://waterservices.usgs.gov/> and <https://waterdata.usgs.gov/nwis>.  Water
quality data are obtained from the Water Quality Portal
<https://www.waterqualitydata.us/>.")
    (license license:cc0)))

(define-public r-dataresqc
  (package
    (name "r-dataresqc")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataresqc" version))
       (sha256
        (base32 "1a4izp25bxvgq3l4m7njy13d3fl6xn8y7v2v18raqk5g8kl8ca2y"))))
    (properties `((upstream-name . "dataresqc")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dataresqc")
    (synopsis "C3S Quality Control Tools for Historical Climate Data")
    (description
     "Quality control and formatting tools developed for the Copernicus Data Rescue
Service.  The package includes functions to handle the Station Exchange Format
(SEF), various statistical tests for climate data at daily and sub-daily
resolution, as well as functions to plot the data.  For more information and
documentation see
<https://datarescue.climate.copernicus.eu/st_data-quality-control>.")
    (license license:asl2.0)))

(define-public r-datareporter
  (package
    (name "r-datareporter")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataReporter" version))
       (sha256
        (base32 "1rjm6j1s229j1j9yb5y1sdi03x22qzrkmhc09k4xdmwmwmpi3s58"))))
    (properties `((upstream-name . "dataReporter")))
    (build-system r-build-system)
    (inputs (list coreutils pandoc git))
    (propagated-inputs (list r-whoami
                             r-stringi
                             r-robustbase
                             r-rmarkdown
                             r-pander
                             r-magrittr
                             r-htmltools
                             r-haven
                             r-gridextra
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ekstroem/dataReporter")
    (synopsis
     "Reproducible Data Screening Checks and Report of Possible Errors")
    (description
     "Data screening is an important first step of any statistical analysis.
@code{dataReporter} auto generates a customizable data report with a thorough
summary of the checks and the results that a human can use to identify possible
errors.  It provides an extendable suite of test for common potential errors in
a dataset.  See Petersen AH, EkstrÃ¸m CT (2019). \"@code{dataMaid}: Your
Assistant for Documenting Supervised Data Quality Screening in R.\" _Journal of
Statistical Software_, *90*(6), 1-38 <doi:10.18637/jss.v090.i06> for more
information.")
    (license license:gpl2)))

(define-public r-datardis
  (package
    (name "r-datardis")
    (version "0.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datardis" version))
       (sha256
        (base32 "0p2cn96ydl9h7fh0cnkr0v11kjpsw9whf9zzrgy07knqiqq0da24"))))
    (properties `((upstream-name . "datardis")))
    (build-system r-build-system)
    (propagated-inputs (list r-dplyr))
    (home-page "https://cran.r-project.org/package=datardis")
    (synopsis "Data from the Doctor Who Series")
    (description "Explore data related to the Doctor Who TV series.")
    (license license:expat)))

(define-public r-dataquier
  (package
    (name "r-dataquier")
    (version "2.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataquieR" version))
       (sha256
        (base32 "1y8s6igz7ckvqamz26lrks62fnh51w1gz18gv7saxkmiwcacfjh4"))))
    (properties `((upstream-name . "dataquieR")))
    (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-withr
                             r-units
                             r-scales
                             r-robustbase
                             r-rlang
                             r-rio
                             r-readr
                             r-r-devices
                             r-qmrparser
                             r-patchwork
                             r-parallelmap
                             r-multinomialci
                             r-mass
                             r-lubridate
                             r-lme4
                             r-lifecycle
                             r-ggplot2
                             r-emmeans
                             r-dplyr))
    (native-inputs (list r-knitr esbuild))
    (home-page "https://dataquality.qihs.uni-greifswald.de/")
    (synopsis "Data Quality in Epidemiological Research")
    (description
     "Data quality assessments guided by a data quality framework introduced by
Schmidt and colleagues, 2021 <doi:10.1186/s12874-021-01252-7> target the data
quality dimensions integrity, completeness, consistency, and accuracy.  The
scope of applicable functions rests on the availability of extensive metadata
which can be provided in spreadsheet tables.  Either standardized (e.g. as html5
reports) or individually tailored reports can be generated.  For an introduction
into the specification of corresponding metadata, please refer to the package
website
<https://dataquality.qihs.uni-greifswald.de/Annotation_of_Metadata.html>.")
    (license license:bsd-2)))

(define-public r-datapreparation
  (package
    (name "r-datapreparation")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataPreparation" version))
       (sha256
        (base32 "0ck3g9hymj6i1a9nr58srm8jxbaghh5w5jg9cqbx5zp18fc0w81v"))))
    (properties `((upstream-name . "dataPreparation")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-progress r-matrix r-lubridate
                             r-data-table))
    (home-page "https://cran.r-project.org/package=dataPreparation")
    (synopsis "Automated Data Preparation")
    (description
     "Do most of the painful data preparation for a data science project with a
minimum amount of code; Take advantages of data.table efficiency and use some
algorithmic trick in order to perform data preparation in a time and RAM
efficient way.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-dataprep
  (package
    (name "r-dataprep")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataprep" version))
       (sha256
        (base32 "1v48ry6xk0qg73j6js6m6fqd1bdhjv500bndb60zzl2qifrjfk2a"))))
    (properties `((upstream-name . "dataprep")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-scales
                             r-reshape2
                             r-ggplot2
                             r-foreach
                             r-dplyr
                             r-doparallel
                             r-data-table))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://cran.r-project.org/package=dataprep")
    (synopsis "Efficient and Flexible Data Preprocessing Tools")
    (description
     "Efficiently and flexibly preprocess data using a set of data filtering,
deletion, and interpolation tools.  These data preprocessing methods are
developed based on the principles of completeness, accuracy, threshold method,
and linear interpolation and through the setting of constraint conditions, time
completion & recovery, and fast & efficient calculation and grouping.  Key
preprocessing steps include deletions of variables and observations, outlier
removal, and missing values (NA) interpolation, which are dependent on the
incomplete and dispersed degrees of raw data.  They clean data more accurately,
keep more samples, and add no outliers after interpolation, compared with
ordinary methods.  Auto-identification of consecutive NA via run-length based
grouping is used in observation deletion, outlier removal, and NA interpolation;
thus, new outliers are not generated in interpolation.  Conditional extremum is
proposed to realize point-by-point weighed outlier removal that saves
non-outliers from being removed.  Plus, time series interpolation with values to
refer to within short periods further ensures reliable interpolation.  These
methods are based on and improved from the reference: Liang, C.-S., Wu, H., Li,
H.-Y., Zhang, Q., Li, Z. & He, K.-B. (2020)
<doi:10.1016/j.scitotenv.2020.140923>.")
    (license license:gpl2+)))

(define-public r-datapasta
  (package
    (name "r-datapasta")
    (version "3.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datapasta" version))
       (sha256
        (base32 "0sqv29iv2rv50rbw1601rn8p7gv7rsw00djhl7h1znr0igzi5b82"))))
    (properties `((upstream-name . "datapasta")))
    (build-system r-build-system)
    (propagated-inputs (list r-rstudioapi r-readr r-clipr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/milesmcbain/datapasta")
    (synopsis "R Tools for Data Copy-Pasta")
    (description
     "RStudio addins and R functions that make copy-pasting vectors and tables to text
painless.")
    (license license:expat)))

(define-public r-datapackager
  (package
    (name "r-datapackager")
    (version "0.16.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DataPackageR" version))
       (sha256
        (base32 "0hq45yyfcw87p93qrivyx341hsamfx4m3bs1ii97h35mb4926k86"))))
    (properties `((upstream-name . "DataPackageR")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-usethis
                             r-rprojroot
                             r-roxygen2
                             r-rmarkdown
                             r-pkgload
                             r-pkgbuild
                             r-knitr
                             r-futile-logger
                             r-digest
                             r-desc
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ropensci/DataPackageR")
    (synopsis "Construct Reproducible Analytic Data Sets as R Packages")
    (description
     "This package provides a framework to help construct R data packages in a
reproducible manner.  Potentially time consuming processing of raw data sets
into analysis ready data sets is done in a reproducible manner and decoupled
from the usual R CMD build process so that data sets can be processed into R
objects in the data package and the data package can then be shared, built, and
installed by others without the need to repeat computationally costly data
processing.  The package maintains data provenance by turning the data
processing scripts into package vignettes, as well as enforcing documentation
and version checking of included data objects.  Data packages can be version
controlled on @code{GitHub}', and used to share data for manuscripts,
collaboration and reproducible research.")
    (license license:expat)))

(define-public r-datapack
  (package
    (name "r-datapack")
    (version "1.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datapack" version))
       (sha256
        (base32 "14vlcgk5sckzkc15cjvrbs113y65rqlwm1az7nsvnsqfx4x76jb1"))))
    (properties `((upstream-name . "datapack")))
    (build-system r-build-system)
    (propagated-inputs (list r-zip
                             r-xml
                             r-uuid
                             r-redland
                             r-fs
                             r-digest))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/datapack/")
    (synopsis
     "Flexible Container to Transport and Manipulate Data and Associated Resources")
    (description
     "This package provides a flexible container to transport and manipulate complex
sets of data.  These data may consist of multiple data files and associated meta
data and ancillary files.  Individual data objects have associated system level
meta data, and data files are linked together using the OAI-ORE standard
resource map which describes the relationships between the files.  The OAI- ORE
standard is described at <https://www.openarchives.org/ore/>.  Data packages can
be serialized and transported as structured files that have been created
following the @code{BagIt} specification.  The @code{BagIt} specification is
described at <https://tools.ietf.org/html/draft-kunze-bagit-08>.")
    (license license:asl2.0)))

(define-public r-dataone
  (package
    (name "r-dataone")
    (version "2.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataone" version))
       (sha256
        (base32 "0509dmvf3kgk15cjbz3m9fzanbdpa5r0rz921m776a4bsjsilv4i"))))
    (properties `((upstream-name . "dataone")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml
                             r-uuid
                             r-stringr
                             r-stringi
                             r-plyr
                             r-parsedate
                             r-jsonlite
                             r-httr
                             r-datapack
                             r-base64enc))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/DataONEorg/rdataone")
    (synopsis "R Interface to the DataONE REST API")
    (description
     "This package provides read and write access to data and metadata from the
@code{DataONE} network <https://www.dataone.org> of data repositories.  Each
@code{DataONE} repository implements a consistent repository application
programming interface.  Users call methods in R to access these remote
repository functions, such as methods to query the metadata catalog, get access
to metadata for particular data packages, and read the data objects from the
data repository.  Users can also insert and update data objects on repositories
that support these methods.")
    (license license:asl2.0)))

(define-public r-dataonderivatives
  (package
    (name "r-dataonderivatives")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataonderivatives" version))
       (sha256
        (base32 "0bp1ynarz70c2clsz60dqfd4vmgm3251jv6821db5n7fffdrr7qa"))))
    (properties `((upstream-name . "dataonderivatives")))
    (build-system r-build-system)
    (propagated-inputs (list r-vetr r-tibble r-readr r-httr2))
    (home-page "https://github.com/imanuelcostigan/dataonderivatives")
    (synopsis "Easily Source Publicly Available Data on Derivatives")
    (description
     "Post Global Financial Crisis derivatives reforms have lifted the veil off
over-the-counter (OTC) derivative markets.  Swap Execution Facilities (SEFs) and
Swap Data Repositories (SDRs) now publish data on swaps that are traded on or
reported to those facilities (respectively).  This package provides you the
ability to get this data from supported sources.")
    (license license:gpl2)))

(define-public r-datanugget
  (package
    (name "r-datanugget")
    (version "1.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datanugget" version))
       (sha256
        (base32 "13y0plgkjnis7xmswqr5gmyygm7137kscbdkamfmahbw1qbi097i"))))
    (properties `((upstream-name . "datanugget")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfast r-foreach r-dosnow))
    (home-page "https://cran.r-project.org/package=datanugget")
    (synopsis "Create, and Refine Data Nuggets")
    (description
     "Creating, and refining data nuggets.  Data nuggets reduce a large dataset into a
small collection of nuggets of data, each containing a center (location), weight
(importance), and scale (variability) parameter.  Data nugget centers are
created by choosing observations in the dataset which are as equally spaced
apart as possible.  Data nugget weights are created by counting the number
observations closest to a given data nugget center.  We then say the data nugget
contains these observations and the data nugget center is recalculated as the
mean of these observations.  Data nugget scales are created by calculating the
trace of the covariance matrix of the observations contained within a data
nugget divided by the dimension of the dataset.  Data nuggets are refined by
splitting data nuggets which have scales or shapes (defined as the ratio of the
two largest eigenvalues of the covariance matrix of the observations contained
within the data nugget) Reference paper: [1] Beavers, T. E., Cheng, G., Duan,
Y., Cabrera, J., Lubomirski, M., Amaratunga, D., & Teigler, J. E. (2024).  Data
Nuggets: A Method for Reducing Big Data While Preserving Data Structure.
Journal of Computational and Graphical Statistics, 1-21. [2] Cherasia, K. E.,
Cabrera, J., Fernholz, L. T., & Fernholz, R. (2022).  Data Nuggets in Supervised
Learning. \\emph{In Robust and Multivariate Statistical Methods: Festschrift in
Honor of David E. Tyler} (pp.  429-449).  Cham: Springer International
Publishing.")
    (license license:gpl2)))

