(define-module (guix-cran packages o)
  #:use-module (guix packages)
  #:use-module (guix download)
  #:use-module (guix build-system r)
  #:use-module ((guix licenses)
                #:prefix license:)
  #:use-module (gnu packages statistics)
  #:use-module (gnu packages cran)
  #:use-module (gnu packages gcc)
  #:use-module (gnu packages bioconductor)
  #:use-module (gnu packages version-control)
  #:use-module (gnu packages java)
  #:use-module (gnu packages pkg-config)
  #:use-module (gnu packages compression)
  #:use-module (gnu packages haskell-xyz)
  #:use-module (gnu packages imagemagick)
  #: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 n)
  #:use-module (guix-cran packages m)
  #:use-module (guix-cran packages l)
  #:use-module (guix-cran packages k)
  #:use-module (guix-cran packages j)
  #:use-module (guix-cran packages i)
  #:use-module (guix-cran packages h)
  #:use-module (guix-cran packages g)
  #:use-module (guix-cran packages f)
  #:use-module (guix-cran packages e)
  #:use-module (guix-cran packages d)
  #:use-module (guix-cran packages c)
  #:use-module (guix-cran packages b)
  #:use-module (guix-cran packages a))

(define-public r-ozmaps
  (package
    (name "r-ozmaps")
    (version "0.4.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ozmaps" version))
       (sha256
        (base32 "0sqxaiw1mdcg81228g7k7r6fla6d7hfk9ax2z6pws8457xbvrzka"))))
    (properties `((upstream-name . "ozmaps")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-sf r-oz))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mdsumner/ozmaps")
    (synopsis "Australia Maps")
    (description
     "Maps of Australian coastline and administrative regions.  Data can be drawn or
accessed directly as simple features objects.  Includes simple functions for
country or state maps of Australia and in-built data sets of administrative
regions from the Australian Bureau of Statistics <https://www.abs.gov.au/>.
Layers include electoral divisions and local government areas, simplified from
the original sources but with sufficient detail to allow mapping of a local
municipality.")
    (license license:gpl3)))

(define-public r-oz
  (package
    (name "r-oz")
    (version "1.0-22")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oz" version))
       (sha256
        (base32 "042f2pplhwj6q7n87qk6r2xcriif76ywyf4mcx3xsr2fjislajw9"))))
    (properties `((upstream-name . "oz")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=oz")
    (synopsis "Plot the Australian Coastline and States")
    (description
     "This package provides functions for plotting Australia's coastline and state
boundaries.")
    (license license:gpl2)))

(define-public r-oyster
  (package
    (name "r-oyster")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oysteR" version))
       (sha256
        (base32 "11zg959h9104hh8wid4003s8c4z9xhmicj39cc5vq1j8g1g7ilr7"))))
    (properties `((upstream-name . "oysteR")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-rjson
                             r-purrr
                             r-jsonlite
                             r-httr
                             r-glue
                             r-dplyr
                             r-cli))
    (home-page "https://github.com/sonatype-nexus-community/oysteR")
    (synopsis "Scans R Projects for Vulnerable Third Party Dependencies")
    (description
     "Collects a list of your third party R packages, and scans them with the OSS
Index provided by Sonatype', reporting back on any vulnerabilities that are
found in the third party packages you use.")
    (license (list license:asl2.0
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-oxybs
  (package
    (name "r-oxybs")
    (version "1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OxyBS" version))
       (sha256
        (base32 "11l3gm0jvw993jb13f6kpv77m6z0d1jswscma2v28qzkw053r3dc"))))
    (properties `((upstream-name . "OxyBS")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=OxyBS")
    (synopsis "Processing of Oxy-Bisulfite Microarray Data")
    (description
     "This package provides utilities for processing of Oxy-Bisulfite microarray data
(e.g. via the Illumina Infinium platform, <http://www.illumina.com>) with tandem
arrays, one using conventional bisulfite conversion, the other using
oxy-bisulfite conversion.")
    (license license:gpl2+)))

(define-public r-oxcaar
  (package
    (name "r-oxcaar")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oxcAAR" version))
       (sha256
        (base32 "1szifw978qr7v8n178jhg4ap2jwvfnwjl2izbbiydwx8q1fyj2q4"))))
    (properties `((upstream-name . "oxcAAR")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-stringi r-jsonlite))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=oxcAAR")
    (synopsis "Interface to 'OxCal' Radiocarbon Calibration")
    (description
     "This package provides a set of tools that enables using @code{OxCal} from within
R. @code{OxCal} (<https://c14.arch.ox.ac.uk/oxcal.html>) is a standard
archaeological tool intended to provide 14C calibration and analysis of
archaeological and environmental chronological information. @code{OxcAAR} allows
simple calibration with Oxcal and plotting of the results as well as the
execution of sophisticated ('@code{OxCal}') code and the import of the results
of bulk analysis and complex Bayesian sequential calibration.")
    (license (list license:gpl2
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-ox
  (package
    (name "r-ox")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ox" version))
       (sha256
        (base32 "0j0va301bmppvmk6paqaqqaw85h8yf92i3pz7i59f2j8q9im82rx"))))
    (properties `((upstream-name . "ox")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ox")
    (synopsis "Shorthand if-Else")
    (description
     "Short hand if-else function to easily switch the values depending on a logical
condition.")
    (license license:gpl2+)))

(define-public r-ows4r
  (package
    (name "r-ows4r")
    (version "0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ows4R" version))
       (sha256
        (base32 "0isp6f4q900yzx2fbm3nflm7ngpvycz33a6i1zilcjxsbyjkhxxk"))))
    (properties `((upstream-name . "ows4R")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml
                             r-terra
                             r-sf
                             r-r6
                             r-openssl
                             r-keyring
                             r-httr
                             r-geometa
                             r-crayon))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/eblondel/ows4R")
    (synopsis "Interface to OGC Web-Services (OWS)")
    (description
     "This package provides an Interface to Web-Services defined as standards by the
Open Geospatial Consortium (OGC), including Web Feature Service (WFS) for vector
data, Web Coverage Service (WCS), Catalogue Service (CSW) for ISO/OGC metadata,
Web Processing Service (WPS) for data processes, and associated standards such
as the common web-service specification (OWS) and OGC Filter Encoding.  Partial
support is provided for the Web Map Service (WMS).  The purpose is to add
support for additional OGC service standards such as Web Coverage Processing
Service (WCPS), the Sensor Observation Service (SOS), or even new standard
services emerging such OGC API or @code{SensorThings}.")
    (license license:expat)))

(define-public r-owmr
  (package
    (name "r-owmr")
    (version "0.8.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "owmr" version))
       (sha256
        (base32 "0qlb5aw6n06yf8y2gd2fjp8kp3w0xgqh3fka7rxqndgvaqmin1a6"))))
    (properties `((upstream-name . "owmr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-plyr
                             r-magrittr
                             r-jsonlite
                             r-httr))
    (home-page "https://github.com/crazycapivara/owmr/")
    (synopsis "OpenWeatherMap API Wrapper")
    (description
     "Accesses @code{OpenWeatherMap's} (owm) <https://openweathermap.org/> API. owm
itself is a service providing weather data in the past, in the future and now.
Furthermore, owm serves weather map layers usable in frameworks like leaflet'.
In order to access the API, you need to sign up for an API key.  There are free
and paid plans.  Beside functions for fetching weather data from owm', owmr
supplies tools to tidy up fetched data (for fast and simple access) and to show
it on leaflet maps.")
    (license license:expat)))

(define-public r-owidr
  (package
    (name "r-owidr")
    (version "1.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "owidR" version))
       (sha256
        (base32 "07l2398xlm2w8pi2az11wvahiq2sy7wpidmvcwplxb10c8pj29gy"))))
    (properties `((upstream-name . "owidR")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-rvest
                             r-purrr
                             r-magrittr
                             r-jsonlite
                             r-httr
                             r-data-table
                             r-curl))
    (home-page "<https://github.com/piersyork/owidR>")
    (synopsis "Import Data from Our World in Data")
    (description
     "Import data from Our World in Data', an organisation which publishes research
and data on global economic and social issues.")
    (license license:expat)))

(define-public r-owenq
  (package
    (name "r-owenq")
    (version "1.0.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OwenQ" version))
       (sha256
        (base32 "0az36s6vrnfa93w12549v9zf6q9xg0a4kvrq5hnkaqxl314zaz1y"))))
    (properties `((upstream-name . "OwenQ")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcppnumerical r-rcppeigen r-rcpp r-bh))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/stla/OwenQ")
    (synopsis "Owen Q-Function")
    (description
     "Evaluates the Owen Q-function for an integer value of the degrees of freedom, by
applying Owen's algorithm (1965) <doi:10.1093/biomet/52.3-4.437>.  It is useful
for the calculation of the power of equivalence tests.")
    (license license:bsd-3)))

(define-public r-owea
  (package
    (name "r-owea")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OWEA" version))
       (sha256
        (base32 "05h3aj074manlwnlzqp023zkql6gmsm9p1nfs6zki7ifdd83wj7m"))))
    (properties `((upstream-name . "OWEA")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-mass r-gtools))
    (home-page "https://cran.r-project.org/package=OWEA")
    (synopsis
     "Optimal Weight Exchange Algorithm for Optimal Designs for Three Models")
    (description
     "An implementation of optimal weight exchange algorithm Yang(2013)
<doi:10.1080/01621459.2013.806268> for three models.  They are Crossover model
with subject dropout, crossover model with proportional first order residual
effects and interference model.  You can use it to find either A-opt or D-opt
approximate designs.  Exact designs can be automatically rounded from
approximate designs and relative efficiency is provided as well.")
    (license license:gpl3)))

(define-public r-owdbr
  (package
    (name "r-owdbr")
    (version "1.0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "owdbr" version))
       (sha256
        (base32 "0q4654zr5aw04sssy7127vafry72b7p3d8i44fqvqg3055awin0i"))))
    (properties `((upstream-name . "owdbr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-magrittr
                             r-jsonlite
                             r-httr
                             r-dplyr
                             r-data-table))
    (home-page "https://github.com/kimjoaoun/owdbr")
    (synopsis "Open Welfare Data Brazil")
    (description
     "This package provides tools for collecting municipal-level data
<http://www.transparencia.gov.br/swagger-ui.html> from several Brazilian
governmental social programs.")
    (license license:expat)))

(define-public r-owd
  (package
    (name "r-owd")
    (version "1.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "owd" version))
       (sha256
        (base32 "08f1zzlnkfdzm5rlw14qm6yvn68j2yas21zjsy31pc59rh3lzkyh"))))
    (properties `((upstream-name . "owd")))
    (build-system r-build-system)
    (home-page "https://github.com/Feakster/owd")
    (synopsis "Open Working Directory")
    (description
     "Open the current working directory (or a given directory path) in your
computer's file manager.")
    (license license:expat)))

(define-public r-ovtool
  (package
    (name "r-ovtool")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OVtool" version))
       (sha256
        (base32 "1ghfbvnfl092g0kikgjghgf0l1y7ihqykssfvvfi6q6pgzl8kz4y"))))
    (properties `((upstream-name . "OVtool")))
    (build-system r-build-system)
    (propagated-inputs (list r-varhandle
                             r-twang
                             r-tidyselect
                             r-tibble
                             r-survey
                             r-rlang
                             r-purrr
                             r-progress
                             r-metr
                             r-magrittr
                             r-glue
                             r-ggrepel
                             r-ggplot2
                             r-envstats
                             r-dplyr
                             r-devtools
                             r-amelia))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OVtool")
    (synopsis "Omitted Variable Tool")
    (description
     "This tool was designed to assess the sensitivity of research findings to omitted
variables when estimating causal effects using propensity score (PS) weighting.
This tool produces graphics and summary results that will enable a researcher to
quantify the impact an omitted variable would have on their results.  Burgette
et al. (2021) describe the methodology behind the primary function in this
package, ov_sim.  The method is demonstrated in Griffin et al. (2020)
<doi:10.1016/j.jsat.2020.108075>.")
    (license license:gpl3)))