(define-public r-datana
  (package
    (name "r-datana")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datana" version))
       (sha256
        (base32 "1dxcx9hrw7z8iizgn3bh6mg512pbf37ncyzwh67zc4jcydlm0p3p"))))
    (properties `((upstream-name . "datana")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2))
    (home-page "https://eljatib.com/rlibro")
    (synopsis "Datasets and Functions to Accompany Analisis De Datos Con R")
    (description
     "Datasets and functions to accompany the book Analisis de datos con el programa
estadistico R: una introduccion aplicada by Salas-Eljatib (2021, ISBN:
9789566086109).  The package helps carry out data management, exploratory
analyses, and model fitting.")
    (license license:gpl3)))

(define-public r-datamojo
  (package
    (name "r-datamojo")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataMojo" version))
       (sha256
        (base32 "0cp4zj85jczm42vm046n0rqmlrllj2r0jv1003h10isamffp59ig"))))
    (properties `((upstream-name . "dataMojo")))
    (build-system r-build-system)
    (propagated-inputs (list r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dataMojo")
    (synopsis "Reshape Data Table")
    (description
     "This package provides a grammar of data manipulation with data.table', providing
a consistent a series of utility functions that help you solve the most common
data manipulation challenges.")
    (license license:expat)))

(define-public r-datamods
  (package
    (name "r-datamods")
    (version "1.5.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datamods" version))
       (sha256
        (base32 "1f516wh3jrpwb4xv5wwghlk1j8q4p9yrwc1d7b99z9f0kpy83i8j"))))
    (properties `((upstream-name . "datamods")))
    (build-system r-build-system)
    (propagated-inputs (list r-writexl
                             r-toastui
                             r-tibble
                             r-shinywidgets
                             r-shinybusy
                             r-shiny
                             r-rlang
                             r-rio
                             r-readxl
                             r-reactable
                             r-phosphoricons
                             r-htmltools
                             r-data-table
                             r-classint
                             r-bslib))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/dreamRs/datamods")
    (synopsis "Modules to Import and Manipulate Data in 'Shiny'")
    (description
     "Shiny modules to import data into an application or addin from various sources,
and to manipulate them after that.")
    (license license:gpl3)))

(define-public r-datametprocess
  (package
    (name "r-datametprocess")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DataMetProcess" version))
       (sha256
        (base32 "0xg0g6rj46m99gkk3xp7h0la96hzp2ykli2pq7aim9fdjgzqyz05"))))
    (properties `((upstream-name . "DataMetProcess")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-shiny r-rlang r-lubridate r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/wagnnerms97/DataMetProcess")
    (synopsis "Meteorological Data Processing")
    (description
     "Set of tools aimed at processing meteorological data, converting hourly recorded
data to daily, monthly and annual data.")
    (license license:gpl3)))

(define-public r-datameta
  (package
    (name "r-datameta")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataMeta" version))
       (sha256
        (base32 "13xxayqxbps07h0xr5b7sb7q30gy5zm7jzzaq4k20fskkjrzhzcm"))))
    (properties `((upstream-name . "dataMeta")))
    (build-system r-build-system)
    (propagated-inputs (list r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/dmrodz/dataMeta")
    (synopsis "Create and Append a Data Dictionary for an R Dataset")
    (description
     "Designed to create a basic data dictionary and append to the original dataset's
attributes list.  The package makes use of a tidy dataset and creates a data
frame that will serve as a linker that will aid in building the dictionary.  The
dictionary is then appended to the list of the original dataset's attributes.
The user will have the option of entering variable and item descriptions by
writing code or use alternate functions that will prompt the user to add these.")
    (license license:gpl3)))

(define-public r-datamaid
  (package
    (name "r-datamaid")
    (version "1.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataMaid" version))
       (sha256
        (base32 "06jywq3llwafjnpklqimra456crdi752zxci6z1w0v7p8blf4vjw"))))
    (properties `((upstream-name . "dataMaid")))
    (build-system r-build-system)
    (inputs (list coreutils pandoc git))
    (propagated-inputs (list r-whoami
                             r-stringi
                             r-robustbase
                             r-rmarkdown
                             r-pander
                             r-magrittr
                             r-htmltools
                             r-haven
                             r-gridextra
                             r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ekstroem/dataMaid")
    (synopsis
     "Suite of Checks for Identification of Potential Errors in a Data Frame as Part of the Data Screening Process")
    (description
     "Data screening is an important first step of any statistical analysis.
@code{dataMaid} auto generates a customizable data report with a thorough
summary of the checks and the results that a human can use to identify possible
errors.  It provides an extendable suite of test for common potential errors in
a dataset.")
    (license license:gpl2)))

(define-public r-dataloader
  (package
    (name "r-dataloader")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DataLoader" version))
       (sha256
        (base32 "18mih6mb95v5xjvmqwby2mma74fcxwyqdm5w8j3bhi4iwgfn6d7v"))))
    (properties `((upstream-name . "DataLoader")))
    (build-system r-build-system)
    (propagated-inputs (list r-xlsx r-readxl r-rchoicedialogs r-plyr))
    (home-page "https://cran.r-project.org/package=DataLoader")
    (synopsis "Import Multiple File Types")
    (description
     "This package provides functions to import multiple files of multiple data file
types ('.xlsx', .xls', .csv', .txt') from a given directory into R data frames.")
    (license license:gpl2+)))

(define-public r-datagraph
  (package
    (name "r-datagraph")
    (version "1.2.14")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DataGraph" version))
       (sha256
        (base32 "1vj008c6l1k738kp8f9vmwm6b9jnyjgix389nqgbfq8ia98qgz0k"))))
    (properties `((upstream-name . "DataGraph")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (home-page "https://cran.r-project.org/package=DataGraph")
    (synopsis "Export Data from 'R' to 'DataGraph'")
    (description
     "This package provides functions to pipe data from R to @code{DataGraph}', a
graphing and analysis application for mac OS. Create a live connection using
either .dtable or .dtbin files that can be read by @code{DataGraph}'.  Can save
a data frame, collection of data frames and sequences of data frames and
individual vectors.  For more information see
<https://community.visualdatatools.com/datagraph/knowledge-base/r-package/>.")
    (license license:gpl2+)))

(define-public r-datagovsgr
  (package
    (name "r-datagovsgr")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datagovsgR" version))
       (sha256
        (base32 "1z3zrvz9dc9a06kp8agrgvx1l6g5hq2cmmn6xpabp68pkw4jdpc6"))))
    (properties `((upstream-name . "datagovsgR")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-purrr r-httr r-dplyr r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=datagovsgR")
    (synopsis "Call Real Time APIs from Data Gov Singapore")
    (description
     "This package provides a wrapper for the Data.gov.sg developer resources, which
provide real time and historical information, ranging from carpark availability
to weather forecasts.  The functions makes the API calls for a given date and
time, before returning the relevant information in a data frame.  All APIs are
supported, less the IPOS one which is not returning any data.  Relevant
information can be found here <https://data.gov.sg/developer>.")
    (license license:expat)))

(define-public r-datafsm
  (package
    (name "r-datafsm")
    (version "0.2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datafsm" version))
       (sha256
        (base32 "0klhkbwpaqxk2mnxha8b03mpgfxk107ff9d2nx6cky59il3c1825"))))
    (properties `((upstream-name . "datafsm")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-ga r-caret))
    (native-inputs (list r-knitr))
    (home-page "https://jonathan-g.github.io/datafsm/")
    (synopsis "Estimating Finite State Machine Models from Data")
    (description
     "Automatic generation of finite state machine models of dynamic decision-making
that both have strong predictive power and are interpretable in human terms.  We
use an efficient model representation and a genetic algorithm-based estimation
process to generate simple deterministic approximations that explain most of the
structure of complex stochastic processes.  We have applied the software to
empirical data, and demonstrated it's ability to recover known data-generating
processes by simulating data with agent-based models and correctly deriving the
underlying decision models for multiple agent models and degrees of
stochasticity.")
    (license license:expat)))

(define-public r-dataframeexplorer
  (package
    (name "r-dataframeexplorer")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataframeexplorer" version))
       (sha256
        (base32 "0g5ajvd81k5pamvn204rxaiw92k20qqffnia1g6z89lp73spxs0s"))))
    (properties `((upstream-name . "dataframeexplorer")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-plyr
                             r-openxlsx
                             r-magrittr
                             r-dplyr
                             r-data-table))
    (home-page "https://cran.r-project.org/package=dataframeexplorer")
    (synopsis "Familiarity with Dataframes Before Data Manipulation")
    (description
     "Real life data is muddy, fuzzy and unpredictable.  This makes data manipulations
tedious and bringing the data to right shape alone is a major chunk of work.
Functions in this package help us get an understanding of dataframes to
dramatically reduces data coding time.")
    (license license:expat)))

(define-public r-datafaker
  (package
    (name "r-datafaker")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DataFakeR" version))
       (sha256
        (base32 "1a25qp627n76qi4xzj62ipiy3qs2qvajcy9inzibwymryizlr0ia"))))
    (properties `((upstream-name . "DataFakeR")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-tidygraph
                             r-tibble
                             r-r6
                             r-purrr
                             r-magrittr
                             r-glue
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/openpharma/DataFakeR")
    (synopsis "Generate Fake Data for Relational Databases")
    (description
     "Based on provided database description and/or database connection generate data
sample preserving source structure.")
    (license license:expat)))

(define-public r-dataexplorer
  (package
    (name "r-dataexplorer")
    (version "0.8.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DataExplorer" version))
       (sha256
        (base32 "11a0b6jrvf81sa0a8595q48j66qky4xya3mvr3vr41vj0k98p90y"))))
    (properties `((upstream-name . "DataExplorer")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales
                             r-rmarkdown
                             r-reshape2
                             r-networkd3
                             r-gridextra
                             r-ggplot2
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "http://boxuancui.github.io/DataExplorer/")
    (synopsis "Automate Data Exploration and Treatment")
    (description
     "Automated data exploration process for analytic tasks and predictive modeling,
so that users could focus on understanding data and extracting insights.  The
package scans and analyzes each variable, and visualizes them with typical
graphical techniques.  Common data processing methods are also available to
treat and format data.")
    (license license:expat)))

(define-public r-dataeditr
  (package
    (name "r-dataeditr")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DataEditR" version))
       (sha256
        (base32 "0kwjgr6kaai42mhcljjs6i93m966x45gic5jgqsrkgfwjmmgf043"))))
    (properties `((upstream-name . "DataEditR")))
    (build-system r-build-system)
    (propagated-inputs (list r-shinyjs
                             r-shinybs
                             r-shiny
                             r-rstudioapi
                             r-rhandsontable
                             r-miniui
                             r-htmltools
                             r-bslib))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/DillonHammill/DataEditR")
    (synopsis
     "An Interactive Editor for Viewing, Entering, Filtering & Editing Data")
    (description
     "An interactive editor built on rhandsontable to allow the interactive viewing,
entering, filtering and editing of data in R
<https://dillonhammill.github.io/@code{DataEditR/>}.")
    (license license:gpl2)))

(define-public r-datadriftr
  (package
    (name "r-datadriftr")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datadriftR" version))
       (sha256
        (base32 "0ggakc73kyhnw60wvlb4pa7j6fvxcl98bbii45z2rrggbcgdjrfr"))))
    (properties `((upstream-name . "datadriftR")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6))
    (home-page "https://github.com/ugurdar/datadriftR")
    (synopsis "Concept Drift Detection Methods for Stream Data")
    (description
     "This package provides a system designed for detecting concept drift in streaming
datasets.  It offers a comprehensive suite of statistical methods to detect
concept drift, including methods for monitoring changes in data distributions
over time.  The package supports several tests, such as Drift Detection Method
(DDM), Early Drift Detection Method (EDDM), Hoeffding Drift Detection Methods
(HDDM_A, HDDM_W), Kolmogorov-Smirnov test-based Windowing (KSWIN) and Page
Hinkley (PH) tests.  The methods implemented in this package are based on
established research and have been demonstrated to be effective in real-time
data analysis.  For more details on the methods, please check to the following
sources.  Gama et al. (2004) <doi:10.1007/978-3-540-28645-5_29>, Baena-Garcia et
al. (2006)
<https://www.researchgate.net/publication/245999704_Early_Drift_Detection_Method>,
FrÃ­as-Blanco et al. (2014) <https://ieeexplore.ieee.org/document/6871418>, Raab
et al. (2020) <doi:10.1016/j.neucom.2019.11.111>, Page (1954)
<doi:10.1093/biomet/41.1-2.100>, Montiel et al. (2018)
<https://jmlr.org/papers/volume19/18-251/18-251.pdf>.")
    (license license:gpl2+)))

(define-public r-datadogr
  (package
    (name "r-datadogr")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datadogr" version))
       (sha256
        (base32 "10zbxb9gkymw78ras9y4wrifz7cxh3y630yzjcf9ds2p557vcjzp"))))
    (properties `((upstream-name . "datadogr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-purrr
                             r-lubridate
                             r-httr
                             r-glue
                             r-dplyr
                             r-anytime))
    (home-page "https://yutannihilation.github.io/K9")
    (synopsis "R Client for 'Datadog' API")
    (description
     "Query for metrics from Datadog (<https://www.datadoghq.com/>) via its API.")
    (license license:expat)))

(define-public r-datadictionary
  (package
    (name "r-datadictionary")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datadictionary" version))
       (sha256
        (base32 "102ll25mi4ac1zkvvirk7k11hqpf9q9h2if1rkz93zlfms843hp7"))))
    (properties `((upstream-name . "datadictionary")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-openxlsx
                             r-magrittr
                             r-lubridate
                             r-labelled
                             r-haven
                             r-dplyr
                             r-data-table
                             r-chron))
    (home-page "https://cran.r-project.org/package=datadictionary")
    (synopsis "Create a Data Dictionary")
    (description
     "This package creates a data dictionary from any dataframe or tibble in your R
environment.  You can opt to add variable labels.  You can write the object
directly to Excel.")
    (license license:expat)))

(define-public r-datacutr
  (package
    (name "r-datacutr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datacutr" version))
       (sha256
        (base32 "1qgmc2r1g5zlvfq84qrmmfp6dv3458zhv741aa5wf1nkw2sv656y"))))
    (properties `((upstream-name . "datacutr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-lubridate
                             r-dplyr
                             r-assertthat
                             r-admiraldev))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=datacutr")
    (synopsis "SDTM Datacut")
    (description
     "Supports the process of applying a cut to Standard Data Tabulation Model (SDTM),
as part of the analysis of specific points in time of the data, normally as part
of investigation into clinical trials.  The functions support different
approaches of cutting to the different domains of SDTM normally observed.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-datacomparer
  (package
    (name "r-datacomparer")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataCompareR" version))
       (sha256
        (base32 "1rapnlbi43z4sx4rq3fp8kpqhdj4g02fi3xglldbdp0c59f9vacg"))))
    (properties `((upstream-name . "dataCompareR")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi r-markdown r-knitr r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/capitalone/dataCompareR")
    (synopsis "Compare Two Data Frames and Summarise the Difference")
    (description
     "Easy comparison of two tabular data objects in R. Specifically designed to show
differences between two sets of data in a useful way that should make it easier
to understand the differences, and if necessary, help you work out how to remedy
them.  Aims to offer a more useful output than all.equal() when your two data
sets do not match, but isn't intended to replace all.equal() as a way to test
for equality.")
    (license (list license:asl2.0
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-datacombine
  (package
    (name "r-datacombine")
    (version "0.2.21")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DataCombine" version))
       (sha256
        (base32 "0iwb4726bk0cjhay694dp43b1553yyk9lpxbncs85kz229b26arm"))))
    (properties `((upstream-name . "DataCombine")))
    (build-system r-build-system)
    (propagated-inputs (list r-dplyr r-data-table))
    (home-page "http://CRAN.R-project.org/package=DataCombine")
    (synopsis "Tools for Easily Combining and Cleaning Data Sets")
    (description
     "This package provides tools for combining and cleaning data sets, particularly
with grouped and time series data.")
    (license license:gpl3+)))

(define-public r-datacleanr
  (package
    (name "r-datacleanr")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "datacleanr" version))
       (sha256
        (base32 "0mrfqm3lgb6sl2j35sfd00gb5121j9wmlff8k0vczr3sgmqz4dg8"))))
    (properties `((upstream-name . "datacleanr")))
    (build-system r-build-system)
    (propagated-inputs (list r-summarytools
                             r-shinywidgets
                             r-shinyfiles
                             r-shiny
                             r-rstudioapi
                             r-rlang
                             r-rcolorbrewer
                             r-purrr
                             r-plotly
                             r-magrittr
                             r-lubridate
                             r-htmlwidgets
                             r-htmltools
                             r-glue
                             r-fs
                             r-formatr
                             r-dt
                             r-dplyr
                             r-clipr
                             r-bslib))
    (home-page "https://github.com/the-Hull/datacleanr")
    (synopsis "Interactive and Reproducible Data Cleaning")
    (description
     "Flexible and efficient cleaning of data with interactivity.  datacleanr
facilitates best practices in data analyses and reproducibility with built-in
features and by translating interactive/manual operations to code.  The package
is designed for interoperability, and so seamlessly fits into reproducible
analyses pipelines in R'.")
    (license license:gpl3)))

(define-public r-dataclean
  (package
    (name "r-dataclean")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DataClean" version))
       (sha256
        (base32 "0wkafjyp6c2mx7g1bpz2pbxyl5nm2wba2hly8miizv0fdc762za5"))))
    (properties `((upstream-name . "DataClean")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml r-xlsx))
    (home-page "https://cran.r-project.org/package=DataClean")
    (synopsis "Data Cleaning")
    (description
     "Includes functions that researchers or practitioners may use to clean raw data,
transferring html, xlsx, txt data file into other formats.  And it also can be
used to manipulate text variables, extract numeric variables from text variables
and other variable cleaning processes.  It is originated from a author's project
which focuses on creative performance in online education environment.  The
resulting paper of that study will be published soon.")
    (license license:gpl3)))

(define-public r-dataclass
  (package
    (name "r-dataclass")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dataclass" version))
       (sha256
        (base32 "1mx2yqxahsqdxp238q1i285q9g9mcvlfi6prchgk3cydqmqshrhy"))))
    (properties `((upstream-name . "dataclass")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-lifecycle
                             r-glue
                             r-dplyr
                             r-cli))
    (home-page "https://cran.r-project.org/package=dataclass")
    (synopsis
     "Easily Create Structured Lists or Data Frames with Input Validation")
    (description
     "Easily define templates for lists and data frames that validate each element.
Specify the expected type (i.e., character, numeric, etc), expected length,
minimum and maximum values, allowable values, and more for each element in your
data.  Decide whether violations of these expectations should throw an error or
a warning.  This package is useful for validating data within R processes which
pull from dynamic data sources such as databases and web APIs to provide an
extra layer of validation around input and output data.")
    (license license:expat)))

(define-public r-databraryr
  (package
    (name "r-databraryr")
    (version "0.6.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "databraryr" version))
       (sha256
        (base32 "0mws4jw81l91cml8fh4n244nzjrfznsg05vsqfbyc75ciqlmw8hk"))))
    (properties `((upstream-name . "databraryr")))
    (build-system r-build-system)
    (propagated-inputs (list r-xfun
                             r-tibble
                             r-stringr
                             r-purrr
                             r-options
                             r-magrittr
                             r-magick
                             r-lifecycle
                             r-keyring
                             r-httr2
                             r-getpass
                             r-dplyr
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://databrary.github.io/databraryr/")
    (synopsis "Interact with the 'Databrary.org' API")
    (description
     "Databrary.org is a restricted access repository for research data, especially
video and audio.  This package provides commands to interact with the data
stored on Databrary.org'.")
    (license license:expat)))

(define-public r-databionicswarm
  (package
    (name "r-databionicswarm")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DatabionicSwarm" version))
       (sha256
        (base32 "1z5amn9b5pgnp58chlqcmz82sdvkmv1682vfy965kh53187gfn20"))))
    (properties `((upstream-name . "DatabionicSwarm")))
    (build-system r-build-system)
    (inputs (list pandoc))
    (propagated-inputs (list r-rcppparallel
                             r-rcpparmadillo
                             r-rcpp
                             r-ggplot2
                             r-generalizedumatrix
                             r-deldir
                             r-abcanalysis))
    (native-inputs (list r-knitr))
    (home-page "https://www.deepbionics.org/")
    (synopsis "Swarm Intelligence for Self-Organized Clustering")
    (description
     "Algorithms implementing populations of agents that interact with one another and
sense their environment may exhibit emergent behavior such as self-organization
and swarm intelligence.  Here, a swarm system called Databionic swarm (DBS) is
introduced which was published in Thrun, M.C., Ultsch A.: \"Swarm Intelligence
for Self-Organized Clustering\" (2020), Artificial Intelligence,
<DOI:10.1016/j.artint.2020.103237>.  DBS is able to adapt itself to structures
of high-dimensional data such as natural clusters characterized by distance
and/or density based structures in the data space.  The first module is the
parameter-free projection method called Pswarm (Pswarm()), which exploits the
concepts of self-organization and emergence, game theory, swarm intelligence and
symmetry considerations.  The second module is the parameter-free
high-dimensional data visualization technique, which generates projected points
on the topographic map with hypsometric tints defined by the generalized
U-matrix (@code{GeneratePswarmVisualization}()).  The third module is the
clustering method itself with non-critical parameters (DBSclustering()).
Clustering can be verified by the visualization and vice versa.  The term DBS
refers to the method as a whole.  It enables even a non-professional in the
field of data mining to apply its algorithms for visualization and/or clustering
to data sets with completely different structures drawn from diverse research
fields.  The comparison to common projection methods can be found in the book of
Thrun, M.C.: \"Projection Based Clustering through Self-Organization and Swarm
Intelligence\" (2018) <DOI:10.1007/978-3-658-20540-9>.")
    (license license:gpl3)))

(define-public r-databaseconnectorjars
  (package
    (name "r-databaseconnectorjars")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DatabaseConnectorJars" version))
       (sha256
        (base32 "18m6ynj30r5xdy51b3s39h0jcz1k2wgka888skr6ds2233lhqk2w"))))
    (properties `((upstream-name . "DatabaseConnectorJars")))
    (build-system r-build-system)
    (propagated-inputs (list r-rjava))
    (home-page "https://github.com/OHDSI/DatabaseConnectorJars")
    (synopsis "JAR Dependencies for the 'DatabaseConnector' Package")
    (description
     "This package provides external JAR dependencies for the @code{DatabaseConnector}
package.")
    (license (license:fsdg-compatible "Apache License"))))

(define-public r-databaseconnector
  (package
    (name "r-databaseconnector")
    (version "6.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DatabaseConnector" version))
       (sha256
        (base32 "1wl78a2jlyqdbdkq1bhw2ymv6d0dn6d38vym80khhclial76rnzp"))))
    (properties `((upstream-name . "DatabaseConnector")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (propagated-inputs (list r-urltools
                             r-stringr
                             r-sqlrender
                             r-rlang
                             r-rjava
                             r-readr
                             r-digest
                             r-dbplyr
                             r-dbi
                             r-checkmate
                             r-bit64))
    (native-inputs (list r-knitr))
    (home-page "https://ohdsi.github.io/DatabaseConnector/")
    (synopsis "Connecting to Various Database Platforms")
    (description
     "An R @code{DataBase} Interface ('DBI') compatible interface to various database
platforms ('@code{PostgreSQL}', Oracle', Microsoft SQL Server', Amazon
Redshift', Microsoft Parallel Database Warehouse', IBM Netezza', Apache Impala',
Google @code{BigQuery}', Snowflake', Spark', and SQLite').  Also includes
support for fetching data as Andromeda objects.  Uses either Java Database
Connectivity ('JDBC') or other DBI drivers to connect to databases.")
    (license (license:fsdg-compatible "Apache License"))))

(define-public r-data360r
  (package
    (name "r-data360r")
    (version "1.0.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "data360r" version))
       (sha256
        (base32 "15934ixmzw3iyqazhlz6s5cimmasf062fc8al0wdyij1f4cjcgny"))))
    (properties `((upstream-name . "data360r")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2 r-jsonlite r-data-table))
    (home-page "https://github.com/mrpsonglao/data360r")
    (synopsis "Wrapper for 'TCdata360' and 'Govdata360' API")
    (description
     "Makes it easy to engage with the Application Program Interface (API) of the
TCdata360 and Govdata360 platforms at <https://tcdata360.worldbank.org/> and
<https://govdata360.worldbank.org/>, respectively.  These application program
interfaces provide access to over 5000 trade, competitiveness, and governance
indicator data, metadata, and related information from sources both inside and
outside the World Bank Group.  Package functions include easier download of data
sets, metadata, and related information, as well as searching based on
user-inputted query.")
    (license license:expat)))

(define-public r-data-validator
  (package
    (name "r-data-validator")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "data.validator" version))
       (sha256
        (base32 "118crpyyp2szj0l3rsqmzi1cpcv45lwlvczp25f28z1lgcx6mgcx"))))
    (properties `((upstream-name . "data.validator")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-shiny-semantic
                             r-rmarkdown
                             r-rlang
                             r-r6
                             r-purrr
                             r-knitr
                             r-htmlwidgets
                             r-htmltools
                             r-dplyr
                             r-assertr))
    (home-page "https://appsilon.github.io/data.validator/")
    (synopsis "Automatic Data Validation and Reporting")
    (description
     "Validate dataset by columns and rows using convenient predicates inspired by
assertr package.  Generate good looking HTML report or print console output to
display in logs of your data processing pipeline.")
    (license license:expat)))

(define-public r-data-table-threads
  (package
    (name "r-data-table-threads")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "data.table.threads" version))
       (sha256
        (base32 "0mcma4386vg8zzqnhk80fny9z8dimpp6q89cv6ga29z39nq2iq5b"))))
    (properties `((upstream-name . "data.table.threads")))
    (build-system r-build-system)
    (propagated-inputs (list r-microbenchmark r-ggplot2 r-data-table))
    (home-page "https://github.com/Anirban166/data.table.threads")
    (synopsis "Analyze Multi-Threading Performance for 'data.table' Functions")
    (description
     "Assists in finding the most suitable thread count for the various data.table
routines that support parallel processing.")
    (license license:expat)))

(define-public r-dat
  (package
    (name "r-dat")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dat" version))
       (sha256
        (base32 "1d3q4bang6pm06rfzh6h947xy3wwqn3l6ri0h4hzklg5pzwpsajd"))))
    (properties `((upstream-name . "dat")))
    (build-system r-build-system)
    (propagated-inputs (list r-progress r-magrittr r-formula r-data-table
                             r-aoos))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=dat")
    (synopsis "Tools for Data Manipulation")
    (description
     "An implementation of common higher order functions with syntactic sugar for
anonymous function.  Provides also a link to dplyr and data.table for common
transformations on data frames to work around non standard evaluation by
default.")
    (license license:expat)))