(define-public r-ovl-ci
  (package
    (name "r-ovl-ci")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OVL.CI" version))
       (sha256
        (base32 "17ksnsj68snxwm5ibjq3zchmybs7a3zq9ack0blhi4cbsx7xd5ds"))))
    (properties `((upstream-name . "OVL.CI")))
    (build-system r-build-system)
    (propagated-inputs (list r-ks))
    (home-page "https://cran.r-project.org/package=OVL.CI")
    (synopsis
     "Inference on the Overlap Coefficient: The Binormal Approach and Alternatives")
    (description
     "This package provides functions to construct confidence intervals for the
Overlap Coefficient (OVL).  OVL measures the similarity between two
distributions through the overlapping area of their distribution functions.
Given its intuitive description and ease of visual representation by the
straightforward depiction of the amount of overlap between the two corresponding
histograms based on samples of measurements from each one of the two
distributions, the development of accurate methods for confidence interval
construction can be useful for applied researchers.  Implements methods based on
the work of Franco-Pereira, A.M., Nakas, C.T., Reiser, B., and Pardo, M.C.
(2021) <doi:10.1177/09622802211046386>.")
    (license license:gpl2)))

(define-public r-overviewr
  (package
    (name "r-overviewr")
    (version "0.0.13")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "overviewR" version))
       (sha256
        (base32 "13g2qjd9421nfmabhs2xx8h393id9c9x1h547r953q7aabjmkr89"))))
    (properties `((upstream-name . "overviewR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-rlang
                             r-ggvenn
                             r-ggrepel
                             r-ggplot2
                             r-dplyr
                             r-data-table))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://github.com/cosimameyer/overviewR")
    (synopsis "Easily Extracting Information About Your Data")
    (description
     "Makes it easy to display descriptive information on a data set.  Getting an easy
overview of a data set by displaying and visualizing sample information in
different tables (e.g., time and scope conditions).  The package also provides
publishable @code{LaTeX} code to present the sample information.")
    (license license:gpl3)))

(define-public r-overturer
  (package
    (name "r-overturer")
    (version "0.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "overtureR" version))
       (sha256
        (base32 "0x4z1dyijw4qrf5g89mskvmxvy01xa94bkdk2ybp2ykfgbh3svcy"))))
    (properties `((upstream-name . "overtureR")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf
                             r-rlang
                             r-glue
                             r-duckdb
                             r-dplyr
                             r-dbplyr
                             r-dbi))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/arthurgailes/overtureR")
    (synopsis
     "Load 'Overture' Datasets as 'dbplyr' and 'sf'-Ready Data Frames")
    (description
     "An integrated R interface to the Overture API
(<https://docs.overturemaps.org/>).  Allows R users to return Overture data as
dbplyr data frames or materialized sf spatial data frames.")
    (license license:expat)))

(define-public r-overturemapsr
  (package
    (name "r-overturemapsr")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "overturemapsr" version))
       (sha256
        (base32 "176vh7gp6ijqb4dqnk3shhrs1q0x3gz0gj1w24a7qrcp5zdp24ff"))))
    (properties `((upstream-name . "overturemapsr")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf r-dplyr r-arrow))
    (home-page "https://cran.r-project.org/package=overturemapsr")
    (synopsis "Download Overture Maps Data in R")
    (description
     "Overture Maps offers free and open geospatial map data sourced from various
providers and standardized to a common schema.  This tool allows you to download
Overture Maps data for a specific region of interest and convert it to several
different file formats.  For more information, visit
<https://overturemaps.org/download/>.")
    (license license:expat)))

(define-public r-overture
  (package
    (name "r-overture")
    (version "0.4-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "overture" version))
       (sha256
        (base32 "1s16x5kn0apb0w1f7hqzcsqvw3x621y5n6yr1qn7yb7431pdw3cz"))))
    (properties `((upstream-name . "overture")))
    (build-system r-build-system)
    (propagated-inputs (list r-bigmemory))
    (home-page "https://github.com/kurtis-s/overture")
    (synopsis "Tools for Writing MCMC")
    (description
     "Simplifies MCMC setup by automatically looping through sampling functions and
saving the results.  Reduces the memory footprint of running MCMC and saves
samples to disk as the chain runs.  Allows samples from the chain to be analyzed
while the MCMC is still running.  Provides functions for commonly performed
operations such as calculating Metropolis acceptance ratios and creating
adaptive Metropolis samplers.  References: Roberts and Rosenthal (2009)
<doi:10.1198/jcgs.2009.06134>.")
    (license license:lgpl3)))

(define-public r-overlapptest
  (package
    (name "r-overlapptest")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "overlapptest" version))
       (sha256
        (base32 "0qvsiwh76isiz3rcrizahp6p35lscrjijidnjwwwpmc0r9pm7xzd"))))
    (properties `((upstream-name . "overlapptest")))
    (build-system r-build-system)
    (propagated-inputs (list r-spatstat-geom))
    (home-page "https://cran.r-project.org/package=overlapptest")
    (synopsis "Test Overlapping of Polygons Against Random Rotation")
    (description
     "Tests the observed overlapping polygon area in a collection of polygons against
a null model of random rotation, as explained in De la Cruz et al. (2017)
<doi:10.13140/RG.2.2.12825.72801>.")
    (license license:gpl2+)))

(define-public r-overlapping
  (package
    (name "r-overlapping")
    (version "2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "overlapping" version))
       (sha256
        (base32 "1dq2xsinl5rh8sf2bayv6xs7x8i0d54c405p8l82ji3xrkz49clf"))))
    (properties `((upstream-name . "overlapping")))
    (build-system r-build-system)
    (propagated-inputs (list r-testthat r-ggplot2))
    (home-page "https://cran.r-project.org/package=overlapping")
    (synopsis "Estimation of Overlapping in Empirical Distributions")
    (description
     "This package provides functions for estimating the overlapping area of two or
more kernel density estimations from empirical data.")
    (license license:gpl2)))

(define-public r-overdisp
  (package
    (name "r-overdisp")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "overdisp" version))
       (sha256
        (base32 "155zkxpv0jqy21winp3r17vnrd6xh2a92glha4d9i2vi541d9kix"))))
    (properties `((upstream-name . "overdisp")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=overdisp")
    (synopsis "Overdispersion in Count Data Multiple Regression Analysis")
    (description
     "Detection of overdispersion in count data for multiple regression analysis.
Log-linear count data regression is one of the most popular techniques for
predictive modeling where there is a non-negative discrete quantitative
dependent variable.  In order to ensure the inferences from the use of count
data models are appropriate, researchers may choose between the estimation of a
Poisson model and a negative binomial model, and the correct decision for
prediction from a count data estimation is directly linked to the existence of
overdispersion of the dependent variable, conditional to the explanatory
variables.  Based on the studies of Cameron and Trivedi (1990)
<doi:10.1016/0304-4076(90)90014-K> and Cameron and Trivedi (2013,
ISBN:978-1107667273), the overdisp() command is a contribution to researchers,
providing a fast and secure solution for the detection of overdispersion in
count data.  Another advantage is that the installation of other packages is
unnecessary, since the command runs in the basic R language.")
    (license license:gpl2+)))

(define-public r-ouwie
  (package
    (name "r-ouwie")
    (version "2.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OUwie" version))
       (sha256
        (base32 "19bh0vb7azxpzrjw2829gcjcq91fnzb5ybhkp3fsvg9xccmjq9dg"))))
    (properties `((upstream-name . "OUwie")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer
                             r-phytools
                             r-phylolm
                             r-phangorn
                             r-paleotree
                             r-numderiv
                             r-nloptr
                             r-lhs
                             r-interp
                             r-igraph
                             r-geiger
                             r-corpcor
                             r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/thej022214/OUwie")
    (synopsis "Analysis of Evolutionary Rates in an OU Framework")
    (description
     "Estimates rates for continuous character evolution under Brownian motion and a
new set of Ornstein-Uhlenbeck based Hansen models that allow both the strength
of the pull and stochastic motion to vary across selective regimes.  Beaulieu et
al (2012).")
    (license license:gpl2+)))

(define-public r-outreg
  (package
    (name "r-outreg")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "outreg" version))
       (sha256
        (base32 "04f1x7mxq4swbd7bfwjjgx4838jm6qj4piaighmhcscwrdkxa1cp"))))
    (properties `((upstream-name . "outreg")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-stringr r-sandwich r-reshape2
                             r-magrittr))
    (home-page "https://github.com/kota7/outreg")
    (synopsis "Regression Table for Publication")
    (description
     "Create regression tables for publication.  Currently supports lm', glm',
survreg', and ivreg outputs.")
    (license license:expat)))

(define-public r-outqrf
  (package
    (name "r-outqrf")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "outqrf" version))
       (sha256
        (base32 "0gl3ix39kx7n1akg1789nfqg84jxq5q9qdxwcmf8ch7zklbkgccb"))))
    (properties `((upstream-name . "outqrf")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-ranger
                             r-missranger
                             r-ggpubr
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/flystar233/outqrf")
    (synopsis "Find the Outlier by Quantile Random Forests")
    (description
     "This package provides a method to find the outlier in custom data by quantile
random forests method.  Introduced by Meinshausen Nicolai (2006)
<https://dl.acm.org/doi/10.5555/1248547.1248582>.  It directly calls the
ranger() function of the ranger package to perform data fitting and prediction.
We also implement the evaluation of outlier prediction results.  Compared with
random forest detection of outliers, this method has higher accuracy and
stability on large datasets.")
    (license license:expat)))

(define-public r-outliertree
  (package
    (name "r-outliertree")
    (version "1.10.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "outliertree" version))
       (sha256
        (base32 "13z39pfc7fzxil5gc48s7b2f0zal4l4d8qw5xvwy4mlp010mwrc5"))))
    (properties `((upstream-name . "outliertree")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-rcereal))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/david-cortes/outliertree")
    (synopsis
     "Explainable Outlier Detection Through Decision Tree Conditioning")
    (description
     "Outlier detection method that flags suspicious values within observations,
constrasting them against the normal values in a user-readable format,
potentially describing conditions within the data that make a given outlier more
rare.  Full procedure is described in Cortes (2020)
<doi:10.48550/@code{arXiv.2001.00636>}.  Loosely based on the @code{GritBot}
<https://www.rulequest.com/gritbot-info.html> software.")
    (license license:gpl3+)))

(define-public r-outlierso3
  (package
    (name "r-outlierso3")
    (version "0.6.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OutliersO3" version))
       (sha256
        (base32 "165v572w9bnvay9f0xyxzbhgj1i86ndia4rzqy98i48dfdbdb990"))))
    (properties `((upstream-name . "OutliersO3")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-robustx
                             r-robustbase
                             r-rlist
                             r-memisc
                             r-hdoutliers
                             r-ggplot2
                             r-ggally
                             r-forcats
                             r-fastpcs
                             r-dplyr
                             r-cellwise))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OutliersO3")
    (synopsis "Draws Overview of Outliers (O3) Plots")
    (description
     "Potential outliers are identified for all combinations of a dataset's variables.
 O3 plots are described in Unwin(2019) <doi:10.1080/10618600.2019.1575226>.  The
available methods are HDoutliers() from the package HDoutliers',
@code{FastPCS}() from the package @code{FastPCS}', @code{mvBACON}() from
@code{robustX}', @code{adjOutlyingness}() from robustbase',
@code{DectectDeviatingCells}() from @code{cellWise}', @code{covMcd}() from
robustbase'.")
    (license license:gpl2+)))

(define-public r-outlierslearn
  (package
    (name "r-outlierslearn")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OutliersLearn" version))
       (sha256
        (base32 "1qjgi3m8727x40dfx9r36m9mg0jwa99qfwxv5xz29k2mwqknhl47"))))
    (properties `((upstream-name . "OutliersLearn")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OutliersLearn")
    (synopsis
     "Educational Outlier Package with Common Outlier Detection Algorithms")
    (description
     "This package provides implementations of some of the most important outlier
detection algorithms.  Includes a tutorial mode option that shows a description
of each algorithm and provides a step-by-step execution explanation of how it
identifies outliers from the given data with the specified input parameters.
References include the works of Azzedine Boukerche, Lining Zheng, and Omar
Alfandi (2020) <doi:10.1145/3381028>, Abir Smiti (2020)
<doi:10.1016/j.cosrev.2020.100306>, and Xiaogang Su, Chih-Ling Tsai (2011)
<doi:10.1002/widm.19>.")
    (license license:expat)))