(define-public r-dasst
  (package
    (name "r-dasst")
    (version "0.3.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Dasst" version))
       (sha256
        (base32 "1q18wss5bla3hvhnvmwxpd8lbs6fpdkqf5bfiqva050hsdfq1fk7"))))
    (properties `((upstream-name . "Dasst")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=Dasst")
    (synopsis "Tools for Reading, Processing and Writing 'DSSAT' Files")
    (description
     "This package provides methods for reading, displaying, processing and writing
files originally arranged for the DSSAT-CSM fixed width format.  The DSSAT-CSM
cropping system model is described at J.W. Jones, G. Hoogenboomb, C.H. Porter,
K.J. Boote, W.D. Batchelor, L.A. Hunt, P.W. Wilkens, U. Singh, A.J. Gijsman,
J.T. Ritchie (2003) <doi:10.1016/S1161-0301(02)00107-7>.")
    (license license:gpl2+)))

(define-public r-dashboardthemes
  (package
    (name "r-dashboardthemes")
    (version "1.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dashboardthemes" version))
       (sha256
        (base32 "0yki4gmklrkhs6ldznabdr04smw3a112ask313z1h93dnvabr06c"))))
    (properties `((upstream-name . "dashboardthemes")))
    (build-system r-build-system)
    (propagated-inputs (list r-htmltools))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/nik01010/dashboardthemes")
    (synopsis
     "Customise the Appearance of 'shinydashboard' Applications using Themes")
    (description
     "Allows manual creation of themes and logos to be used in applications created
using the shinydashboard package.  Removes the need to change the underlying css
code by wrapping it into a set of convenient R functions.")
    (license license:expat)))

(define-public r-dartrverse
  (package
    (name "r-dartrverse")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dartRverse" version))
       (sha256
        (base32 "0z6nx5j1jgyzmcxdmdbxdhigq7qc3mka0fq6ghyfqaa3089lc823"))))
    (properties `((upstream-name . "dartRverse")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-devtools r-cli))
    (home-page "https://github.com/green-striped-gecko/dartRverse")
    (synopsis "Install and Load the 'dartRverse' Suits of Packages")
    (description
     "This package provides a single function that supports the installation of all
packages belonging to the @code{dartRverse}'.  The @code{dartRverse} is a set of
packages that work together to analyse SNP (single nuclear polymorphism) data.
All packages aim to have a similar look and feel and are based on the same type
of data structure ('genlight'), with additional metadata for loci and
individuals (samples).  For more information visit the @code{GitHub} pages
<https://github.com/green-striped-gecko/@code{dartRverse>}.")
    (license license:gpl3+)))

(define-public r-dartr-spatial
  (package
    (name "r-dartr-spatial")
    (version "0.78")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dartR.spatial" version))
       (sha256
        (base32 "1fjajinsc2ikvhz4igjyldvfd5skdqhnay5209dzx4xjpnkik5vv"))))
    (properties `((upstream-name . "dartR.spatial")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-tidyr
                             r-stampp
                             r-sp
                             r-raster
                             r-mass
                             r-ggplot2
                             r-data-table
                             r-dartr-data
                             r-dartr-base
                             r-crayon
                             r-adegenet))
    (home-page "https://green-striped-gecko.github.io/dartR/")
    (synopsis
     "Applying Landscape Genomic Methods on 'SNP' and 'Silicodart' Data")
    (description
     "This package provides landscape genomic functions to analyse SNP (single nuclear
polymorphism) data, such as least cost path analysis and isolation by distance.
Therefore each sample needs to have coordinate data attached (lat/lon) to be
able to run most of the functions. @code{dartR.spatial} is a package that
belongs to the @code{dartRverse} suit of packages and depends on
@code{dartR.base} and @code{dartR.data}'.")
    (license license:gpl3+)))

(define-public r-dartr-sim
  (package
    (name "r-dartr-sim")
    (version "0.70")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dartR.sim" version))
       (sha256
        (base32 "02l18hvdd1hr9l15frvaw7nikjmr7iyq3wvg5xz8drma4v9r9lwb"))))
    (properties `((upstream-name . "dartR.sim")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-stringi
                             r-shinywidgets
                             r-shinythemes
                             r-shinyjs
                             r-shinybs
                             r-shiny
                             r-reshape2
                             r-rcpp
                             r-hierfstat
                             r-ggplot2
                             r-fields
                             r-data-table
                             r-dartr-data
                             r-dartr-base
                             r-adegenet))
    (home-page "https://green-striped-gecko.github.io/dartR/")
    (synopsis "Computer Simulations of 'SNP' Data")
    (description
     "Allows to simulate SNP data using genlight objects.  For example, it is straight
forward to simulate a simple drift scenario with exchange of individuals between
two populations or create a new genlight object based on allele frequencies of
an existing genlight object.")
    (license license:gpl3+)))

(define-public r-dartr-sexlinked
  (package
    (name "r-dartr-sexlinked")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dartR.sexlinked" version))
       (sha256
        (base32 "07x9zly2vwzd9riw0hfwl8nqq4chs9rgwjj7b39whz25an6aqvvw"))))
    (properties `((upstream-name . "dartR.sexlinked")))
    (build-system r-build-system)
    (propagated-inputs (list r-patchwork
                             r-ggplot2
                             r-foreach
                             r-doparallel
                             r-dartr-data
                             r-dartr-base
                             r-adegenet))
    (home-page "https://green-striped-gecko.github.io/dartR/")
    (synopsis "Analysing SNP Data to Identify Sex-Linked Markers")
    (description
     "Identifies, filters and exports sex linked markers using SNP (single nucleotide
polymorphism) data.  To install the other packages, we recommend to install the
@code{dartRverse} package, that supports the installation of all packages in the
@code{dartRverse}'.  If you want understand the applied rational to identify
sexlinked markers and/or want to cite @code{dartR.sexlinked}', you find the
information by typing citation('@code{dartR.sexlinked}') in the console.")
    (license license:gpl3+)))

(define-public r-dartr-popgen
  (package
    (name "r-dartr-popgen")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dartR.popgen" version))
       (sha256
        (base32 "0wi2pkd3c2f05m0g3mhr3j6nq0wgn656c6z8h4vlphfinnz0knja"))))
    (properties `((upstream-name . "dartR.popgen")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-patchwork
                             r-mass
                             r-ggplot2
                             r-ggdendro
                             r-future
                             r-furrr
                             r-dplyr
                             r-data-table
                             r-dartr-data
                             r-dartr-base
                             r-crayon
                             r-adegenet))
    (home-page "https://green-striped-gecko.github.io/dartR/")
    (synopsis
     "Analysing 'SNP' and 'Silicodart' Data Generated by Genome-Wide Restriction Fragment Analysis")
    (description
     "Facilitates the analysis of SNP (single nucleotide polymorphism) and silicodart
(presence/absence) data. @code{dartR.popgen} provides a suit of functions to
analyse such data in a population genetics context.  It provides several
functions to calculate population genetic metrics and to study population
structure.  Quite a few functions need additional software to be able to run
(gl.run.structure(), gl.blast(), gl.LDNe()).  You find detailed description in
the help pages how to download and link the packages so the function can run the
software. @code{dartR.popgen} is part of the the @code{dartRverse} suit of
packages.  Gruber et al. (2018) <doi:10.1111/1755-0998.12745>.  Mijangos et al.
(2022) <doi:10.1111/2041-210X.13918>.")
    (license license:gpl3+)))

(define-public r-dartr-data
  (package
    (name "r-dartr-data")
    (version "1.0.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dartR.data" version))
       (sha256
        (base32 "179nqwnkkkjw3c2a7z3gw4d37122fnidnxrxi05sh62aqmjlw5ip"))))
    (properties `((upstream-name . "dartR.data")))
    (build-system r-build-system)
    (propagated-inputs (list r-crayon r-adegenet))
    (home-page "https://github.com/green-striped-gecko/dartR.data")
    (synopsis "Auxiliary Data Package for Our Main Package 'dartR'")
    (description
     "Data package for @code{dartR}'.  Provides data sets to run examples in
@code{dartR}'.  This was necessary due to the size limit imposed by CRAN'.  The
data in @code{dartR.data} is needed to run the examples provided in the
@code{dartR} functions.  All available data sets are either based on actual data
(but reduced in size) and/or simulated data sets to allow the fast execution of
examples and demonstration of the functions.")
    (license license:gpl3+)))

(define-public r-dartr-captive
  (package
    (name "r-dartr-captive")
    (version "0.75")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dartR.captive" version))
       (sha256
        (base32 "1n6qhn87111ydznmy85lj7sbxkkak4nwiq1kyky3p43x9679b2p9"))))
    (properties `((upstream-name . "dartR.captive")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-patchwork
                             r-ggplot2
                             r-dartr-data
                             r-dartr-base
                             r-crayon
                             r-adegenet))
    (home-page "https://green-striped-gecko.github.io/dartR/")
    (synopsis "Analysing 'SNP' Data to Support Captive Breeding")
    (description
     "This package provides functions are provided that facilitate the analysis of SNP
(single nucleotide polymorphism) data to answer questions regarding captive
breeding and relatedness between individuals. @code{dartR.captive} is part of
the @code{dartRverse} suit of packages.  Gruber et al. (2018)
<doi:10.1111/1755-0998.12745>.  Mijangos et al. (2022)
<doi:10.1111/2041-210X.13918>.")
    (license license:gpl3+)))

(define-public r-dartr-base
  (package
    (name "r-dartr-base")
    (version "0.98")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dartR.base" version))
       (sha256
        (base32 "0ndl0319pidlkk5fv49zqr8kbib51v60h32k906rwc57jf60xbjk"))))
    (properties `((upstream-name . "dartR.base")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-stampp
                             r-snprelate
                             r-snpassoc
                             r-reshape2
                             r-plyr
                             r-patchwork
                             r-mass
                             r-gridextra
                             r-ggplot2
                             r-foreach
                             r-dplyr
                             r-data-table
                             r-dartr-data
                             r-crayon
                             r-ape
                             r-adegenet))
    (home-page "https://green-striped-gecko.github.io/dartR/")
    (synopsis "Analysing 'SNP' and 'Silicodart' Data - Basic Functions")
    (description
     "Facilitates the import and analysis of SNP (single nucleotide polymorphism') and
silicodart (presence/absence) data.  The main focus is on data generated by
@code{DarT} (Diversity Arrays Technology), however, data from other sequencing
platforms can be used once SNP or related fragment presence/absence data from
any source is imported.  Genetic datasets are stored in a derived genlight
format (package adegenet'), that allows for a very compact storage of data and
metadata.  Functions are available for importing and exporting of SNP and
silicodart data, for reporting on and filtering on various criteria (e.g.
callrate', heterozygosity', reproducibility', maximum allele frequency).
Additional functions are available for visualization (e.g. Principle Coordinate
Analysis) and creating a spatial representation using maps. @code{dartR.base} is
the base package of the @code{dartRverse} suits of packages.  To install the
other packages, we recommend to install the @code{dartRverse} package, that
supports the installation of all packages in the @code{dartRverse}'.  If you
want to cite @code{dartR}', you find the information by typing
citation('@code{dartR.base}') in the console.")
    (license license:gpl3+)))

(define-public r-dartr
  (package
    (name "r-dartr")
    (version "2.9.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dartR" version))
       (sha256
        (base32 "1wwm2gq743l90jsa1hsgxknqxqp0ga8vf3xv652m3ifpyrkp93vx"))))
    (properties `((upstream-name . "dartR")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan
                             r-tidyr
                             r-stringr
                             r-stampp
                             r-sp
                             r-snprelate
                             r-shiny
                             r-reshape2
                             r-raster
                             r-popgenreport
                             r-plyr
                             r-patchwork
                             r-mass
                             r-gridextra
                             r-ggplot2
                             r-foreach
                             r-fields
                             r-dplyr
                             r-data-table
                             r-dartr-data
                             r-crayon
                             r-ape
                             r-adegenet))
    (native-inputs (list r-knitr))
    (home-page "https://green-striped-gecko.github.io/dartR/")
    (synopsis
     "Importing and Analysing 'SNP' and 'Silicodart' Data Generated by Genome-Wide Restriction Fragment Analysis")
    (description
     "This package provides functions are provided that facilitate the import and
analysis of SNP (single nucleotide polymorphism) and silicodart
(presence/absence) data.  The main focus is on data generated by @code{DarT}
(Diversity Arrays Technology), however, data from other sequencing platforms can
be used once SNP or related fragment presence/absence data from any source is
imported.  Genetic datasets are stored in a derived genlight format (package
adegenet'), that allows for a very compact storage of data and metadata.
Functions are available for importing and exporting of SNP and silicodart data,
for reporting on and filtering on various criteria (e.g. @code{CallRate}',
heterozygosity, reproducibility, maximum allele frequency).  Additional
functions are available for visualization (e.g. Principle Coordinate Analysis)
and creating a spatial representation using maps. @code{dartR} supports also the
analysis of 3rd party software package such as newhybrid', structure',
@code{NeEstimator} and blast'.  Since version 2.0.3 we also implemented
simulation functions, that allow to forward simulate SNP dynamics under
different population and evolutionary dynamics.  Comprehensive tutorials and
support can be found at our github repository:
github.com/green-striped-gecko/@code{dartR}/.  If you want to cite
@code{dartR}', you find the information by typing citation('@code{dartR}') in
the console.")
    (license license:gpl3+)))

(define-public r-darksky
  (package
    (name "r-darksky")
    (version "1.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "darksky" version))
       (sha256
        (base32 "1740cw5qifgvqa0nafd6lmllxi32n1zm45zlify1yn3h1qdcszhb"))))
    (properties `((upstream-name . "darksky")))
    (build-system r-build-system)
    (propagated-inputs (list r-plyr r-httr r-gtable r-gridextra r-ggplot2))
    (home-page "https://github.com/hrbrmstr/darksky")
    (synopsis "Tools to Work with the 'Dark Sky' 'API'")
    (description
     "This package provides programmatic access to the Dark Sky API
<https://darksky.net/dev/docs>, which provides current or historical global
weather conditions.")
    (license license:expat)))

(define-public r-darkdiv
  (package
    (name "r-darkdiv")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DarkDiv" version))
       (sha256
        (base32 "0cjf5rpn4myd21rh04bk2gjk65rjx77mn8mxy4ym704fiycrsj87"))))
    (properties `((upstream-name . "DarkDiv")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan))
    (home-page "https://cran.r-project.org/package=DarkDiv")
    (synopsis "Estimating Dark Diversity and Site-Specific Species Pools")
    (description
     "Estimation of dark diversity and site-specific species pools using species
co-occurrences.  It includes implementations of probabilistic dark diversity
based on the Hypergeometric distribution, as well as estimations based on the
Beals index, which can be transformed to binary predictions using different
thresholds, or transformed into a favorability index.  All methods include the
possibility of using a calibration dataset that is used to estimate the
indication matrix between pairs of species, or to estimate dark diversity
directly on a single dataset.  See De Caceres and Legendre (2008)
<doi:10.1007/s00442-008-1017-y>, Lewis et al. (2016)
<doi:10.1111/2041-210X.12443>, Partel et al. (2011)
<doi:10.1016/j.tree.2010.12.004>, Real et al. (2017) <doi:10.1093/sysbio/syw072>
for further information.")
    (license license:gpl3)))

(define-public r-dark
  (package
    (name "r-dark")
    (version "0.9.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Dark" version))
       (sha256
        (base32 "1f01aq4g50f07005c8k91cfy9hvl3fmb4yl2924d7512m3884xlv"))))
    (properties `((upstream-name . "Dark")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/emkayoh/Dark")
    (synopsis "The Analysis of Dark Adaptation Data")
    (description
     "The recovery of visual sensitivity in a dark environment is known as dark
adaptation.  In a clinical or research setting the recovery is typically
measured after a dazzling flash of light and can be described by the Mahroo,
Lamb and Pugh (MLP) model of dark adaptation.  The functions in this package
take dark adaptation data and use nonlinear regression to find the parameters of
the model that best describe the data.  They do this by firstly, generating
rapid initial objective estimates of data adaptation parameters, then a
multi-start algorithm is used to reduce the possibility of a local minimum.
There is also a bootstrap method to calculate parameter confidence intervals.
The functions rely upon a dark list or object.  This object is created as the
first step in the workflow and parts of the object are updated as it is
processed.")
    (license license:gpl3)))

(define-public r-darand
  (package
    (name "r-darand")
    (version "0.0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DArand" version))
       (sha256
        (base32 "1pwd5srrjy8mhs40k6g6x5j3vk9cr5hylk8sdyiiqalpq490nzqy"))))
    (properties `((upstream-name . "DArand")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=DArand")
    (synopsis "Differential Analysis with Random Reference Genes")
    (description
     "Differential Analysis of short RNA transcripts that can be modeled by either
Poisson or Negative binomial distribution.  The statistical methodology
implemented in this package is based on the random selection of references genes
(Desaulle et al. (2021) <@code{arXiv:2103.09872>}).")
    (license license:expat)))

(define-public r-daqapo
  (package
    (name "r-daqapo")
    (version "0.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "daqapo" version))
       (sha256
        (base32 "1c00ppsqzjmrw16zdifkcigi4ll2nd2hlhj17lydmin0djg5cpby"))))
    (properties `((upstream-name . "daqapo")))
    (build-system r-build-system)
    (propagated-inputs (list r-xesreadr
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-stringdist
                             r-shiny
                             r-rlang
                             r-readr
                             r-purrr
                             r-miniui
                             r-magrittr
                             r-lubridate
                             r-glue
                             r-edear
                             r-dplyr
                             r-bupar))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/bupaverse/daqapo/")
    (synopsis "Data Quality Assessment for Process-Oriented Data")
    (description
     "This package provides a variety of methods to identify data quality issues in
process-oriented data, which are useful to verify data quality in a process
mining context.  Builds on the class for activity logs implemented in the
package @code{bupaR}'.  Methods to identify data quality issues either consider
each activity log entry independently (e.g. missing values, activity duration
outliers,...), or focus on the relation amongst several activity log entries
(e.g. batch registrations, violations of the expected activity order,...).")
    (license license:expat)))

(define-public r-dapper
  (package
    (name "r-dapper")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dapper" version))
       (sha256
        (base32 "06s78b80215lxsi68isaha6kfrr0490s4bg0y9yf5v5ns9a6x0wv"))))
    (properties `((upstream-name . "dapper")))
    (build-system r-build-system)
    (propagated-inputs (list r-progressr
                             r-posterior
                             r-memoise
                             r-furrr
                             r-checkmate
                             r-bayesplot))
    (home-page "https://github.com/mango-empire/dapper")
    (synopsis "Data Augmentation for Private Posterior Estimation")
    (description
     "This package provides a data augmentation based sampler for conducting
privacy-aware Bayesian inference.  The dapper_sample() function takes an
existing sampler as input and automatically constructs a privacy-aware sampler.
The process of constructing a sampler is simplified through the specification of
four independent modules, allowing for easy comparison between different privacy
mechanisms by only swapping out the relevant modules.  Probability mass
functions for the discrete Gaussian and discrete Laplacian are provided to
facilitate analyses dealing with privatized count data.  The output of
dapper_sample() can be analyzed using many of the same tools from the `rstan`
ecosystem.  For methodological details on the sampler see Ju et al. (2022)
<doi:10.48550/@code{arXiv.2206.00710>}, and for details on the discrete Gaussian
and discrete Laplacian distributions see Canonne et al. (2020)
<doi:10.48550/@code{arXiv.2004.00010>}.")
    (license license:expat)))

(define-public r-danstat
  (package
    (name "r-danstat")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "danstat" version))
       (sha256
        (base32 "16b0dl41g56s6iyxndpl403wgqqj1l3g9k78y3ciq5djq3a25m97"))))
    (properties `((upstream-name . "danstat")))
    (build-system r-build-system)
    (propagated-inputs (list r-readr r-jsonlite r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=danstat")
    (synopsis "R Client for the Statistics Denmark Databank API")
    (description
     "The purpose of the package is to enable an R function interface into the
Statistics Denmark Databank API mainly for research purposes.  The Statistics
Denmark Databank API has four endpoints, see here for more information and
testing the API in their console:
<https://www.dst.dk/en/Statistik/brug-statistikken/muligheder-i-statistikbanken/api>.
 This package mimics the structure of the API and provides four main functions
to match the functionality of the API endpoints.")
    (license license:expat)))

(define-public r-dann
  (package
    (name "r-dann")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dann" version))
       (sha256
        (base32 "0hmmkzv3cq0yl8kgcj08557zx086ablh6ngmyxhb1chig7kmmb4x"))))
    (properties `((upstream-name . "dann")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-rlang
                             r-rcpparmadillo
                             r-rcpp
                             r-purrr
                             r-mass
                             r-hardhat
                             r-ggplot2
                             r-fpc
                             r-ellipsis))
    (home-page "https://cran.r-project.org/package=dann")
    (synopsis "Discriminant Adaptive Nearest Neighbor Classification")
    (description
     "Discriminant Adaptive Nearest Neighbor Classification is a variation of k
nearest neighbors where the shape of the neighborhood is data driven.  This
package implements dann and sub_dann from Hastie (1996)
<https://web.stanford.edu/~hastie/Papers/dann_IEEE.pdf>.")
    (license license:expat)))

(define-public r-danielbiostatistics10th
  (package
    (name "r-danielbiostatistics10th")
    (version "0.2.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DanielBiostatistics10th" version))
       (sha256
        (base32 "0qgakqybrg7knpgvl5v0126h9mpah5a392hl1sm7hprwvqm4xg5f"))))
    (properties `((upstream-name . "DanielBiostatistics10th")))
    (build-system r-build-system)
    (propagated-inputs (list r-vcd r-pracma r-e1071 r-cli))
    (home-page "https://cran.r-project.org/package=DanielBiostatistics10th")
    (synopsis "Functions for Wayne W. Daniel's Biostatistics, Tenth Edition")
    (description
     "This package provides functions to accompany Wayne W. Daniel's Biostatistics: A
Foundation for Analysis in the Health Sciences, Tenth Edition.")
    (license license:gpl2)))

(define-public r-dani
  (package
    (name "r-dani")
    (version "0.1-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dani" version))
       (sha256
        (base32 "0ff0hcb5r8k6m6kv1zhjrpvl7gr1al3q0zlk4yjj89qd2j5byqp8"))))
    (properties `((upstream-name . "dani")))
    (build-system r-build-system)
    (propagated-inputs (list r-epi))
    (home-page "https://cran.r-project.org/package=dani")
    (synopsis "Design and Analysis of Non-Inferiority Trials")
    (description
     "This package provides tools to help the design and analysis of resilient
non-inferiority trials.  These include functions for sample size calculations
and analyses of trials, with either a risk difference, risk ratio or arc-sine
difference margin, and a function to run simulations to design a trial with the
methods described in Quartagno et al. (2019) <@code{arXiv:1905.00241>}.")
    (license license:gpl2)))

(define-public r-dang
  (package
    (name "r-dang")
    (version "0.0.16")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dang" version))
       (sha256
        (base32 "1h0j2pxwp8dnaw2vrclj069xmd6adwah8ld4vmmh3zm7kwflvcx8"))))
    (properties `((upstream-name . "dang")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidycpp))
    (home-page "https://github.com/eddelbuettel/dang")
    (synopsis "'Dang' Associated New Goodies")
    (description "This package provides a collection of utility functions.")
    (license license:gpl2+)))

(define-public r-dandefa
  (package
    (name "r-dandefa")
    (version "1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DandEFA" version))
       (sha256
        (base32 "1ir1z76c8742vqdlwv35l4rhr0x7lhghz24g35zn7b30671lypf8"))))
    (properties `((upstream-name . "DandEFA")))
    (build-system r-build-system)
    (propagated-inputs (list r-polycor r-gplots))
    (home-page "https://cran.r-project.org/package=DandEFA")
    (synopsis "Dandelion Plot for R-Mode Exploratory Factor Analysis")
    (description
     "This package contains the function used to create the Dandelion Plot.  Dandelion
Plot is a visualization method for R-mode Exploratory Factor Analysis.")
    (license license:gpl2)))

(define-public r-dams
  (package
    (name "r-dams")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dams" version))
       (sha256
        (base32 "1jlx1b4cir1vwq75jnmk0pc6j95syfpi0hlnkx82g7pwfxwrdrib"))))
    (properties `((upstream-name . "dams")))
    (build-system r-build-system)
    (propagated-inputs (list r-readxl r-janitor r-fauxpas r-crul))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jsta/dams")
    (synopsis
     "Dams in the United States from the National Inventory of Dams (NID)")
    (description
     "The single largest source of dams in the United States is the National Inventory
of Dams (NID) <http://nid.usace.army.mil> from the US Army Corps of Engineers.
Entire data from the NID cannot be obtained all at once and NID's website limits
extraction of more than a couple of thousand records at a time.  Moreover,
selected data from the NID's user interface cannot not be saved to a file.  In
order to make the analysis of this data easier, all the data from NID was
extracted manually.  Subsequently, the raw data was checked for potential errors
and cleaned.  This package provides sample cleaned data from the NID and
provides functionality to access the entire cleaned NID data.")
    (license license:gpl2+)))

(define-public r-damr
  (package
    (name "r-damr")
    (version "0.3.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "damr" version))
       (sha256
        (base32 "12vr630m2az8xb8wndk8cyh7r8mwg3lvr7i3fcgqqxcq9rsgqm4r"))))
    (properties `((upstream-name . "damr")))
    (build-system r-build-system)
    (propagated-inputs (list r-readr r-data-table r-behavr))
    (home-page "https://github.com/rethomics/damr")
    (synopsis "Interface to Drosophila Activity Monitor System Result Files")
    (description
     "Loads behavioural data from the widely used Drosophila Activity Monitor System
(DAMS, @code{TriKinetics} <https://trikinetics.com/>) into the rethomics
framework.")
    (license license:gpl3)))

(define-public r-dampack
  (package
    (name "r-dampack")
    (version "1.0.2.1000")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dampack" version))
       (sha256
        (base32 "0zbxl1m4rhf69qwvhxph18wim0hwnhqijkfkwm2nfgv9nnyi3m0k"))))
    (properties `((upstream-name . "dampack")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncnorm
                             r-triangle
                             r-tidyr
                             r-stringr
                             r-scales
                             r-rlang
                             r-mgcv
                             r-ggrepel
                             r-ggplot2
                             r-ellipse
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/DARTH-git/dampack")
    (synopsis "Decision-Analytic Modeling Package")
    (description
     "This package provides a suite of functions for analyzing and visualizing the
health economic outputs of mathematical models.  This package was developed with
funding from the National Institutes of Allergy and Infectious Diseases of the
National Institutes of Health under award no.  R01AI138783.  The content of this
package is solely the responsibility of the authors and does not necessarily
represent the official views of the National Institutes of Health.  The
theoretical underpinnings of dampack''s functionality are detailed in Hunink et
al. (2014) <doi:10.1017/CBO9781139506779>.")
    (license license:gpl3)))