(define-public r-outliers-ts-oga
  (package
    (name "r-outliers-ts-oga")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "outliers.ts.oga" version))
       (sha256
        (base32 "1v10v4nw7xkrranv4pa4xqw3cayb1lq2p3qda76w6vxxwfch32pi"))))
    (properties `((upstream-name . "outliers.ts.oga")))
    (build-system r-build-system)
    (propagated-inputs (list r-slbdd
                             r-robust
                             r-parallelly
                             r-gsarima
                             r-forecast
                             r-caret))
    (home-page "https://cran.r-project.org/package=outliers.ts.oga")
    (synopsis
     "Efficient Outlier Detection in Heterogeneous Time Series Databases")
    (description
     "Programs for detecting and cleaning outliers in single time series and in time
series from homogeneous and heterogeneous databases using an Orthogonal Greedy
Algorithm (OGA) for saturated linear regression models.  The programs implement
the procedures presented in the paper entitled \"Efficient outlier detection in
heterogeneous time series databases\" by Pedro Galeano, Daniel PeÃ±a and Ruey S.
Tsay (2024), working paper, Universidad Carlos III de Madrid.")
    (license license:gpl3)))

(define-public r-outlierensembles
  (package
    (name "r-outlierensembles")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "outlierensembles" version))
       (sha256
        (base32 "0m2iaf3rbpwvyrjz6qglbrinmz676hnbqqm6vc38zb3k3cjcllaq"))))
    (properties `((upstream-name . "outlierensembles")))
    (build-system r-build-system)
    (propagated-inputs (list r-psych r-estcrm r-apcluster r-airt))
    (native-inputs (list r-knitr))
    (home-page "https://sevvandi.github.io/outlierensembles/")
    (synopsis "Collection of Outlier Ensemble Algorithms")
    (description
     "Ensemble functions for outlier/anomaly detection.  There is a new ensemble
method proposed using Item Response Theory.  Existing outlier ensemble methods
from Schubert et al (2012) <doi:10.1137/1.9781611972825.90>, Chiang et al (2017)
<doi:10.1016/j.jal.2016.12.002> and Aggarwal and Sathe (2015)
<doi:10.1145/2830544.2830549> are also included.")
    (license license:gpl3+)))

(define-public r-outforest
  (package
    (name "r-outforest")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "outForest" version))
       (sha256
        (base32 "03m3jfbydagv4skpijz1xjhsydfb0ci2n0qz4zigfys6hxhfzg36"))))
    (properties `((upstream-name . "outForest")))
    (build-system r-build-system)
    (propagated-inputs (list r-ranger r-missranger r-fnn))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mayer79/outForest")
    (synopsis "Multivariate Outlier Detection and Replacement")
    (description
     "This package provides a random forest based implementation of the method
described in Chapter 7.1.2 (Regression model based anomaly detection) of
Chandola et al. (2009) <doi:10.1145/1541880.1541882>.  It works as follows: Each
numeric variable is regressed onto all other variables by a random forest.  If
the scaled absolute difference between observed value and out-of-bag prediction
of the corresponding random forest is suspiciously large, then a value is
considered an outlier.  The package offers different options to replace such
outliers, e.g. by realistic values found via predictive mean matching.  Once the
method is trained on a reference data, it can be applied to new data.")
    (license license:gpl2+)))

(define-public r-outcomerate
  (package
    (name "r-outcomerate")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "outcomerate" version))
       (sha256
        (base32 "07mwml7r98qjgvrp938sqf7klyspz110583j0zwb72j69n4whmrj"))))
    (properties `((upstream-name . "outcomerate")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ropensci/outcomerate")
    (synopsis "AAPOR Survey Outcome Rates")
    (description
     "Standardized survey outcome rate functions, including the response rate, contact
rate, cooperation rate, and refusal rate.  These outcome rates allow survey
researchers to measure the quality of survey data using definitions published by
the American Association of Public Opinion Research (AAPOR).  For details on
these standards, see AAPOR (2016)
<https://www.aapor.org/Standards-Ethics/Standard-Definitions-(1).aspx>.")
    (license license:cc0)))

(define-public r-outbreaks
  (package
    (name "r-outbreaks")
    (version "1.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "outbreaks" version))
       (sha256
        (base32 "0x6r4rzcvd1rp8j4brq9c0zl2xsl5jfi18dny20an7aqk310p11v"))))
    (properties `((upstream-name . "outbreaks")))
    (build-system r-build-system)
    (home-page "https://github.com/reconhub/outbreaks")
    (synopsis "Collection of Disease Outbreak Data")
    (description
     "Empirical or simulated disease outbreak data, provided either as RData or as
text files.")
    (license license:gpl2+)))

(define-public r-outbreaker2
  (package
    (name "r-outbreaker2")
    (version "1.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "outbreaker2" version))
       (sha256
        (base32 "06wlmf51ciy7zy5nchfn2myvkwrvq44cnzzjl75vz32ixn8iy56v"))))
    (properties `((upstream-name . "outbreaker2")))
    (build-system r-build-system)
    (propagated-inputs (list r-visnetwork r-rcpp r-magrittr r-ggplot2 r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=outbreaker2")
    (synopsis
     "Bayesian Reconstruction of Disease Outbreaks by Combining Epidemiologic and Genomic Data")
    (description
     "Bayesian reconstruction of disease outbreaks using epidemiological and genetic
information.  Jombart T, Cori A, Didelot X, Cauchemez S, Fraser C and Ferguson
N. 2014. <doi:10.1371/journal.pcbi.1003457>.  Campbell, F, Cori A, Ferguson N,
Jombart T. 2019. <doi:10.1371/journal.pcbi.1006930>.")
    (license license:expat)))

(define-public r-ouladformat
  (package
    (name "r-ouladformat")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ouladFormat" version))
       (sha256
        (base32 "1m8m5nrf2y42yvz9f0j976dvq5jrmyswiznq7iv32bppm0jwz92m"))))
    (properties `((upstream-name . "ouladFormat")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-magrittr r-httr r-dplyr))
    (home-page "https://cran.r-project.org/package=ouladFormat")
    (synopsis
     "Loads and Formats the Open University Learning Analytics Dataset for Data Analysis")
    (description
     "The Open University Learning Analytics Dataset (OULAD) is available from Kuzilek
et al. (2017) <doi:10.1038/sdata.2017.171>.  The @code{ouladFormat} package
loads, cleans and formats the OULAD for data analysis (each row of the returned
data set is an individual student).  The packageâs main function,
combined_dataset(), allows the user to choose whether the returned data set
includes assessment, demographics, virtual learning environment (VLE), or
registration variables etc.")
    (license license:gpl2+)))

(define-public r-otutable
  (package
    (name "r-otutable")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OTUtable" version))
       (sha256
        (base32 "1sm037ihm12xyp7ns5f0c1psflvm1aj3xnsj5nzh2rsjn35hvd6h"))))
    (properties `((upstream-name . "OTUtable")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=OTUtable")
    (synopsis
     "North Temperate Lakes - Microbial Observatory 16S Time Series Data and Functions")
    (description
     "Analyses of OTU tables produced by 16S @code{rRNA} gene amplicon sequencing, as
well as example data.  It contains the data and scripts used in the paper Linz,
et al. (2017) \"Bacterial community composition and dynamics spanning five years
in freshwater bog lakes,\" <doi: 10.1128/@code{mSphere.00169-17>}.")
    (license license:gpl3)))

(define-public r-otusummary
  (package
    (name "r-otusummary")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "otuSummary" version))
       (sha256
        (base32 "0zyjycymdlzszaqns5y2507lpy52dhl82wm4frv8nfy4xcwb3yxy"))))
    (properties `((upstream-name . "otuSummary")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2))
    (home-page "https://github.com/cam315/otuSummary")
    (synopsis
     "Summarizing OTU Table Regarding the Composition, Abundance and Beta Diversity of Abundant and Rare Biospheres")
    (description
     "Summarizes the taxonomic composition, diversity contribution of the rare and
abundant community by using OTU (operational taxonomic unit) table which was
generated by analyzing pipeline of QIIME or mothur'.  The rare biosphere in this
package is subset by the relative abundance threshold (for details about rare
biosphere please see Lynch and Neufeld (2015) <doi:10.1038/nrmicro3400>).")
    (license license:gpl3+)))

(define-public r-ottrpal
  (package
    (name "r-ottrpal")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ottrpal" version))
       (sha256
        (base32 "0wjavfgn9cjk83bsrcj820nxairb5jxszryqzppwwbjf844vi17y"))))
    (properties `((upstream-name . "ottrpal")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-xml2
                             r-stringr
                             r-rvest
                             r-rprojroot
                             r-rmarkdown
                             r-readr
                             r-r-utils
                             r-purrr
                             r-openssl
                             r-magrittr
                             r-knitr
                             r-jsonlite
                             r-httr
                             r-glue
                             r-fs
                             r-dplyr
                             r-curl
                             r-bookdown))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jhudsl/ottrpal")
    (synopsis
     "Companion Tools for Open-Source Tools for Training Resources (OTTR)")
    (description
     "This package provides tools for converting Open-Source Tools for Training
Resources (OTTR) courses into Leanpub or Coursera courses.  ottrpal is for use
with the OTTR Template repository to create courses.")
    (license license:gpl3)))

(define-public r-ottr
  (package
    (name "r-ottr")
    (version "1.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ottr" version))
       (sha256
        (base32 "1b1p957plsx09xfa4qwqk2bnib1hnbikrsdn2cll17b8pfwrp29k"))))
    (properties `((upstream-name . "ottr")))
    (build-system r-build-system)
    (propagated-inputs (list r-zip r-testthat r-r6 r-jsonlite))
    (home-page "https://cran.r-project.org/package=ottr")
    (synopsis "An R Autograding Extension for Otter-Grader")
    (description
     "An R autograding extension for Otter-Grader
(<https://otter-grader.readthedocs.io>).  It supports grading R scripts, R
Markdown documents, and R Jupyter Notebooks.")
    (license license:bsd-3)))

(define-public r-otsfeatures
  (package
    (name "r-otsfeatures")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "otsfeatures" version))
       (sha256
        (base32 "1akny7bdls9ddvkpm906ih9h7bc5sgnj03z7kkzbpy703d1y6krr"))))
    (properties `((upstream-name . "otsfeatures")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-latex2exp r-ggplot2 r-bolstad2 r-astsa))
    (home-page "https://cran.r-project.org/package=otsfeatures")
    (synopsis "Ordinal Time Series Analysis")
    (description
     "An implementation of several functions for feature extraction in ordinal time
series datasets.  Specifically, some of the features proposed by Weiss (2019)
<doi:10.1080/01621459.2019.1604370> can be computed.  These features can be used
to perform inferential tasks or to feed machine learning algorithms for ordinal
time series, among others.  The package also includes some interesting datasets
containing financial time series.  Practitioners from a broad variety of fields
could benefit from the general framework provided by otsfeatures'.")
    (license license:gpl2)))

(define-public r-otrselect
  (package
    (name "r-otrselect")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OTRselect" version))
       (sha256
        (base32 "02aslqz8k10jglxwifn8sm1y3cg10vaq6dd5n15s4nrvcfg53180"))))
    (properties `((upstream-name . "OTRselect")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-lars))
    (home-page "https://cran.r-project.org/package=OTRselect")
    (synopsis "Variable Selection for Optimal Treatment Decision")
    (description
     "This package provides a penalized regression framework that can simultaneously
estimate the optimal treatment strategy and identify important variables.
Appropriate for either censored or uncensored continuous response.")
    (license license:gpl2)))

(define-public r-otrkm
  (package
    (name "r-otrkm")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "otrKM" version))
       (sha256
        (base32 "16zydn1vpxqh0xn6bi5159sjlnqxqvmwwhg9cx016sxfiv579m1z"))))
    (properties `((upstream-name . "otrKM")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-rgenoud))
    (home-page "https://cran.r-project.org/package=otrKM")
    (synopsis
     "Optimal Treatment Regimes in Survival Contexts with Kaplan-Meier-Like Estimators")
    (description
     "Provide methods for estimating optimal treatment regimes in survival contexts
with Kaplan-Meier-like estimators when no unmeasured confounding assumption is
satisfied (Jiang, R., Lu, W., Song, R., and Davidian, M. (2017)
<doi:10.1111/rssb.12201>) and when no unmeasured confounding assumption fails to
hold and a binary instrument is available (Xia, J., Zhan, Z., Zhang, J. (2022)
<@code{arXiv:2210.05538>}).")
    (license license:expat)))