(define-public r-damocles
  (package
    (name "r-damocles")
    (version "2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DAMOCLES" version))
       (sha256
        (base32 "0pk9gq82qa18fl7zp74d47bgy8lhj9rkvfq23w8844nz9kn58s1f"))))
    (properties `((upstream-name . "DAMOCLES")))
    (build-system r-build-system)
    (propagated-inputs (list r-picante
                             r-matrixstats
                             r-matrix
                             r-hmisc
                             r-expm
                             r-desolve
                             r-ddd
                             r-caper
                             r-ape))
    (home-page "https://cran.r-project.org/package=DAMOCLES")
    (synopsis
     "Dynamic Assembly Model of Colonization, Local Extinction and Speciation")
    (description
     "Simulates and computes (maximum) likelihood of a dynamical model of community
assembly that takes into account phylogenetic history.")
    (license license:gpl2)))

(define-public r-damiann
  (package
    (name "r-damiann")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DamiaNN" version))
       (sha256
        (base32 "09viy1lilz0b29s3myky03981bfnhxjxxgfhdah33cn5x682rbp4"))))
    (properties `((upstream-name . "DamiaNN")))
    (build-system r-build-system)
    (propagated-inputs (list r-testthat r-caret))
    (home-page "https://cran.r-project.org/package=DamiaNN")
    (synopsis "Neural Network Numerai")
    (description
     "Interactively train neural networks on Numerai, <https://numer.ai/>, data.
Generate tournament predictions and write them to a CSV.")
    (license license:gpl3)))

(define-public r-damaoi
  (package
    (name "r-damaoi")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "damAOI" version))
       (sha256
        (base32 "14cfixlc50ml9l2b8m397b292ddq1l36bp8yqw8jw93c3d1q3zpp"))))
    (properties `((upstream-name . "damAOI")))
    (build-system r-build-system)
    (propagated-inputs (list r-units
                             r-tidyr
                             r-tibble
                             r-terra
                             r-smoothr
                             r-shinydashboard
                             r-shiny
                             r-sf
                             r-magrittr
                             r-leaflet
                             r-fnn
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/chrislittleboy/damaoi")
    (synopsis
     "Create an 'Area of Interest' Around a Constructed Dam for Comparative Impact Evaluations")
    (description
     "Define a spatial Area of Interest (AOI) around a constructed dam using hydrology
data.  Dams have environmental and social impacts, both positive and negative.
Current analyses of dams have no consistent way to specify at what spatial
extent we should evaluate these impacts. @code{damAOI} implements methods to
adjust reservoir polygons to match satellite-observed surface water areas, plot
upstream and downstream rivers using elevation data and accumulated river flow,
and draw buffers clipped by river basins around reservoirs and relevant rivers.
This helps to consistently determine the areas which could be impacted by dam
construction, facilitating comparative analysis and informed infrastructure
investments.")
    (license license:gpl3+)))

(define-public r-dam
  (package
    (name "r-dam")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dam" version))
       (sha256
        (base32 "1b0fi3l8jxgpr9fwvi03giq7wm39msbh0c82ffgkh54a3bbf5blc"))))
    (properties `((upstream-name . "dam")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dam")
    (synopsis "Data Analysis Metabolomics")
    (description
     "This package provides a collection of functions which aim to assist common
computational workflow for analysis of matabolomic data..")
    (license license:cc0)))

(define-public r-daly
  (package
    (name "r-daly")
    (version "1.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DALY" version))
       (sha256
        (base32 "1v7ld01xcn5jiygl1c3xhd5h71ip90lks87fs9gmpnivp8jz5cr5"))))
    (properties `((upstream-name . "DALY")))
    (build-system r-build-system)
    (inputs (list tcl))
    (home-page "http://daly.cbra.be")
    (synopsis
     "The DALY Calculator - Graphical User Interface for Probabilistic DALY Calculation in R")
    (description
     "The DALY Calculator is a free, open-source Graphical User Interface (GUI) for
stochastic disability-adjusted life year (DALY) calculation.")
    (license license:gpl2+)))

(define-public r-daltoolboxdp
  (package
    (name "r-daltoolboxdp")
    (version "1.0.767")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "daltoolboxdp" version))
       (sha256
        (base32 "1l34wb2vl9wmf0vrhis29w4hz1m9jx9qdfi494rfnwals054j3ah"))))
    (properties `((upstream-name . "daltoolboxdp")))
    (build-system r-build-system)
    (propagated-inputs (list r-smotefamily
                             r-leaps
                             r-glmnet
                             r-fselector
                             r-doby
                             r-daltoolbox))
    (home-page "https://github.com/cefet-rj-dal/daltoolboxdp")
    (synopsis "Data Pre-Processing Extensions")
    (description
     "An important aspect of data analytics is related to data management support for
artificial intelligence.  It is related to preparing data correctly.  This
package provides extensions to support data preparation in terms of both data
sampling and data engineering.  Overall, the package provides researchers with a
comprehensive set of functionalities for data science based on experiment lines,
promoting ease of use, extensibility, and integration with various tools and
libraries.  Information on Experiment Line is based on Ogasawara et al. (2009)
<doi:10.1007/978-3-642-02279-1_20>.")
    (license license:expat)))

(define-public r-daltoolbox
  (package
    (name "r-daltoolbox")
    (version "1.0.767")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "daltoolbox" version))
       (sha256
        (base32 "02rhbcgjwlx45y0641yjlamzgl2swm60hmvwppr4nk24hb0hjczs"))))
    (properties `((upstream-name . "daltoolbox")))
    (build-system r-build-system)
    (propagated-inputs (list r-tree
                             r-reticulate
                             r-reshape
                             r-randomforest
                             r-nnet
                             r-mlmetrics
                             r-ggplot2
                             r-forecast
                             r-fnn
                             r-elmnnrcpp
                             r-e1071
                             r-dplyr
                             r-dbscan
                             r-cluster
                             r-class
                             r-caret))
    (home-page "https://github.com/cefet-rj-dal/daltoolbox")
    (synopsis "Leveraging Experiment Lines to Data Analytics")
    (description
     "The natural increase in the complexity of current research experiments and data
demands better tools to enhance productivity in Data Analytics.  The package is
a framework designed to address the modern challenges in data analytics
workflows.  The package is inspired by Experiment Line concepts.  It aims to
provide seamless support for users in developing their data mining workflows by
offering a uniform data model and method API. It enables the integration of
various data mining activities, including data preprocessing, classification,
regression, clustering, and time series prediction.  It also offers options for
hyper-parameter tuning and supports integration with existing libraries and
languages.  Overall, the package provides researchers with a comprehensive set
of functionalities for data science, promoting ease of use, extensibility, and
integration with various tools and libraries.  Information on Experiment Line is
based on Ogasawara et al. (2009) <doi:10.1007/978-3-642-02279-1_20>.")
    (license license:expat)))

(define-public r-dalsm
  (package
    (name "r-dalsm")
    (version "0.9.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DALSM" version))
       (sha256
        (base32 "00v3h9np8nfhiyiz6r4bs5gzqqw3qfx275ab1byvjsr42zx11qpr"))))
    (properties `((upstream-name . "DALSM")))
    (build-system r-build-system)
    (propagated-inputs (list r-plyr r-mass r-cubicbsplines))
    (home-page "<https://github.com/plambertULiege/DALSM>")
    (synopsis "Nonparametric Double Additive Location-Scale Model (DALSM)")
    (description
     "Fit of a double additive location-scale model with a nonparametric error
distribution from possibly right- or interval censored data.  The additive terms
in the location and dispersion submodels, as well as the unknown error
distribution in the location-scale model, are estimated using Laplace P-splines.
 For more details, see Lambert (2021) <doi:10.1016/j.csda.2021.107250>.")
    (license license:gpl3)))

(define-public r-dalextra
  (package
    (name "r-dalextra")
    (version "2.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DALEXtra" version))
       (sha256
        (base32 "1yxsk6cmqrhc7aw62vx5pr2g18lh32j5x73jbfxv4k0ia66mmwqf"))))
    (properties `((upstream-name . "DALEXtra")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2 r-dalex))
    (home-page "https://ModelOriented.github.io/DALEXtra/")
    (synopsis "Extension for 'DALEX' Package")
    (description
     "This package provides wrapper of various machine learning models.  In applied
machine learning, there is a strong belief that we need to strike a balance
between interpretability and accuracy.  However, in field of the interpretable
machine learning, there are more and more new ideas for explaining black-box
models, that are implemented in R'.  DALEXtra creates DALEX Biecek (2018)
<@code{arXiv:1806.08915>} explainer for many type of models including those
created using python scikit-learn and keras libraries, and java h2o library.
Important part of the package is Champion-Challenger analysis and innovative
approach to model performance across subsets of test data presented in Funnel
Plot.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-daks
  (package
    (name "r-daks")
    (version "2.1-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DAKS" version))
       (sha256
        (base32 "0vmpwxvksnmyq40faimbgpj0y3zbk519986n38ipwdfzllcg0zs4"))))
    (properties `((upstream-name . "DAKS")))
    (build-system r-build-system)
    (propagated-inputs (list r-sets r-relations))
    (home-page "http://www.meb.edu.tum.de")
    (synopsis "Data Analysis and Knowledge Spaces")
    (description
     "This package provides functions and an example dataset for the psychometric
theory of knowledge spaces.  This package implements data analysis methods and
procedures for simulating data and quasi orders and transforming different
formulations in knowledge space theory.  See package?DAKS for an overview.")
    (license license:gpl2+)))

(define-public r-daisieprep
  (package
    (name "r-daisieprep")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DAISIEprep" version))
       (sha256
        (base32 "0ch3mc725lip67fpbk405rv3bai44w13vvjlspv8y6jzmb5jg6bp"))))
    (properties `((upstream-name . "DAISIEprep")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-scales
                             r-rlang
                             r-phylobase
                             r-ggtree
                             r-ggplot2
                             r-daisie
                             r-castor
                             r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/joshwlambert/DAISIEprep")
    (synopsis
     "Extracts Phylogenetic Island Community Data from Phylogenetic Trees")
    (description
     "Extracts colonisation and branching times of island species to be used for
analysis in the R package DAISIE'.  It uses phylogenetic and endemicity data to
extract the separate island colonists and store them.")
    (license license:gpl3+)))

(define-public r-daisie
  (package
    (name "r-daisie")
    (version "4.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DAISIE" version))
       (sha256
        (base32 "0f1ym3k49m2wdilsg7vwsb7m4ccdg87pnaksmbqv9smcxn5v8rn2"))))
    (properties `((upstream-name . "DAISIE")))
    (build-system r-build-system)
    (propagated-inputs (list r-testit
                             r-tensor
                             r-subplex
                             r-rcppeigen
                             r-rcpp
                             r-pracma
                             r-matrix
                             r-magrittr
                             r-foreach
                             r-doparallel
                             r-desolve
                             r-ddd
                             r-bh))
    (native-inputs (list r-knitr gfortran))
    (home-page "https://github.com/rsetienne/DAISIE")
    (synopsis
     "Dynamical Assembly of Islands by Speciation, Immigration and Extinction")
    (description
     "Simulates and computes the (maximum) likelihood of a dynamical model of island
biota assembly through speciation, immigration and extinction.  See Valente et
al. (2015) <doi:10.1111/ele.12461>.")
    (license (list license:gpl3+
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-dair
  (package
    (name "r-dair")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "daiR" version))
       (sha256
        (base32 "110car64pgpg71dcqnbkj91md0xwikpmd6iy90nj84nglycc5v00"))))
    (properties `((upstream-name . "daiR")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-stringr
                             r-readtext
                             r-purrr
                             r-pdftools
                             r-magick
                             r-lifecycle
                             r-jsonlite
                             r-httr
                             r-googlecloudstorager
                             r-glue
                             r-gargle
                             r-fs
                             r-data-table
                             r-cli
                             r-beepr
                             r-base64enc))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Hegghammer/daiR")
    (synopsis "Interface with Google Cloud Document AI API")
    (description
     "R interface for the Google Cloud Services Document AI API
<https://cloud.google.com/document-ai/> with additional tools for output file
parsing and text reconstruction.  Document AI is a powerful server-based OCR
service that extracts text and tables from images and PDF files with high
accuracy. @code{daiR} gives R users programmatic access to this service and
additional tools to handle and visualize the output.  See the package website
<https://dair.info/> for more information and examples.")
    (license license:expat)))

(define-public r-daiquiri
  (package
    (name "r-daiquiri")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "daiquiri" version))
       (sha256
        (base32 "05057i8xvkzyd8h1ppw7qip1d4yjgzimmb5chbdw72mwwgbrwrfy"))))
    (properties `((upstream-name . "daiquiri")))
    (build-system r-build-system)
    (propagated-inputs (list r-xfun
                             r-scales
                             r-rmarkdown
                             r-readr
                             r-reactable
                             r-ggplot2
                             r-data-table
                             r-cowplot))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ropensci/daiquiri")
    (synopsis "Data Quality Reporting for Temporal Datasets")
    (description
     "Generate reports that enable quick visual review of temporal shifts in
record-level data.  Time series plots showing aggregated values are
automatically created for each data field (column) depending on its contents
(e.g. min/max/mean values for numeric data, no.  of distinct values for
categorical data), as well as overviews for missing values, non-conformant
values, and duplicated rows.  The resulting reports are shareable and can
contribute to forming a transparent record of the entire analysis process.  It
is designed with Electronic Health Records in mind, but can be used for any type
of record-level temporal data (i.e.  tabular data where each row represents a
single \"event\", one column contains the \"event date\", and other columns contain
any associated values for the event).")
    (license license:gpl3+)))