(define-public r-otrimle
  (package
    (name "r-otrimle")
    (version "2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "otrimle" version))
       (sha256
        (base32 "0rca8ln9cyikfpsf1af550cfx2zx110c8jxv64xf8dnnd09s9h7b"))))
    (properties `((upstream-name . "otrimle")))
    (build-system r-build-system)
    (propagated-inputs (list r-robustbase r-mvtnorm r-mclust r-foreach
                             r-doparallel))
    (home-page "https://cran.r-project.org/package=otrimle")
    (synopsis "Robust Model-Based Clustering")
    (description
     "This package performs robust cluster analysis allowing for outliers and noise
that cannot be fitted by any cluster.  The data are modelled by a mixture of
Gaussian distributions and a noise component, which is an improper uniform
distribution covering the whole Euclidean space.  Parameters are estimated by
(pseudo) maximum likelihood.  This is fitted by a EM-type algorithm.  See
Coretto and Hennig (2016) <doi:10.1080/01621459.2015.1100996>, and Coretto and
Hennig (2017) <https://jmlr.org/papers/v18/16-382.html>.")
    (license license:gpl2+)))

(define-public r-otrecod
  (package
    (name "r-otrecod")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OTrecod" version))
       (sha256
        (base32 "1w3w6vsp5v2sccpn0zzjiwcnwmgcindh7wnsnf90qprvjwlys7mw"))))
    (properties `((upstream-name . "OTrecod")))
    (build-system r-build-system)
    (propagated-inputs (list r-vcd
                             r-statmatch
                             r-roi-plugin-glpk
                             r-roi
                             r-rdist
                             r-proxy
                             r-plyr
                             r-party
                             r-ompr-roi
                             r-ompr
                             r-missmda
                             r-mice
                             r-factominer
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OTrecod")
    (synopsis "Data Fusion using Optimal Transportation Theory")
    (description
     "In the context of data fusion, the package provides a set of functions dedicated
to the solving of recoding problems using optimal transportation theory (Gares,
Guernec, Savy (2019) <doi:10.1515/ijb-2018-0106> and Gares, Omer (2020)
<doi:10.1080/01621459.2020.1775615>).  From two databases with no overlapping
part except a subset of shared variables, the functions of the package assist
users until obtaining a unique synthetic database, where the missing information
is fully completed.")
    (license license:gpl3)))

(define-public r-otpr
  (package
    (name "r-otpr")
    (version "0.5.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "otpr" version))
       (sha256
        (base32 "1wh5rmwwwdf1wkb18ayx6zcnhwf80zziznk64jg1974g8crgdxsb"))))
    (properties `((upstream-name . "otpr")))
    (build-system r-build-system)
    (propagated-inputs (list r-urltools
                             r-sf
                             r-rrapply
                             r-rlang
                             r-jsonlite
                             r-janitor
                             r-httr
                             r-geojsonsf
                             r-dplyr
                             r-checkmate))
    (home-page "https://cran.r-project.org/package=otpr")
    (synopsis "An R Wrapper for the 'OpenTripPlanner' REST API")
    (description
     "This package provides a wrapper for the @code{OpenTripPlanner}
<http://www.opentripplanner.org/> REST API. Queries are submitted to the
relevant @code{OpenTripPlanner} API resource, the response is parsed and useful
R objects are returned.")
    (license license:expat)))

(define-public r-otp
  (package
    (name "r-otp")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "otp" version))
       (sha256
        (base32 "19fi2a4gi6fjhhkybrlx9chph2adjqqx4h1mc214cjn6m5bg37mq"))))
    (properties `((upstream-name . "otp")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6 r-openssl r-base64url))
    (home-page "https://github.com/randy3k/otp")
    (synopsis "One Time Password Generation and Verification")
    (description
     "Generating and validating One-time Password based on Hash-based Message
Authentication Code (HOTP) and Time Based One-time Password (TOTP) according to
RFC 4226 <https://datatracker.ietf.org/doc/html/rfc4226> and RFC 6238
<https://datatracker.ietf.org/doc/html/rfc6238>.")
    (license license:expat)))

(define-public r-otinference
  (package
    (name "r-otinference")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "otinference" version))
       (sha256
        (base32 "1l75jjnkyk8yzaw9zyk45jq9ys304i6pzm2xd5apxrb1jk75a3li"))))
    (properties `((upstream-name . "otinference")))
    (build-system r-build-system)
    (propagated-inputs (list r-transport r-sm r-rglpk r-mass))
    (home-page "https://cran.r-project.org/package=otinference")
    (synopsis "Inference for Optimal Transport")
    (description
     "Sample from the limiting distributions of empirical Wasserstein distances under
the null hypothesis and under the alternative.  Perform a two-sample test on
multivariate data using these limiting distributions and binning.")
    (license license:gpl2)))

(define-public r-ote
  (package
    (name "r-ote")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OTE" version))
       (sha256
        (base32 "0jvvrrfhpc5kibbxrd5r4dj97jp5m072fxnkpcyz11gi65db3z4g"))))
    (properties `((upstream-name . "OTE")))
    (build-system r-build-system)
    (propagated-inputs (list r-randomforest))
    (home-page "https://cran.r-project.org/package=OTE")
    (synopsis
     "Optimal Trees Ensembles for Regression, Classification and Class Membership Probability Estimation")
    (description
     "This package provides functions for creating ensembles of optimal trees for
regression, classification (Khan, Z., Gul, A., Perperoglou, A., Miftahuddin, M.,
Mahmoud, O., Adler, W., & Lausen, B. (2019). (2019)
<doi:10.1007/s11634-019-00364-9>) and class membership probability estimation
(Khan, Z, Gul, A, Mahmoud, O, Miftahuddin, M, Perperoglou, A, Adler, W & Lausen,
B (2016) <doi:10.1007/978-3-319-25226-1_34>) are given.  A few trees are
selected from an initial set of trees grown by random forest for the ensemble on
the basis of their individual and collective performance.  Three different
methods of tree selection for the case of classification are given.  The
prediction functions return estimates of the test responses and their class
membership probabilities.  Unexplained variations, error rates, confusion
matrix, Brier scores, etc.  are also returned for the test data.")
    (license license:gpl3+)))

(define-public r-otclust
  (package
    (name "r-otclust")
    (version "1.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OTclust" version))
       (sha256
        (base32 "00609z2fp3ijqid7yjgh045xz038h5jl7i1k2kww3kfpcf40mhzs"))))
    (properties `((upstream-name . "OTclust")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-rcolorbrewer r-magrittr r-ggplot2
                             r-class))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OTclust")
    (synopsis
     "Mean Partition, Uncertainty Assessment, Cluster Validation and Visualization Selection for Cluster Analysis")
    (description
     "Providing mean partition for ensemble clustering by optimal transport
alignment(OTA), uncertainty measures for both partition-wise and cluster-wise
assessment and multiple visualization functions to show uncertainty, for
instance, membership heat map and plot of covering point set.  A partition
refers to an overall clustering result.  Jia Li, Beomseok Seo, and Lin Lin
(2019) <doi:10.1002/sam.11418>.  Lixiang Zhang, Lin Lin, and Jia Li (2020)
<doi:10.1093/bioinformatics/btaa165>.")
    (license license:gpl2+)))

(define-public r-otargen
  (package
    (name "r-otargen")
    (version "1.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "otargen" version))
       (sha256
        (base32 "1akqdz0qcc5clj2mqn71zqi7d93l5yihzr9d4wsk4pv9rsw3vqry"))))
    (properties `((upstream-name . "otargen")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-magrittr
                             r-jsonlite
                             r-janitor
                             r-ghql
                             r-ggrepel
                             r-ggplot2
                             r-ggiraphextra
                             r-dplyr
                             r-cli))
    (home-page "https://amirfeizi.github.io/otargen/")
    (synopsis "Access Open Target Genetics")
    (description
     "Interact seamlessly with Open Target Genetics @code{GraphQL} endpoint to query
and retrieve tidy data tables, facilitating the analysis of genetic data.  For
more information about the Open Target Genetics API
(<https://genetics.opentargets.org/api>).")
    (license license:expat)))

(define-public r-osum
  (package
    (name "r-osum")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "osum" version))
       (sha256
        (base32 "066h6xylagrs313zy4p9qm5rgml6pkz6kq4jvpw922f89q5cd04m"))))
    (properties `((upstream-name . "osum")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://zivankaraman.github.io/osum/")
    (synopsis "Provide Summary Information About R Objects")
    (description
     "Inspired by S-PLUS function objects.summary(), provides a function with the same
name that returns data class, storage mode, mode, type, dimension, and size
information for R objects in the specified environment.  Various filtering and
sorting options are also proposed.")
    (license license:gpl3)))

(define-public r-oste
  (package
    (name "r-oste")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OSTE" version))
       (sha256
        (base32 "0l8whr883g3jp5ckgxr4zf9vj055jrjb7pfraacd15smnrbl0v5d"))))
    (properties `((upstream-name . "OSTE")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-ranger r-prodlim r-pec))
    (home-page "https://cran.r-project.org/package=OSTE")
    (synopsis "Optimal Survival Trees Ensemble")
    (description
     "Function for growing survival trees ensemble ('Naz Gul', Nosheen Faiz', Dan
Brawn', Rafal Kulakowski', Zardad Khan', and Berthold Lausen (2020)
<@code{arXiv:2005.09043>}) is given.  The trees are grown by the method of
random survival forest ('Marvin Wright', Andreas Ziegler (2017)
<doi:10.18637/jss.v077.i01>).  The survival trees grown are assessed for both
individual and collective performances.  The ensemble can give promising results
on fewer survival trees selected in the final ensemble.")
    (license (license:fsdg-compatible "GPL (>= 3.5.0)"))))

(define-public r-ostats
  (package
    (name "r-ostats")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Ostats" version))
       (sha256
        (base32 "0d2qk76issb2k5f2ghfvpq0k8ra7d7nj9hp4ja1s0817zwr0g3zz"))))
    (properties `((upstream-name . "Ostats")))
    (build-system r-build-system)
    (propagated-inputs (list r-viridis
                             r-sfsmisc
                             r-matrixstats
                             r-mass
                             r-hypervolume
                             r-gridextra
                             r-ggplot2
                             r-circular))
    (native-inputs (list r-knitr))
    (home-page "https://neon-biodiversity.github.io/Ostats/")
    (synopsis "O-Stats, or Pairwise Community-Level Niche Overlap Statistics")
    (description
     "O-statistics, or overlap statistics, measure the degree of community-level trait
overlap.  They are estimated by fitting nonparametric kernel density functions
to each speciesâ trait distribution and calculating their areas of overlap.
For instance, the median pairwise overlap for a community is calculated by first
determining the overlap of each species pair in trait space, and then taking the
median overlap of each species pair in a community.  This median overlap value
is called the O-statistic (O for overlap).  The Ostats() function calculates
separate univariate overlap statistics for each trait, while the
Ostats_multivariate() function calculates a single multivariate overlap
statistic for all traits.  O-statistics can be evaluated against null models to
obtain standardized effect sizes.  Ostats is part of the collaborative
Macrosystems Biodiversity Project \"Local- to continental-scale drivers of
biodiversity across the National Ecological Observatory Network (NEON).\" For
more information on this project, see the Macrosystems Biodiversity Website
(<https://neon-biodiversity.github.io/>).  Calculation of O-statistics is
described in Read et al. (2018) <doi:10.1111/ecog.03641>, and a teaching module
for introducing the underlying biological concepts at an undergraduate level is
described in Grady et al. (2018)
<http://tiee.esa.org/vol/v14/issues/figure_sets/grady/abstract.html>.")
    (license license:expat)))

(define-public r-ossurvival
  (package
    (name "r-ossurvival")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OSsurvival" version))
       (sha256
        (base32 "1fbxddbhppqlh49wgh2fldixar5mk7rywjbfvbpdb6fvpgn1sc4g"))))
    (properties `((upstream-name . "OSsurvival")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=OSsurvival")
    (synopsis "Assessing Surrogacy with a Censored Outcome")
    (description
     "Identifies the optimal transformation of a surrogate marker and estimates the
proportion of treatment explained (PTE) by the optimally-transformed surrogate
at an earlier time point when the primary outcome of interest is a censored
time-to-event outcome; details are described in Wang et al (2021)
<doi:10.1002/sim.9185>.")
    (license license:gpl3)))

(define-public r-ossanma
  (package
    (name "r-ossanma")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OssaNMA" version))
       (sha256
        (base32 "04y36yi1qvxazf0s563d41g91x2190r1c5phkgkfqdcml94dmnln"))))
    (properties `((upstream-name . "OssaNMA")))
    (build-system r-build-system)
    (propagated-inputs (list r-nlcoptim r-deoptimr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/fangshuye/OssaNMA")
    (synopsis
     "Optimal Sample Size and Allocation with a Network Meta-Analysis")
    (description
     "This package provides a system for calculating the minimum total sample size
needed to achieve a prespecified power or the optimal allocation for each
treatment group with a fixed total sample size to maximize the power.")
    (license license:gpl3)))

(define-public r-osrmr
  (package
    (name "r-osrmr")
    (version "0.1.36")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "osrmr" version))
       (sha256
        (base32 "1vnf6g1d9fjckz9ay910nb9gr1km2adwk3b0k460mxvpr36izkh7"))))
    (properties `((upstream-name . "osrmr")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-rjson r-r-utils r-bitops r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=osrmr")
    (synopsis "Wrapper for the 'OSRM' API")
    (description
     "Wrapper around the Open Source Routing Machine (OSRM) API
<http://project-osrm.org/>.  osrmr works with API versions 4 and 5 and can
handle servers that run locally as well as the OSRM webserver.")
    (license license:gpl3)))

(define-public r-osrm
  (package
    (name "r-osrm")
    (version "4.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "osrm" version))
       (sha256
        (base32 "1256pksd8mxzxi1vnl6ghhyl8f7g2li4wabs0kllw9i54yxvc83b"))))
    (properties `((upstream-name . "osrm")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf r-rcppsimdjson r-mapiso r-googlepolylines
                             r-curl))
    (home-page "https://github.com/riatelab/osrm")
    (synopsis
     "Interface Between R and the OpenStreetMap-Based Routing Service OSRM")
    (description
     "An interface between R and the OSRM API. OSRM is a routing service based on
@code{OpenStreetMap} data.  See <http://project-osrm.org/> for more information.
 This package enables the computation of routes, trips, isochrones and travel
distances matrices (travel time and kilometric distance).")
    (license license:gpl3+)))

(define-public r-osnmtf
  (package
    (name "r-osnmtf")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OSNMTF" version))
       (sha256
        (base32 "0g83wqh97iz3g4ganj2dy3biyn8cmb0v8zz6rydald1hfszj8aa2"))))
    (properties `((upstream-name . "OSNMTF")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OSNMTF")
    (synopsis "Orthogonal Sparse Non-Negative Matrix Tri-Factorization")
    (description
     "This package provides a novel method to implement cancer subtyping and subtype
specific drug targets identification via non-negative matrix tri-factorization.
To improve the interpretability, we introduce orthogonal constraint to the row
coefficient matrix and column coefficient matrix.  To meet the prior knowledge
that each subtype should be strongly associated with few gene sets, we introduce
sparsity constraint to the association sub-matrix.  The average residue was
introduced to evaluate the row and column cluster numbers.  This is part of the
work \"Liver Cancer Analysis via Orthogonal Sparse Non-Negative Matrix Tri-
Factorization\" which will be submitted to BBRC.")
    (license license:gpl2+)))

(define-public r-osmscale
  (package
    (name "r-osmscale")
    (version "0.5.20")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OSMscale" version))
       (sha256
        (base32 "14n5574j083xllj0xs87cl8szc0favb8wp3v10bbdljbk35qvmbm"))))
    (properties `((upstream-name . "OSMscale")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf r-pbapply r-openstreetmap r-berryfunctions))
    (home-page "https://github.com/brry/OSMscale")
    (synopsis "Add a Scale Bar to 'OpenStreetMap' Plots")
    (description
     "Functionality to handle and project lat-long coordinates, easily download
background maps and add a correct scale bar to @code{OpenStreetMap} plots in any
map projection.")
    (license license:gpl2+)))

(define-public r-osmextract
  (package
    (name "r-osmextract")
    (version "0.5.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "osmextract" version))
       (sha256
        (base32 "03q3ra119j8rxkqasyxg0m4dlcpb378milfa1mwihsmmq4qd6ak5"))))
    (properties `((upstream-name . "osmextract")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf r-jsonlite r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/osmextract/")
    (synopsis "Download and Import Open Street Map Data Extracts")
    (description
     "Match, download, convert and import Open Street Map data extracts obtained from
several providers.")
    (license license:gpl3)))

(define-public r-osmdata
  (package
    (name "r-osmdata")
    (version "0.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "osmdata" version))
       (sha256
        (base32 "0073dnnznq479ffnizrv8wqmfiv3gmdmmlkmkh1hxgr7p32v1i4z"))))
    (properties `((upstream-name . "osmdata")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-tibble
                             r-rvest
                             r-reproj
                             r-rcpp
                             r-magrittr
                             r-lubridate
                             r-httr2
                             r-curl))
    (native-inputs (list r-knitr))
    (home-page
     "https://docs.ropensci.org/osmdata/https://github.com/ropensci/osmdata/")
    (synopsis
     "Import 'OpenStreetMap' Data as Simple Features or Spatial Objects")
    (description
     "Download and import of @code{OpenStreetMap} ('OSM') data as sf or sp objects.
OSM data are extracted from the Overpass web server (<https://overpass-api.de/>)
and processed with very fast C++ routines for return to R'.")
    (license license:gpl3)))

(define-public r-osmclass
  (package
    (name "r-osmclass")
    (version "0.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "osmclass" version))
       (sha256
        (base32 "16vpb1fq93s386anvyl6i8ynk5mijs0c40sh86lcpmp9wmdb6msp"))))
    (properties `((upstream-name . "osmclass")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi r-data-table r-collapse))
    (home-page "https://cran.r-project.org/package=osmclass")
    (synopsis "Classify Open Street Map Features")
    (description
     "Classify Open Street Map (OSM) features into meaningful functional or analytical
categories.  Designed for OSM PBF files, e.g. from
<https://download.geofabrik.de/> imported as spatial data frames.  A
classification consists of a list of categories that are related to certain OSM
tags and values.  Given a layer from an OSM PBF file and a classification, the
main osm_classify() function returns a classification data table giving, for
each feature, the primary and alternative categories (if there is overlap)
assigned, and the tag(s) and value(s) matched on.  The package also contains a
classification of OSM features by economic function/significance, following
Krantz (2023) <https://www.ssrn.com/abstract=4537867>.")
    (license license:gpl3)))

(define-public r-osmapir
  (package
    (name "r-osmapir")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "osmapiR" version))
       (sha256
        (base32 "1c0x6132h0wa3652sy4kxzq2mkzik8nk0kdxz3357a3pfh0d9n0x"))))
    (properties `((upstream-name . "osmapiR")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2 r-httr2 r-curl))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/osmapiR/")
    (synopsis "'OpenStreetMap' API")
    (description
     "Interface to @code{OpenStreetMap} API for fetching and saving data from/to the
@code{OpenStreetMap} database (<https://wiki.openstreetmap.org/wiki/API_v0.6>).")
    (license license:gpl3+)))

(define-public r-osldecomposition
  (package
    (name "r-osldecomposition")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OSLdecomposition" version))
       (sha256
        (base32 "0xz27p4wd1a5y8x24sqgpyvgdwi2dzk4qh2s50xrdr82prb2znkv"))))
    (properties `((upstream-name . "OSLdecomposition")))
    (build-system r-build-system)
    (propagated-inputs (list r-scales
                             r-rmarkdown
                             r-minpack-lm
                             r-luminescence
                             r-gridextra
                             r-ggpubr
                             r-ggplot2
                             r-deoptim))
    (home-page "https://cran.r-project.org/package=OSLdecomposition")
    (synopsis
     "Signal Component Analysis for Optically Stimulated Luminescence")
    (description
     "Function library for the identification and separation of exponentially decaying
signal components in continuous-wave optically stimulated luminescence
measurements.  A special emphasis is laid on luminescence dating with quartz,
which is known for systematic errors due to signal components with unequal
physical behaviour.  Also, this package enables an easy to use signal
decomposition of data sets imported and analysed with the R package
Luminescence'.  This includes the optional automatic creation of HTML reports.
Further information and tutorials can be found at <https://luminescence.de>.")
    (license license:gpl3)))

(define-public r-oskeyring
  (package
    (name "r-oskeyring")
    (version "0.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oskeyring" version))
       (sha256
        (base32 "1fsgz4jln3nk53bxpmjpc7dcapc9j1wdqlrab169ymvrlzypgvqc"))))
    (properties `((upstream-name . "oskeyring")))
    (build-system r-build-system)
    (home-page "https://github.com/r-lib/oskeyring#readme")
    (synopsis "Raw System Credential Store Access from R")
    (description
     "Aims to support all features of the system credential store, including
non-portable ones.  Supports Keychain on @code{macOS}', and Credential Manager
on Windows'.  See the keyring package if you need a portable API'.")
    (license license:expat)))

(define-public r-oshka
  (package
    (name "r-oshka")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oshka" version))
       (sha256
        (base32 "02hglpq5lknq93zbcf219lhnhppzgygkhxqixb15f89rxf9fczgs"))))
    (properties `((upstream-name . "oshka")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/brodieG/oshka")
    (synopsis "Recursive Quoted Language Expansion")
    (description
     "Expands quoted language by recursively replacing any symbol that points to
quoted language with the language it points to.  The recursive process continues
until only symbols that point to non-language objects remain.  The resulting
quoted language can then be evaluated normally.  This differs from the
traditional quote'/'eval pattern because it resolves intermediate language
objects that would interfere with evaluation.")
    (license license:gpl2+)))

(define-public r-osfr
  (package
    (name "r-osfr")
    (version "0.2.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "osfr" version))
       (sha256
        (base32 "0gbkg6hlip2bkwifsgvnaimrmi1pamaxf8xv7g0yxw5wdf8zyy5c"))))
    (properties `((upstream-name . "osfr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringi
                             r-rlang
                             r-purrr
                             r-memoise
                             r-jsonlite
                             r-httr
                             r-fs
                             r-crul))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/osfr/")
    (synopsis "Interface to the 'Open Science Framework' ('OSF')")
    (description
     "An interface for interacting with OSF (<https://osf.io>).  osfr enables you to
access open research materials and data, or create and manage your own private
or public projects.")
    (license license:expat)))

(define-public r-osfd
  (package
    (name "r-osfd")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OSFD" version))
       (sha256
        (base32 "1xw76hi34vgq1r6r22z4bqp114nzg4h85mvz6pya724vyf110vhg"))))
    (properties `((upstream-name . "OSFD")))
    (build-system r-build-system)
    (propagated-inputs (list r-twinning r-rcpparmadillo r-rcpp r-lhs r-dplyr))
    (home-page "https://cran.r-project.org/package=OSFD")
    (synopsis "Output Space-Filling Design")
    (description
     "This package provides a method to generate a design in the input space that
sequentially fills the output space of a black-box function.  The output
space-filling design will be helpful in inverse design or feature-based modeling
problem.  Please see Wang et al.(2023) <DOI:10.48550/@code{arXiv.2305.07202>}
for details.  This work is supported by U.S. National Foundation grant
CMMI-1921646.")
    (license license:gpl2+)))