(define-public r-daime
  (package
    (name "r-daime")
    (version "2.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DAIME" version))
       (sha256
        (base32 "099pbzgryz9lxhcqlrywcv8zl5af4ir5dyyqvgc16xi5bddxk7ld"))))
    (properties `((upstream-name . "DAIME")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DAIME")
    (synopsis "Effects of Changing Deposition Rates")
    (description
     "Reverse and model the effects of changing deposition rates on geological data
and rates.  Based on Hohmann (2018) <doi:10.13140/RG.2.2.23372.51841> .")
    (license (license:fsdg-compatible "CC BY 4.0"))))

(define-public r-dail
  (package
    (name "r-dail")
    (version "1.5.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dail" version))
       (sha256
        (base32 "0a82ch0l7ci9vjrwyy38qhw8zrp9d4h2bmk963llm9aqf4j7lkhf"))))
    (properties `((upstream-name . "dail")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidytext
                             r-stringr
                             r-stopwords
                             r-readr
                             r-rcurl
                             r-magrittr
                             r-lubridate
                             r-janitor
                             r-dplyr
                             r-deflatebr))
    (home-page "https://cran.r-project.org/package=dail")
    (synopsis "Data from Access to Information Law")
    (description
     "Downloads the public data available from the Brazilian Access to Information Law
and and performs a search on information requests and appeals made since 2015.")
    (license license:expat)))

(define-public r-dagwood
  (package
    (name "r-dagwood")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dagwood" version))
       (sha256
        (base32 "1lp6swfmfzv28cfybmvj7czkfljd0sldv2qqi83q0fwcb7kxgdfz"))))
    (properties `((upstream-name . "dagwood")))
    (build-system r-build-system)
    (propagated-inputs (list r-dagitty))
    (home-page "https://cran.r-project.org/package=dagwood")
    (synopsis "DAGs with Omitted Objects Displayed (DAGWOOD)")
    (description
     "DAGs With Omitted Objects Displayed (DAGWOOD) is a framework to help reveal key
hidden assumptions in a causal DAG. This package provides an implementation of
the DAGWOOD algorithm.  Further description can be found in Haber et al (2022)
<DOI:10.1016/j.annepidem.2022.01.001>.")
    (license license:expat)))

(define-public r-dagr
  (package
    (name "r-dagr")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dagR" version))
       (sha256
        (base32 "16dx7gpbq61xwnk3769mf6nsynqb3zgjl6l0zcvh8j0cp1s35m82"))))
    (properties `((upstream-name . "dagR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dagR")
    (synopsis "Directed Acyclic Graphs: Analysis and Data Simulation")
    (description
     "Draw, manipulate, and evaluate directed acyclic graphs and simulate
corresponding data, as described in International Journal of Epidemiology
50(6):1772-1777.")
    (license license:gpl2)))

(define-public r-dagitty
  (package
    (name "r-dagitty")
    (version "0.3-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dagitty" version))
       (sha256
        (base32 "10iw5ldra7ih3jpp1iaac6cbfgpl62bq09zl30c0z03mzhj18vvr"))))
    (properties `((upstream-name . "dagitty")))
    (build-system r-build-system)
    (propagated-inputs (list r-v8 r-mass r-jsonlite r-boot))
    (native-inputs (list r-knitr))
    (home-page "https://www.dagitty.net")
    (synopsis "Graphical Analysis of Structural Causal Models")
    (description
     "This package provides a port of the web-based software DAGitty', available at
<https://dagitty.net>, for analyzing structural causal models (also known as
directed acyclic graphs or DAGs).  This package computes covariate adjustment
sets for estimating causal effects, enumerates instrumental variables, derives
testable implications (d-separation and vanishing tetrads), generates equivalent
models, and includes a simple facility for data simulation.")
    (license license:gpl2)))

(define-public r-dagirlite
  (package
    (name "r-dagirlite")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dagirlite" version))
       (sha256
        (base32 "12j5mfxcv32qgx1yklcq8yl2kx4lkxap4biywjrj0sjx6zj60f8l"))))
    (properties `((upstream-name . "dagirlite")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-knitr))
    (home-page "https://cran.r-project.org/package=dagirlite")
    (synopsis
     "Spatial Vector Data for Danmarks Administrative Geografiske Inddeling DAGI")
    (description
     "Compressed spatial vector data originally from
<https://dawadocs.dataforsyningen.dk/> saved as Simple Features, SF, objects
with data on population, age and gender from Statistics Denmark
<https://www.dst.dk/da/>.")
    (license license:expat)))

(define-public r-dafs
  (package
    (name "r-dafs")
    (version "1.0-38")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dafs" version))
       (sha256
        (base32 "0ljhpw2f4hbkqh6c6gwqwwdsa4kp5qvyphig5zcn6qrb9ryf3wh1"))))
    (properties `((upstream-name . "dafs")))
    (build-system r-build-system)
    (propagated-inputs (list r-s20x))
    (home-page "https://cran.r-project.org/package=dafs")
    (synopsis "Data Analysis for Forensic Scientists")
    (description
     "Data and miscellanea to support the book \"Introduction to Data analysis with R
for Forensic Scientists.\" This book was written by James Curran and published by
CRC Press in 2010 (ISBN: 978-1-4200-8826-7).")
    (license license:gpl2+)))

(define-public r-dafishr
  (package
    (name "r-dafishr")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dafishr" version))
       (sha256
        (base32 "1pdw0qrsln6cf7k1r0a09j7va5nzyz7a484nz5fjccxs0lwgxhjx"))))
    (properties `((upstream-name . "dafishr")))
    (build-system r-build-system)
    (propagated-inputs (list r-vroom
                             r-tidyselect
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-sf
                             r-rlang
                             r-readxl
                             r-readr
                             r-mixtools
                             r-magrittr
                             r-lubridate
                             r-ggplot2
                             r-fst
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/CBMC-GCMP/dafishr")
    (synopsis "Download, Wrangle, and Analyse Vessel Monitoring System Data")
    (description
     "Allows to download, clean and analyse raw Vessel Monitoring System, VMS, data
from Mexican government.  You can use the vms_download() function to download
raw data, or you can use the sample_dataset provided within the package.  You
can follow the tutorial in the vignette available at
<https://cbmc-gcmp.github.io/dafishr/index.html>.")
    (license license:expat)))

(define-public r-daff
  (package
    (name "r-daff")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "daff" version))
       (sha256
        (base32 "0zbh3p7d2r04j9kzfk32j2zw9f745dk7yl2dx8lflrm0zidwbxc4"))))
    (properties `((upstream-name . "daff")))
    (build-system r-build-system)
    (propagated-inputs (list r-v8 r-jsonlite))
    (home-page "https://github.com/edwindj/daff")
    (synopsis "Diff, Patch and Merge for Data.frames")
    (description
     "Diff, patch and merge for data frames.  Document changes in data sets and use
them to apply patches.  Changes to data can be made visible by using
render_diff().  The V8 package is used to wrap the daff.js @code{JavaScript}
library which is included in the package.")
    (license license:expat)))

(define-public r-daewr
  (package
    (name "r-daewr")
    (version "1.2-11")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "daewr" version))
       (sha256
        (base32 "0hh7z0sdynrw4746hqvyra4dsqa9p1j8bip7b8asyvdpirxhvh23"))))
    (properties `((upstream-name . "daewr")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi r-lattice))
    (home-page "https://cran.r-project.org/package=daewr")
    (synopsis "Design and Analysis of Experiments with R")
    (description
     "This package contains Data frames and functions used in the book \"Design and
Analysis of Experiments with R\", Lawson(2015) ISBN-13:978-1-4398-6813-3.")
    (license license:gpl2)))

(define-public r-dados
  (package
    (name "r-dados")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dados" version))
       (sha256
        (base32 "1jdna8s10qz50zrsrm36y1jx489sznd86akx2lwdmriiiz3abn65"))))
    (properties `((upstream-name . "dados")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-tidyr
                             r-tibble
                             r-rlang
                             r-pixarfilms
                             r-palmerpenguins
                             r-nycflights13
                             r-nasaweather
                             r-lahman
                             r-ggplot2
                             r-gapminder
                             r-fueleconomy
                             r-forcats
                             r-dplyr
                             r-babynames
                             r-ameshousing))
    (home-page "https://github.com/cienciadedatos/dados")
    (synopsis "Translate Datasets to Portuguese")
    (description
     "Este pacote traduz os seguintes conjuntos de dados: airlines', airports',
ames_raw', @code{AwardsManagers}', babynames', Batting', diamonds', faithful',
fueleconomy', Fielding', flights', gapminder', gss_cat', iris', Managers', mpg',
mtcars', atmos', penguins', People, Pitching', pixarfilms','planes',
presidential', table1', table2', table3', table4a', table4b', table5',
vehicles', weather', who'.  English: It provides a Portuguese translated version
of the datasets listed above.")
    (license license:gpl3)))

(define-public r-dadjokeapi
  (package
    (name "r-dadjokeapi")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dadjokeapi" version))
       (sha256
        (base32 "143xs3nkf6ynr83z5gggz318nvpnsbfmskl1ipavlzrqk785dlac"))))
    (properties `((upstream-name . "dadjokeapi")))
    (build-system r-build-system)
    (propagated-inputs (list r-png r-httr r-dplyr r-curl r-beepr))
    (home-page "https://github.com/jhollist/dadjokeapi/")
    (synopsis "Return a Random Dad Joke")
    (description
     "What is funnier than a dad joke? A dad joke in R! This package utilizes the API
for <https://icanhazdadjoke.com> and returns dad jokes from several API
endpoints.")
    (license license:expat)))

(define-public r-dadjoke
  (package
    (name "r-dadjoke")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dadjoke" version))
       (sha256
        (base32 "118pacwc2qb3c5zbhr71zf4zj1ab2g4rs5h6bvrscjyd7a71jc3f"))))
    (properties `((upstream-name . "dadjoke")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=dadjoke")
    (synopsis "Displays a Dad Joke")
    (description "Displays a terrible joke, the kind only dads crack.")
    (license license:gpl2)))

(define-public r-dad
  (package
    (name "r-dad")
    (version "4.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dad" version))
       (sha256
        (base32 "12jwfa1849mfjwplc57qw3lhn5zrqjrlxhisg9hykvhcpj6i0nfl"))))
    (properties `((upstream-name . "dad")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2 r-e1071 r-desctools))
    (native-inputs (list r-knitr))
    (home-page "https://forgemia.inra.fr/dad/dad")
    (synopsis "Three-Way / Multigroup Data Analysis Through Densities")
    (description
     "The data consist of a set of variables measured on several groups of
individuals.  To each group is associated an estimated probability density
function.  The package provides tools to create or manage such data and
functional methods (principal component analysis, multidimensional scaling,
cluster analysis, discriminant analysis...) for such probability densities.")
    (license license:gpl2+)))

(define-public r-dacf
  (package
    (name "r-dacf")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DACF" version))
       (sha256
        (base32 "0hv7c9lk6ivj4iz953yn11iy5p611q4si4ghn9d5a9i229s5hig8"))))
    (properties `((upstream-name . "DACF")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=DACF")
    (synopsis "Data Analysis with Ceiling and/or Floor Data")
    (description
     "An implementation of data analytic methods in R for analyses for data with
ceiling/floor effects.  The package currently includes functions for
mean/variance estimation and mean comparison tests.  Implemented methods are
from Aitkin (1964) <doi:10.1007/BF02289723> and Liu & Wang (in prep).")
    (license license:gpl2)))

(define-public r-dacc
  (package
    (name "r-dacc")
    (version "0.0-5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dacc" version))
       (sha256
        (base32 "19gk3dgkhr6vzyh6bravanzbvykhnp6yippicx7wmcdwi9mhzqvb"))))
    (properties `((upstream-name . "dacc")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp
                             r-pracma
                             r-ncdf4
                             r-mass
                             r-magrittr
                             r-janitor
                             r-iso
                             r-cftime))
    (home-page "https://github.com/LiYanStat/dacc")
    (synopsis "Detection and Attribution Analysis of Climate Change")
    (description
     "Conduct detection and attribution of climate change using methods including
optimal fingerprinting via generalized total least squares or estimating
equation approach from Ma et al. (2023) <doi:10.1175/JCLI-D-22-0681.1>.  Provide
shrinkage estimators for covariance matrix from Ledoit and Wolf (2004)
<doi:10.1016/S0047-259X(03)00096-4>, and Ledoit and Wolf (2017)
<doi:10.2139/ssrn.2383361>.")
    (license license:gpl3+)))

(define-public r-dabr
  (package
    (name "r-dabr")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dabr" version))
       (sha256
        (base32 "14q8frsg8qk46yldawh58cjm4v10im4ar5r5f4yfdxf6jdaadfih"))))
    (properties `((upstream-name . "dabr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-rmariadb r-magrittr r-knitr))
    (home-page "https://github.com/special-uor/dabr/")
    (synopsis "Database Management with R")
    (description
     "This package provides functions to manage databases: select, update, insert, and
delete records, list tables, backup tables as CSV files, and import CSV files as
tables.")
    (license license:gpl3)))

(define-public r-dabestr
  (package
    (name "r-dabestr")
    (version "2023.9.12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "dabestr" version))
       (sha256
        (base32 "0fm6gk1q86nkls2y3zcklszqb570jcll9hfn2mpd4b4qj2vl2d4x"))))
    (properties `((upstream-name . "dabestr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-scales
                             r-rlang
                             r-magrittr
                             r-ggsci
                             r-ggplot2
                             r-ggbeeswarm
                             r-effsize
                             r-dplyr
                             r-cowplot
                             r-cli
                             r-brunnermunzel
                             r-boot))
    (native-inputs (list r-knitr r-kableextra))
    (home-page "https://github.com/ACCLAB/dabestr")
    (synopsis "Data Analysis using Bootstrap-Coupled Estimation")
    (description
     "Data Analysis using Bootstrap-Coupled ESTimation.  Estimation statistics is a
simple framework that avoids the pitfalls of significance testing.  It uses
familiar statistical concepts: means, mean differences, and error bars.  More
importantly, it focuses on the effect size of one's experiment/intervention, as
opposed to a false dichotomy engendered by P values.  An estimation plot has two
key features: 1.  It presents all datapoints as a swarmplot, which orders each
point to display the underlying distribution.  2.  It presents the effect size
as a bootstrap 95% confidence interval on a separate but aligned axes.
Estimation plots are introduced in Ho et al., Nature Methods 2019, 1548-7105.
<doi:10.1038/s41592-019-0470-3>.  The free-to-view PDF is located at
<https://www.nature.com/articles/s41592-019-0470-3.epdf?author_access_token=Euy6API@code{TxsYA3huBKOFBvNRgN0jAjWel9jnR3ZoTv0Pr6zJiJ3AA5aH4989gOJS_dajtNr1Wt17D0fh-t4GFcvqwMYN03qb8C33na_UrCUcGrt-Z0J9aPL6TPSbOxIC-pbHWKUDo2XsUOr3hQmlRew%3D%3D>}.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-daarem
  (package
    (name "r-daarem")
    (version "0.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "daarem" version))
       (sha256
        (base32 "1pm8nj4ffc18njpr87hb988j551zp0s6ysr37nk784ibk4awxf7x"))))
    (properties `((upstream-name . "daarem")))
    (build-system r-build-system)
    (home-page "https://doi.org/10.1080/10618600.2019.1594835")
    (synopsis
     "Damped Anderson Acceleration with Epsilon Monotonicity for Accelerating EM-Like Monotone Algorithms")
    (description
     "This package implements the DAAREM method for accelerating the convergence of
slow, monotone sequences from smooth, fixed-point iterations such as the EM
algorithm.  For further details about the DAAREM method, see Henderson, N.C. and
Varadhan, R. (2019) <doi:10.1080/10618600.2019.1594835>.")
    (license license:gpl2)))

(define-public r-daagbio
  (package
    (name "r-daagbio")
    (version "0.63-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DAAGbio" version))
       (sha256
        (base32 "03lkq84x3skhvcrbs7235jlrhcnszk0pgziik4z93gy1qngrshn2"))))
    (properties `((upstream-name . "DAAGbio")))
    (build-system r-build-system)
    (propagated-inputs (list r-limma))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jhmaindonald/DAAGbio/")
    (synopsis
     "Data Sets and Functions, for Demonstrations with Expression Arrays and Gene Sequences")
    (description
     "Data sets and functions, for the display of gene expression array (microarray)
data, and for demonstrations with such data.")
    (license license:gpl2+)))

(define-public r-daag
  (package
    (name "r-daag")
    (version "1.25.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DAAG" version))
       (sha256
        (base32 "0vm4r1ds2xxxf4vml6mrb5alnkr72a08nby88h3qk7xalny28xkf"))))
    (properties `((upstream-name . "DAAG")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-latticeextra r-lattice))
    (native-inputs (list r-knitr))
    (home-page "https://gitlab.com/daagur/DAAG")
    (synopsis "Data Analysis and Graphics Data and Functions")
    (description
     "This package provides functions and data sets used in examples and exercises in
the text Maindonald, J.H. and Braun, W.J. (2003, 2007, 2010) \"Data Analysis and
Graphics Using R\", and in an upcoming Maindonald, Braun, and Andrews text that
builds on this earlier text.")
    (license license:gpl3)))

(define-public r-da
  (package
    (name "r-da")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "DA" version))
       (sha256
        (base32 "0bcx6lh93yl1cawrbrkqx7dypypvfnf27nlxf9vkz16n1hy50xnl"))))
    (properties `((upstream-name . "DA")))
    (build-system r-build-system)
    (propagated-inputs (list r-rarpack
                             r-plotly
                             r-mass
                             r-lfda
                             r-klar
                             r-kernlab
                             r-adegenet))
    (native-inputs (list r-knitr))
    (home-page "https://xinghuq.github.io/DA/index.html")
    (synopsis "Discriminant Analysis for Evolutionary Inference")
    (description
     "Discriminant Analysis (DA) for evolutionary inference (Qin, X. et al, 2020,
<doi:10.22541/au.159256808.83862168>), especially for population genetic
structure and community structure inference.  This package incorporates the
commonly used linear and non-linear, local and global supervised learning
approaches (discriminant analysis), including Linear Discriminant Analysis of
Kernel Principal Components (LDAKPC), Local (Fisher) Linear Discriminant
Analysis (LFDA), Local (Fisher) Discriminant Analysis of Kernel Principal
Components (LFDAKPC) and Kernel Local (Fisher) Discriminant Analysis (KLFDA).
These discriminant analyses can be used to do ecological and evolutionary
inference, including demography inference, species identification, and
population/community structure inference.")
    (license license:gpl3)))

(define-public r-d4talink-light
  (package
    (name "r-d4talink-light")
    (version "2.1.14")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "D4TAlink.light" version))
       (sha256
        (base32 "1cpvi5jzlyvwygyzv4smi3qcr3gx85s7bfjspsfkz9011aqb1aci"))))
    (properties `((upstream-name . "D4TAlink.light")))
    (build-system r-build-system)
    (propagated-inputs (list r-rmarkdown r-openssl r-jsonlite))
    (native-inputs (list r-knitr))
    (home-page "https://bitbucket.org/SQ4/d4talink.light")
    (synopsis "FAIR Data - Workflow Management")
    (description
     "Tools, methods and processes for the management of analysis workflows.  These
lightweight solutions facilitate structuring R&D activities.  These solutions
were developed to comply with FAIR principles as discussed by Jacobsen et al.
(2017) <doi:10.1162/dint_r_00024>, and with ALCOA+ principles as proposed by the
U.S. FDA.")
    (license license:gpl3)))

(define-public r-d4storagehub4r
  (package
    (name "r-d4storagehub4r")
    (version "0.4-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "d4storagehub4R" version))
       (sha256
        (base32 "0ixv8wypcvcrn3xig8sg54mizsll4v2665l8hqd1q15d0ln2p789"))))
    (properties `((upstream-name . "d4storagehub4R")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-xml
                             r-r6
                             r-keyring
                             r-jsonlite
                             r-httr))
    (home-page "https://github.com/eblondel/d4storagehub4R")
    (synopsis "Interface to 'D4Science' 'StorageHub' API")
    (description
     "This package provides an interface to D4Science @code{StorageHub} API
(<https://dev.d4science.org/>).  Allows to get user profile, and perform actions
over the @code{StorageHub} (workspace) including creation of folders, files
management (upload/update/deletion/sharing), and listing of stored resources.")
    (license license:expat)))

(define-public r-d3tree
  (package
    (name "r-d3tree")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "d3Tree" version))
       (sha256
        (base32 "13qvwmv5nfiv0c3545f2jlhmvgavqnc0jclvm5razjs4hv4kai7i"))))
    (properties `((upstream-name . "d3Tree")))
    (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-tidyselect r-tibble r-htmlwidgets r-dplyr))
    (native-inputs (list esbuild))
    (home-page "https://github.com/yonicd/d3Tree")
    (synopsis
     "Create Interactive Collapsible Trees with the JavaScript 'D3' Library")
    (description
     "Create and customize interactive collapsible D3 trees using the D3
@code{JavaScript} library and the htmlwidgets package.  These trees can be used
directly from the R console, from RStudio', in Shiny apps and R Markdown
documents.  When in Shiny the tree layout is observed by the server and can be
used as a reactive filter of structured data.")
    (license license:expat)))

(define-public r-d3po
  (package
    (name "r-d3po")
    (version "0.5.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "d3po" version))
       (sha256
        (base32 "1fyk0152x9zsbf7qm02wixrk9fldl0jlrg33fnbx06jjg1s431r7"))))
    (properties `((upstream-name . "d3po")))
    (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-rlang
                             r-purrr
                             r-magrittr
                             r-htmlwidgets
                             r-dplyr
                             r-assertthat))
    (native-inputs (list r-knitr esbuild))
    (home-page "https://pacha.dev/d3po/")
    (synopsis
     "Fast and Beautiful Interactive Visualization for 'Markdown' and 'Shiny'")
    (description
     "Apache licensed alternative to Highcharter which provides functions for both
fast and beautiful interactive visualization for Markdown and Shiny'.")
    (license license:asl2.0)))

(define-public r-d3plus
  (package
    (name "r-d3plus")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "d3plus" version))
       (sha256
        (base32 "0kadz83pals03n0v3zqhmhf6visigk52yn58xckhb57fid4xzj5w"))))
    (properties `((upstream-name . "d3plus")))
    (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-magrittr r-htmlwidgets))
    (native-inputs (list esbuild))
    (home-page "https://cran.r-project.org/package=d3plus")
    (synopsis "Seamless 'D3Plus' Integration")
    (description
     "This package provides functions that offer seamless D3Plus integration.  The
examples provided here are taken from the official D3Plus website
<http://d3plus.org>.")
    (license license:expat)))

(define-public r-d3partitionr
  (package
    (name "r-d3partitionr")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "D3partitionR" version))
       (sha256
        (base32 "10067rdgbpjzgw2wiq75kdd0gd7bl41hp16sxc0k2p72ybqfpw03"))))
    (properties `((upstream-name . "D3partitionR")))
    (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-titanic
                             r-rcolorbrewer
                             r-magrittr
                             r-htmlwidgets
                             r-functional
                             r-data-table))
    (native-inputs (list esbuild))
    (home-page "https://cran.r-project.org/package=D3partitionR")
    (synopsis
     "Interactive Charts of Nested and Hierarchical Data with 'D3.js'")
    (description
     "Builds interactive d3.js hierarchical visualisation easily.  D3@code{partitionR}
makes it easy to build and customize sunburst, circle treemap, treemap,
partition chart, ...")
    (license license:agpl3)))

(define-public r-d3mirt
  (package
    (name "r-d3mirt")
    (version "2.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "D3mirt" version))
       (sha256
        (base32 "0mdiirc0k8hlqyj9fq62bpgin6nk2jl604qdrcfh2ympwkm54iz6"))))
    (properties `((upstream-name . "D3mirt")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgl r-mirt))
    (native-inputs (list r-r-rsp))
    (home-page "https://github.com/ForsbergPyschometrics/D3mirt")
    (synopsis "Descriptive 3D Multidimensional Item Response Theory Modelling")
    (description
     "For identifying, estimating, and plotting descriptive multidimensional item
response theory models, restricted to 3D and dichotomous or polytomous data that
fit the two-parameter logistic model or the graded response model.  The method
is foremost explorative and centered around the plot function that exposes item
characteristics and constructs, represented by vector arrows, located in a
three-dimensional interactive latent space.  The results can be useful for
item-level analysis as well as test development.")
    (license license:gpl3+)))

(define-public r-d3gb
  (package
    (name "r-d3gb")
    (version "2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "D3GB" version))
       (sha256
        (base32 "0g86nyfrhqbnlvls2l5ppi2zlij2wpg6zq83qrllzzrh28qx0rjk"))))
    (properties `((upstream-name . "D3GB")))
    (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-rsqlite r-dbi r-base64enc))
    (native-inputs (list esbuild))
    (home-page "http://d3gb.usal.es")
    (synopsis "Interactive Genome Browser")
    (description
     "This package creates interactive genome browser.  It joins the data analysis
power of R and the visualization libraries of @code{JavaScript} in one package.
Barrios, D. & Prieto, C. (2017) <doi:10.1089/cmb.2016.0213>.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-d2mcs
  (package
    (name "r-d2mcs")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "D2MCS" version))
       (sha256
        (base32 "0rjfjnh8gcbm83cwqk1yjrjv6jsrarr53c629bkg9zw7s5sm35nz"))))
    (properties `((upstream-name . "D2MCS")))
    (build-system r-build-system)
    (propagated-inputs (list r-varhandle
                             r-tictoc
                             r-recipes
                             r-r6
                             r-questionr
                             r-modelmetrics
                             r-mltools
                             r-mccr
                             r-infotheo
                             r-gridextra
                             r-ggrepel
                             r-ggplot2
                             r-fselector
                             r-dplyr
                             r-devtools
                             r-caret))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/drordas/D2MCS")
    (synopsis "Data Driving Multiple Classifier System")
    (description
     "This package provides a novel framework to able to automatically develop and
deploy an accurate Multiple Classifier System based on the feature-clustering
distribution achieved from an input dataset.  D2MCS was developed focused on
four main aspects: (i) the ability to determine an effective method to evaluate
the independence of features, (ii) the identification of the optimal number of
feature clusters, (iii) the training and tuning of ML models and (iv) the
execution of voting schemes to combine the outputs of each classifier comprising
the Multiple Classifier System.")
    (license license:gpl3)))