(define-public r-osdr
  (package
    (name "r-osdr")
    (version "1.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OSDR" version))
       (sha256
        (base32 "0yf9l0fkqf9adanl8182nyislj2s2xvsnf2xp5y7pdj3af2k4m7w"))))
    (properties `((upstream-name . "OSDR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=OSDR")
    (synopsis "Finds an Optimal System of Distinct Representatives")
    (description
     "This package provides routines for finding an Optimal System of Distinct
Representatives (OSDR), as defined by D.Gale (1968)
<doi:10.1016/S0021-9800(68)80039-0>.")
    (license license:gpl3)))

(define-public r-osdesign
  (package
    (name "r-osdesign")
    (version "1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "osDesign" version))
       (sha256
        (base32 "0l5dq8rj4rg4v324610kj2j5nv7py6z1jcplhb6br1gvldj7ng1d"))))
    (properties `((upstream-name . "osDesign")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=osDesign")
    (synopsis "Design, Planning and Analysis of Observational Studies")
    (description
     "This package provides a suite of functions for the design of case-control and
two-phase studies, and the analysis of data that arise from them.  Functions in
this packages provides Monte Carlo based evaluation of operating characteristics
such as powers for estimators of the components of a logistic regression model.
For additional detail see: Haneuse S, Saegusa T and Lumley T
(2011)<doi:10.18637/jss.v043.i11>.")
    (license license:gpl3+)))

(define-public r-osdatahub
  (package
    (name "r-osdatahub")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "osdatahub" version))
       (sha256
        (base32 "00pk0c9v3r0kdgin4gg4hk3hhf0274pw283919pr9kg926nddc3r"))))
    (properties `((upstream-name . "osdatahub")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr r-geos r-geojsonsf))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=osdatahub")
    (synopsis "Easier Interaction with the Ordnance Survey Data Hub")
    (description
     "Ordnance Survey ('OS') is the national mapping agency for Great Britain and
produces a large variety of mapping and geospatial products.  Much of OS's data
is available via the OS Data Hub <https://osdatahub.os.uk/>, a platform that
hosts both free and premium data products.  osdatahub provides a user-friendly
way to access, query, and download these data.")
    (license license:expat)))

(define-public r-osd
  (package
    (name "r-osd")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "osd" version))
       (sha256
        (base32 "1py9p15nrcydr8w9ilxkxabiz9zlqnls8xn9avjkxd8x6602jx6p"))))
    (properties `((upstream-name . "osd")))
    (build-system r-build-system)
    (propagated-inputs (list r-nnls r-jade))
    (home-page "https://cran.r-project.org/package=osd")
    (synopsis
     "Orthogonal Signal Deconvolution for Spectra Deconvolution in GC-MS and GCxGC-MS Data")
    (description
     "Compound deconvolution for chromatographic data, including gas chromatography -
mass spectrometry (GC-MS) and comprehensive gas chromatography - mass
spectrometry (G@code{CxGC-MS}).  The package includes functions to perform
independent component analysis - orthogonal signal deconvolution (ICA-OSD),
independent component regression (ICR), multivariate curve resolution (MCR-ALS)
and orthogonal signal deconvolution (OSD) alone.")
    (license license:gpl2+)))

(define-public r-oscv
  (package
    (name "r-oscv")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OSCV" version))
       (sha256
        (base32 "17wrfak6b6m2l3iqbhdwcfh0rlqb14rkvrbari7v46gya9v7hq20"))))
    (properties `((upstream-name . "OSCV")))
    (build-system r-build-system)
    (propagated-inputs (list r-mc2d))
    (home-page "https://cran.r-project.org/package=OSCV")
    (synopsis "One-Sided Cross-Validation")
    (description
     "This package provides functions for implementing different versions of the OSCV
method in the kernel regression and density estimation frameworks.  The package
mainly supports the following articles: (1) Savchuk, O.Y., Hart, J.D. (2017).
Fully robust one-sided cross-validation for regression functions.  Computational
Statistics, <doi:10.1007/s00180-017-0713-7> and (2) Savchuk, O.Y. (2017).
One-sided cross-validation for nonsmooth density functions,
<@code{arXiv:1703.05157>}.")
    (license license:gpl2)))

(define-public r-oscillatorgenerator
  (package
    (name "r-oscillatorgenerator")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OscillatorGenerator" version))
       (sha256
        (base32 "0zqw8l955msxkdviw5vd493749zwc22qby9mfmyqnqqmq0pyjw4w"))))
    (properties `((upstream-name . "OscillatorGenerator")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=OscillatorGenerator")
    (synopsis
     "Generation of Customizable, Discretized Time Series of Oscillating Species")
    (description
     "The supplied code allows for the generation of discrete time series of
oscillating species.  General shapes can be selected by means of individual
functions, which are widely customizable by means of function arguments.  All
code was developed in the Biological Information Processing Group at the
@code{BioQuant} Center at Heidelberg University, Germany.")
    (license license:gpl3+)))

(define-public r-oscar
  (package
    (name "r-oscar")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oscar" version))
       (sha256
        (base32 "1khyl3y8rpyn0skn45wcl1saa713fh48fv6vh3hfgyf46j8ibgra"))))
    (properties `((upstream-name . "oscar")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-proc r-matrix r-hamlet))
    (native-inputs (list r-knitr gfortran))
    (home-page "https://github.com/Syksy/oscar")
    (synopsis
     "Optimal Subset Cardinality Regression (OSCAR) Models Using the L0-Pseudonorm")
    (description
     "Optimal Subset Cardinality Regression (OSCAR) models offer regularized linear
regression using the L0-pseudonorm, conventionally known as the number of
non-zero coefficients.  The package estimates an optimal subset of features
using the L0-penalization via cross-validation, bootstrapping and visual
diagnostics.  Effective Fortran implementations are offered along the package
for finding optima for the DC-decomposition, which is used for transforming the
discrete L0-regularized optimization problem into a continuous non-convex
optimization task.  These optimization modules include DBDC ('Double Bundle
method for nonsmooth DC optimization as described in Joki et al. (2018)
<doi:10.1137/16M1115733>) and LMBM ('Limited Memory Bundle Method for
large-scale nonsmooth optimization as in Haarala et al. (2004)
<doi:10.1080/10556780410001689225>).  The OSCAR models are comprehensively
exemplified in Halkola et al. (2023) <doi:10.1371/journal.pcbi.1010333>).
Multiple regression model families are supported: Cox, logistic, and Gaussian.")
    (license license:gpl3)))

(define-public r-osc
  (package
    (name "r-osc")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "osc" version))
       (sha256
        (base32 "00a0ys5ni0hg5zxi0sr5ak3n4c252vhvd6gynnx1b0lqna7bz9qi"))))
    (properties `((upstream-name . "osc")))
    (build-system r-build-system)
    (propagated-inputs (list r-raster))
    (home-page "https://www.pik-potsdam.de/~kriewald/osc/")
    (synopsis "Orthodromic Spatial Clustering")
    (description
     "Allows distance based spatial clustering of georeferenced data by implementing
the City Clustering Algorithm - CCA. Multiple versions allow clustering for a
matrix, raster and single coordinates on a plain (Euclidean distance) or on a
sphere (great-circle or orthodromic distance).")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-oryzaprobe
  (package
    (name "r-oryzaprobe")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OryzaProbe" version))
       (sha256
        (base32 "0sih1pc0ch5w769w7sc56ixppv4njqq31g7n49290kzn8d46i3fw"))))
    (properties `((upstream-name . "OryzaProbe")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OryzaProbe")
    (synopsis
     "Rice Microarray Probe ID Conversion, from Probe ID to RAP-DB ID")
    (description
     "Microarray probe ID is not convenient for further enrichment analysis and target
gene selection.  The package is created for the rice microarray probe ID
conversion.  This package can convert microarray probe ID from GPL6864
<https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL6864>, GPL8852
<https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL8852>, and GPL2025
<https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL2025> platforms to RAP-DB
ID. RAP-DB \"The Rice Annotation Project Database\"
<https://rapdb.dna.affrc.go.jp> is a well-known database for rice Oryza sativa,
and the gene ID in this database is widely used in many areas related to rice
research.  For multiple probes representing a single gene, This package can
merge them by taking the mean, max, or min value of these probes.  Or we can
keep multiple probes by appending sequence numbers to duplicate the RAP-DB ID.")
    (license license:gpl3)))

(define-public r-orus
  (package
    (name "r-orus")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oRus" version))
       (sha256
        (base32 "0q6hgiidcpm95pyisndihxjg78v6k1zycdqd72309aankdk0g5h4"))))
    (properties `((upstream-name . "oRus")))
    (build-system r-build-system)
    (propagated-inputs (list r-xlsx
                             r-topicmodels
                             r-tm
                             r-tidytext
                             r-tibble
                             r-stringr
                             r-rmarkdown
                             r-knitr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/melvidoni/oRus")
    (synopsis "Operational Research User Stories")
    (description
     "This package provides a first implementation of automated parsing of user
stories, when used to defined functional requirements for operational research
mathematical models.  It allows reading user stories, splitting them on the
who-what-why template, and classifying them according to the parts of the
mathematical model that they represent.  Also provides semantic grouping of
stories, for project management purposes.")
    (license license:gpl3)))

(define-public r-ortsc
  (package
    (name "r-ortsc")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ORTSC" version))
       (sha256
        (base32 "0byja1gi44ymn68cfai8apcimlxmnflqr1pj8k4y7l8lqd3fyz60"))))
    (properties `((upstream-name . "ORTSC")))
    (build-system r-build-system)
    (propagated-inputs (list r-googlecloudvisionr r-googleauthr))
    (home-page "https://github.com/MohmedSoudy/ORTSC")
    (synopsis "Connects to Google Cloud API for Label Detection")
    (description
     "Connects to Google cloud vision <https://cloud.google.com/vision> to perform
label detection and repurpose this feature for image classification.")
    (license license:gpl3)))

(define-public r-orthopolynom
  (package
    (name "r-orthopolynom")
    (version "1.0-6.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orthopolynom" version))
       (sha256
        (base32 "1ig2pyyibbynwmhapbicij5g47acnz8npjm46xnjybskcv96wjpc"))))
    (properties `((upstream-name . "orthopolynom")))
    (build-system r-build-system)
    (propagated-inputs (list r-polynom))
    (home-page "https://cran.r-project.org/package=orthopolynom")
    (synopsis
     "Collection of Functions for Orthogonal and Orthonormal Polynomials")
    (description
     "This package provides a collection of functions to construct sets of orthogonal
polynomials and their recurrence relations.  Additional functions are provided
to calculate the derivative, integral, value and roots of lists of polynomial
objects.")
    (license license:gpl2+)))

(define-public r-orthopanels
  (package
    (name "r-orthopanels")
    (version "1.2-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OrthoPanels" version))
       (sha256
        (base32 "1l7fllkswiypdg88l3hy1ckd1gx7visfrzw24wrr2xc265iqyn26"))))
    (properties `((upstream-name . "OrthoPanels")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OrthoPanels")
    (synopsis
     "Dynamic Panel Models with Orthogonal Reparameterization of Fixed Effects")
    (description
     "This package implements the orthogonal reparameterization approach recommended
by Lancaster (2002) to estimate dynamic panel models with fixed effects (and
optionally: panel specific intercepts).  The approach uses a likelihood-based
estimator and produces estimates that are asymptotically unbiased as N goes to
infinity, with a T as low as 2.")
    (license license:gpl3+)))

(define-public r-orthogonalsplinebasis
  (package
    (name "r-orthogonalsplinebasis")
    (version "0.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orthogonalsplinebasis" version))
       (sha256
        (base32 "0wdqyijvwf9fdg22s6ck22bjk3xc30snlx29sxvm15yiz3rj498v"))))
    (properties `((upstream-name . "orthogonalsplinebasis")))
    (build-system r-build-system)
    (home-page "https://github.com/halpo/obsplines")
    (synopsis "Orthogonal B-Spline Basis Functions")
    (description
     "Represents the basis functions for B-splines in a simple matrix formulation that
facilitates, taking integrals, derivatives, and making orthogonal the basis
functions.")
    (license license:gpl2+)))

(define-public r-orthodr
  (package
    (name "r-orthodr")
    (version "0.6.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orthoDr" version))
       (sha256
        (base32 "0dsdmrmqib5mx57v0f32dw9ybydxh80h1xn0130nrw27268bqi52"))))
    (properties `((upstream-name . "orthoDr")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival
                             r-rgl
                             r-rcpparmadillo
                             r-rcpp
                             r-pracma
                             r-plot3d
                             r-mass
                             r-dr))
    (home-page "https://github.com/teazrq/orthoDr")
    (synopsis
     "Semi-Parametric Dimension Reduction Models Using Orthogonality Constrained Optimization")
    (description
     "Utilize an orthogonality constrained optimization algorithm of Wen & Yin (2013)
<DOI:10.1007/s10107-012-0584-1> to solve a variety of dimension reduction
problems in the semiparametric framework, such as Ma & Zhu (2012)
<DOI:10.1080/01621459.2011.646925>, Ma & Zhu (2013) <DOI:10.1214/12-AOS1072>,
Sun, Zhu, Wang & Zeng (2019) <DOI:10.1093/biomet/asy064> and Zhou, Zhu & Zeng
(2021) <DOI:10.1093/biomet/asaa087>.  The package also implements some existing
dimension reduction methods such as @code{hMave} by Xia, Zhang, & Xu (2010)
<DOI:10.1198/jasa.2009.tm09372> and partial SAVE by Feng, Wen & Zhu (2013)
<DOI:10.1080/01621459.2012.746065>.  It also serves as a general purpose
optimization solver for problems with orthogonality constraints, i.e., in
Stiefel manifold.  Parallel computing for approximating the gradient is enabled
through @code{OpenMP}'.")
    (license license:gpl2+)))

(define-public r-orthgs
  (package
    (name "r-orthgs")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orthGS" version))
       (sha256
        (base32 "03hx6z6li49m8b51kqii6ixygw95h31fnvj7z29j8iyzjq96jqga"))))
    (properties `((upstream-name . "orthGS")))
    (build-system r-build-system)
    (propagated-inputs (list r-treetools
                             r-seqinr
                             r-phytools
                             r-phangorn
                             r-igraph
                             r-castor
                             r-bio3d
                             r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=orthGS")
    (synopsis
     "Orthology vs Paralogy Relationships among Glutamine Synthetase from Plants")
    (description
     "This package provides tools to analyze and infer orthology and paralogy
relationships between glutamine synthetase proteins in seed plants.")
    (license license:gpl2+)))

(define-public r-orth-ord
  (package
    (name "r-orth-ord")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ORTH.Ord" version))
       (sha256
        (base32 "0n8m8dpxbb6zss7mlyq6v44yja566q3hf23qqspk88ksrah8wgiv"))))
    (properties `((upstream-name . "ORTH.Ord")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-magic))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ORTH.Ord")
    (synopsis
     "Alternating Logistic Regression with Orthogonalized Residuals for Correlated Ordinal Outcomes")
    (description
     "This package provides a modified version of alternating logistic regressions
(ALR) with estimation based on orthogonalized residuals (ORTH) is implemented,
which use paired estimating equations to jointly estimate parameters in marginal
mean and within-association models.  The within-cluster association between
ordinal responses is modeled by global pairwise odds ratios (POR).  A
finite-sample bias correction is provided to POR parameter estimates based on
matrix multiplicative adjusted orthogonalized residuals (MMORTH) for correcting
estimating equations, and different bias-corrected variance estimators such as
BC1, BC2, and BC3.")
    (license license:gpl2+)))

(define-public r-orsk
  (package
    (name "r-orsk")
    (version "1.0-8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orsk" version))
       (sha256
        (base32 "01gnqqcasdwbh5dk1yg50qiyn59wsk0d01q0xwg0aqcclmnsfkds"))))
    (properties `((upstream-name . "orsk")))
    (build-system r-build-system)
    (propagated-inputs (list r-bhh2 r-bb))
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=orsk")
    (synopsis
     "Converting Odds Ratio to Relative Risk in Cohort Studies with Partial Data Information")
    (description
     "Convert odds ratio to relative risk in cohort studies with partial data
information (Wang (2013) <doi:10.18637/jss.v055.i05>).")
    (license license:gpl2+)))

(define-public r-orsifronts
  (package
    (name "r-orsifronts")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orsifronts" version))
       (sha256
        (base32 "0nxhijiqhhrxwrm5fy619lsdqyji43xyfqg4309pfb7da4377i3q"))))
    (properties `((upstream-name . "orsifronts")))
    (build-system r-build-system)
    (propagated-inputs (list r-sp))
    (native-inputs (list r-knitr))
    (home-page "https://australianantarcticdivision.github.io/orsifronts/")
    (synopsis "Southern Ocean Frontal Distributions (Orsi)")
    (description
     "This package provides a data set package with the \"Orsi\" and \"Park/Durand\"
fronts as @code{SpatialLinesDataFrame} objects.  The Orsi et al. (1995) fronts
are published at the Southern Ocean Atlas Database Page, and the Park et al.
(2019) fronts are published at the SEANOE Altimetry-derived Antarctic
Circumpolar Current fronts page, please see package CITATION for details.")
    (license license:gpl3)))

(define-public r-oro-pet
  (package
    (name "r-oro-pet")
    (version "0.2.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oro.pet" version))
       (sha256
        (base32 "0drk4mlacg443y5qljyp5jrq3lcr08qmsxnr8mgp93cxrdlwvr1i"))))
    (properties `((upstream-name . "oro.pet")))
    (build-system r-build-system)
    (propagated-inputs (list r-oro-nifti r-oro-dicom r-msm r-minpack-lm))
    (home-page "http://rig.oro.us.com")
    (synopsis "Rigorous - Positron Emission Tomography")
    (description
     "Image analysis techniques for positron emission tomography (PET) that form part
of the Rigorous Analytics bundle.")
    (license license:bsd-3)))

(define-public r-oro-dicom
  (package
    (name "r-oro-dicom")
    (version "0.5.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oro.dicom" version))
       (sha256
        (base32 "1ar70xk2bqk7jgckfivgp4np3dxaynmgdg41n8x0sg9cpxl2lc38"))))
    (properties `((upstream-name . "oro.dicom")))
    (build-system r-build-system)
    (propagated-inputs (list r-oro-nifti))
    (home-page "http://rig.oro.us.com")
    (synopsis "Rigorous - DICOM Input / Output")
    (description
     "Data input/output functions for data that conform to the Digital Imaging and
Communications in Medicine (DICOM) standard, part of the Rigorous Analytics
bundle.")
    (license license:bsd-3)))

(define-public r-ormplot
  (package
    (name "r-ormplot")
    (version "0.3.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ormPlot" version))
       (sha256
        (base32 "0fr1g2lkzc50y79f1czkagcavnq1kfmk6qxg05gqj07jc66mvici"))))
    (properties `((upstream-name . "ormPlot")))
    (build-system r-build-system)
    (propagated-inputs (list r-rms r-gtable r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://doi.org/10.1186/s12889-019-8072-7")
    (synopsis "Advanced Plotting of Ordinal Regression Models")
    (description
     "An extension to the Regression Modeling Strategies package that facilitates
plotting ordinal regression model predictions together with confidence intervals
for each dependent variable level.  It also adds a functionality to plot the
model summary as a modifiable object.")
    (license license:expat)))

(define-public r-ormbigdata
  (package
    (name "r-ormbigdata")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ormBigData" version))
       (sha256
        (base32 "1rq202k4assmij21bjjk1ba7121p5p3rp21k548cc6lk81xj1rcc"))))
    (properties `((upstream-name . "ormBigData")))
    (build-system r-build-system)
    (propagated-inputs (list r-sparsem
                             r-rms
                             r-iterators
                             r-hmisc
                             r-foreach
                             r-doparallel
                             r-benchmarkme))
    (home-page "https://cran.r-project.org/package=ormBigData")
    (synopsis
     "Fitting Semiparametric Cumulative Probability Models for Big Data")
    (description
     "This package provides a big data version for fitting cumulative probability
models using the orm() function.  See Liu et al. (2017) <DOI:10.1002/sim.7433>
for details.")
    (license license:gpl2+)))

(define-public r-orloca-es
  (package
    (name "r-orloca-es")
    (version "4.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orloca.es" version))
       (sha256
        (base32 "00zb08dqcsh1ljl4f2djm1pwbrfbaddgapn3v8nascmwxlhb2hkw"))))
    (properties `((upstream-name . "orloca.es")))
    (build-system r-build-system)
    (propagated-inputs (list r-orloca))
    (home-page "http://knuth.uca.es/orloca")
    (synopsis
     "Spanish version of orloca package. Modelos de localizacion en investigacion operativa")
    (description
     "Help and demo in Spanish of the orloca package. (Ayuda y demo en espanol del
paquete orloca.) Objetos y metodos para manejar y resolver el problema de
localizacion de suma minima, tambien conocido como problema de Fermat-Weber.  El
problema de localizacion de suma minima busca un punto tal que la suma ponderada
de las distancias a los puntos de demanda se minimice.  Vease \"The Fermat-Weber
location problem revisited\" por Brimberg, Mathematical Programming, 1, pag.
71-76, 1995. <DOI: 10.1007/BF01592245>.  Se usan algoritmos generales de
optimizacion global para resolver el problema, junto con el metodo adhoc
Weiszfeld, vease \"Sur le point pour lequel la Somme des distance de n points
donnes est minimum\", por Weiszfeld, Tohoku Mathematical Journal, First Series,
43, pag.  355-386, 1937 o \"On the point for which the sum of the distances to n
given points is minimum\", por E. Weiszfeld y F. Plastria, Annals of Operations
Research, 167, pg.  7-41, 2009. <DOI:10.1007/s10479-008-0352-z>.")
    (license license:gpl3+)))

(define-public r-orloca
  (package
    (name "r-orloca")
    (version "5.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orloca" version))
       (sha256
        (base32 "0zfi64whis248fi5fggjqym7jhyh7ix7l371kchkdxcib3xylnps"))))
    (properties `((upstream-name . "orloca")))
    (build-system r-build-system)
    (propagated-inputs (list r-ucminf r-rmarkdown r-png r-knitr))
    (native-inputs (list r-knitr))
    (home-page "http://knuth.uca.es/orloca/")
    (synopsis "Operations Research LOCational Analysis Models")
    (description
     "Objects and methods to handle and solve the min-sum location problem, also known
as Fermat-Weber problem.  The min-sum location problem search for a point such
that the weighted sum of the distances to the demand points are minimized.  See
\"The Fermat-Weber location problem revisited\" by Brimberg, Mathematical
Programming, 1, pg.  71-76, 1995. <DOI:10.1007/BF01592245>.  General global
optimization algorithms are used to solve the problem, along with the adhoc
Weiszfeld method, see \"Sur le point pour lequel la Somme des distances de n
points donnes est minimum\", by Weiszfeld, Tohoku Mathematical Journal, First
Series, 43, pg.  355-386, 1937 or \"On the point for which the sum of the
distances to n given points is minimum\", by E. Weiszfeld and F. Plastria, Annals
of Operations Research, 167, pg.  7-41, 2009. <DOI:10.1007/s10479-008-0352-z>.")
    (license license:gpl3+)))

(define-public r-orkm
  (package
    (name "r-orkm")
    (version "0.8.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ORKM" version))
       (sha256
        (base32 "132459zd83c3www2gijcb97f5c765p66y459irlv63ny21hwpnsp"))))
    (properties `((upstream-name . "ORKM")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-mass))
    (home-page "https://cran.r-project.org/package=ORKM")
    (synopsis "The Online Regularized K-Means Clustering Algorithm")
    (description
     "Algorithm of online regularized k-means to deal with online multi(single) view
data.  The philosophy of the package is described in Guo G. (2020)
<doi:10.1080/02331888.2020.1823979>.")
    (license license:expat)))

(define-public r-orionz-g
  (package
    (name "r-orionz-g")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ORIONZ.G" version))
       (sha256
        (base32 "05223qkvqpr1nr7jxznin11jcyapzp76p47xqhl1jr1hif3akvrb"))))
    (properties `((upstream-name . "ORIONZ.G")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ORIONZ.G")
    (synopsis
     "EAP Scoring in Exploratory FA Solutions with Correlated Residuals")
    (description
     "Obtaining Bayes Expected A Posteriori (EAP) individual score estimates based on
linear and non-linear extended Exploratoy Factor Analysis solutions that include
a correlated-residual structure.")
    (license license:gpl3)))

(define-public r-orion
  (package
    (name "r-orion")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ORION" version))
       (sha256
        (base32 "0zzlvx1yd3hy8dy7nbmkj7d2k6609ys91s894qcgx5n7jirqviy3"))))
    (properties `((upstream-name . "ORION")))
    (build-system r-build-system)
    (propagated-inputs (list r-tunepareto
                             r-rmarkdown
                             r-randomforest
                             r-knitr
                             r-igraph
                             r-foreach
                             r-e1071
                             r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ORION")
    (synopsis "Ordinal Relations")
    (description
     "This package provides functions to handle ordinal relations reflected within the
feature space.  Those function allow to search for ordinal relations in
multi-class datasets.  One can check whether proposed relations are reflected in
a specific feature representation.  Furthermore, it provides functions to
filter, organize and further analyze those ordinal relations.")
    (license license:gpl2)))

(define-public r-origin
  (package
    (name "r-origin")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "origin" version))
       (sha256
        (base32 "0gnq66zsnmnwsn0xaxavw4ipkcb91371g5rh7i9pk863q7fvzkc0"))))
    (properties `((upstream-name . "origin")))
    (build-system r-build-system)
    (propagated-inputs (list r-rstudioapi r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mnist91/origin")
    (synopsis
     "Explicitly Qualifying Namespaces by Automatically Adding 'pkg::' to Functions")
    (description
     "Automatically adding pkg:: to a function, i.e.  mutate() becomes
dplyr::mutate().  It is up to the user to determine which packages should be
used explicitly, whether to include base R packages or use the functionality on
selected text, a file, or a complete directory.  User friendly logging is
provided in the RStudio Markers pane.  Lives in the spirit of lintr and styler'.
 Can also be used for checking which packages are actually used in a project.")
    (license license:expat)))

(define-public r-origamiplot
  (package
    (name "r-origamiplot")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OrigamiPlot" version))
       (sha256
        (base32 "1p2fzv8bx3pxhskf1h9b6mk72b15g0l0ribp4da1vq58xn9cjgil"))))
    (properties `((upstream-name . "OrigamiPlot")))
    (build-system r-build-system)
    (propagated-inputs (list r-plotrix r-fmsb))
    (home-page "https://cran.r-project.org/package=OrigamiPlot")
    (synopsis
     "Visualization Tool Enhancing Radar Plot Visualizations for Multivariate Data")
    (description
     "This package provides a visualization tool for multivariate data.  This package
maintains the original functionality of a radar chart and avoids potential
misuse of its connected regions, with newly added features to better assist
multi-criteria decision-making.")
    (license license:gpl2+)))

(define-public r-origami
  (package
    (name "r-origami")
    (version "1.0.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "origami" version))
       (sha256
        (base32 "0b66alm1mr6vsgj5cgliqxw8vpm1x504qs42crlf0n6339a38h5l"))))
    (properties `((upstream-name . "origami")))
    (build-system r-build-system)
    (propagated-inputs (list r-listenv
                             r-future-apply
                             r-future
                             r-data-table
                             r-assertthat
                             r-abind))
    (native-inputs (list r-knitr))
    (home-page "https://tlverse.org/origami/")
    (synopsis "Generalized Framework for Cross-Validation")
    (description
     "This package provides a general framework for the application of
cross-validation schemes to particular functions.  By allowing arbitrary lists
of results, origami accommodates a range of cross-validation applications.  This
implementation was first described by Coyle and Hejazi (2018)
<doi:10.21105/joss.00512>.")
    (license license:gpl3)))

(define-public r-orientlib
  (package
    (name "r-orientlib")
    (version "0.10.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orientlib" version))
       (sha256
        (base32 "05xwx040l1ln06rkmsg8l4394b3inaf663mw4fng54wwacgv9jfj"))))
    (properties `((upstream-name . "orientlib")))
    (build-system r-build-system)
    (home-page "https://github.com/dmurdoch/orientlib")
    (synopsis "Support for Orientation Data")
    (description
     "Representations, conversions and display of orientation SO(3) data.  See the
orientlib help topic for details.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-oriclust
  (package
    (name "r-oriclust")
    (version "1.0-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ORIClust" version))
       (sha256
        (base32 "036jbfq4klzlppybvcj8wjchcyqmmxwvvr3rn9436cz4zm2yjy4a"))))
    (properties `((upstream-name . "ORIClust")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ORIClust")
    (synopsis
     "Order-Restricted Information Criterion-Based Clustering Algorithm")
    (description
     "This package provides a user-friendly R-based software package for gene
clustering.  Clusters are given by genes matched to prespecified profiles across
various ordered treatment groups.  It is particularly useful for analyzing data
obtained from short time-course or dose-response microarray experiments.")
    (license license:gpl2)))

(define-public r-orgutils
  (package
    (name "r-orgutils")
    (version "0.5-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orgutils" version))
       (sha256
        (base32 "1gvj82m67xmi0kwd883zmqgxnc621q30bgbnnszm5fnb3y2ni7d6"))))
    (properties `((upstream-name . "orgutils")))
    (build-system r-build-system)
    (propagated-inputs (list r-textutils))
    (home-page "http://enricoschumann.net/R/packages/orgutils/")
    (synopsis "Helper Functions for Org Files")
    (description
     "Helper functions for Org files (<https://orgmode.org/>): a generic function
@code{toOrg} for transforming R objects into Org markup (most useful for data
frames; there are also methods for Dates/POSIXt) and a function to read Org
tables into data frames.")
    (license license:gpl2+)))

(define-public r-orgr
  (package
    (name "r-orgr")
    (version "0.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orgR" version))
       (sha256
        (base32 "1q4qbwnbhmja8rqiph7g7m4wxhzhk9mh91x1jgbnky8bs4ljdgrx"))))
    (properties `((upstream-name . "orgR")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-lubridate r-ggthemes r-ggplot2
                             r-data-table))
    (home-page "https://cran.r-project.org/package=orgR")
    (synopsis "Analyse Text Files Created by Emacs' Org mode")
    (description
     "This package provides functionality to process text files created by Emacs Org
mode, and decompose the content to the smallest components (headlines, body,
tag, clock entries etc).  Emacs is an extensible, customizable text editor and
Org mode is for keeping notes, maintaining TODO lists, planning projects.
Allows users to analyze org files as data frames in R, e.g., to convieniently
group tasks by tag into project and calculate total working hours.  Also
provides some help functions like search.parent, gg.pie (visualise working hours
in ggplot2) and tree.headlines (visualise headline stricture in tree format) to
help user managing their complex org files.")
    (license license:gpl2+)))

(define-public r-organizr
  (package
    (name "r-organizr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "organizr" version))
       (sha256
        (base32 "1i6j7c7d588gnjmh3ddknrs95mhw6ikq53c6wd3zy82lmjvh96bv"))))
    (properties `((upstream-name . "organizr")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-rstudioapi
                             r-rlang
                             r-readr
                             r-here
                             r-fs))
    (home-page "https://github.com/jobrachem/organizr")
    (synopsis "Shortcuts for File Creation with Informative Prefixes")
    (description
     "This package provides functions for quickly creating R and Python scripts, as
well as Rmarkdown or Quarto documents with automatically assigned name prefixes.
 Prefixes are either file counts (e.g. \"001\") or dates (e.g. \"2022-09-26\").")
    (license license:expat)))

(define-public r-org
  (package
    (name "r-org")
    (version "2024.6.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "org" version))
       (sha256
        (base32 "1kpaij3qz6amccf01kplmx6ql90qkkqmswq364jj5x2jwx7k5w26"))))
    (properties `((upstream-name . "org")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://www.csids.no/org/")
    (synopsis "Organising Projects")
    (description
     "This package provides a system to help you organize projects.  Most analyses
have three (or more) main sections: code, results, and data, each with different
requirements (version control/sharing/encryption).  You provide folder locations
and org helps you take care of the details.")
    (license license:expat)))

(define-public r-orfid
  (package
    (name "r-orfid")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ORFID" version))
       (sha256
        (base32 "11g4l45x3jwyffamr2qd0h7y15kyynqqwxh1mp1mnv0lchmdyr89"))))
    (properties `((upstream-name . "ORFID")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-rlang
                             r-readr
                             r-openxlsx
                             r-magrittr
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/hugo-marques/ORFID")
    (synopsis
     "Manage and Summarize Data from Oregon RFID ORMR and ORSR Antenna Readers")
    (description
     "Automates and standardizes the import of raw data from Oregon RFID
(radio-frequency identification) ORMR (Oregon RFID Multi-Reader) and ORSR
(Oregon RFID Single Reader) antenna readers.  Compiled data can then be combined
within multi-reader arrays for further analysis, including summarizing tag and
reader detections, determining tag direction, and calculating antenna
efficiency.")
    (license license:expat)))

(define-public r-orf
  (package
    (name "r-orf")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orf" version))
       (sha256
        (base32 "1njcnya5f2wx50l7gyf53js16xj1y6pwgbghxq4nm4grf2ck3mz1"))))
    (properties `((upstream-name . "orf")))
    (build-system r-build-system)
    (propagated-inputs (list r-xtable r-rcpp r-ranger r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/okasag/orf")
    (synopsis "Ordered Random Forests")
    (description
     "An implementation of the Ordered Forest estimator as developed in Lechner &
Okasa (2019) <@code{arXiv:1907.02436>}.  The Ordered Forest flexibly estimates
the conditional probabilities of models with ordered categorical outcomes
(so-called ordered choice models).  Additionally to common machine learning
algorithms the orf package provides functions for estimating marginal effects as
well as statistical inference thereof and thus provides similar output as in
standard econometric models for ordered choice.  The core forest algorithm
relies on the fast C++ forest implementation from the ranger package (Wright &
Ziegler, 2017) <@code{arXiv:1508.04409>}.")
    (license license:gpl3)))

(define-public r-oreo
  (package
    (name "r-oreo")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oreo" version))
       (sha256
        (base32 "1qzv6fjana5fx45msqasqfniiancsch6j8r1llh1xyg2wjhqdj23"))))
    (properties `((upstream-name . "oreo")))
    (build-system r-build-system)
    (propagated-inputs (list r-spectral
                             r-scales
                             r-pracma
                             r-openxlsx
                             r-gridextra
                             r-ggplot2
                             r-fftwtools))
    (home-page "https://cran.r-project.org/package=oreo")
    (synopsis "Large Amplitude Oscillatory Shear (LAOS)")
    (description
     "The Sequence of Physical Processes (SPP) framework is a way of interpreting the
transient data derived from oscillatory rheological tests.  It is designed to
allow both the linear and non-linear deformation regimes to be understood within
a single unified framework.  This code provides a convenient way to determine
the SPP framework metrics for a given sample of oscillatory data.  It will
produce a text file containing the SPP metrics, which the user can then plot
using their software of choice.  It can also produce a second text file with
additional derived data (components of tangent, normal, and binormal vectors),
as well as pre-plotted figures if so desired.  It is the R version of the
Package SPP by Simon Rogers Group for Soft Matter (Simon A. Rogers, Brian M.
Erwin, Dimitris Vlassopoulos, Michel Cloitre (2011) <doi:10.1122/1.3544591>).")
    (license license:gpl2)))

(define-public r-ordr
  (package
    (name "r-ordr")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ordr" version))
       (sha256
        (base32 "07nsl6mdm4dmyl8vsqzcpd2mihcxsm68gjx3v1dfqgjqmz477nvf"))))
    (properties `((upstream-name . "ordr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-scales
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-labeling
                             r-ggrepel
                             r-ggplot2
                             r-generics
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/corybrunson/ordr")
    (synopsis "'tidyverse' Extension for Ordinations and Biplots")
    (description
     "Ordination comprises several multivariate exploratory and explanatory techniques
with theoretical foundations in geometric data analysis; see Podani (2000,
ISBN:90-5782-067-6) for techniques and applications and Le Roux & Rouanet (2005)
<doi:10.1007/1-4020-2236-0> for foundations.  Greenacre (2010,
ISBN:978-84-923846) shows how the most established of these, including principal
components analysis, correspondence analysis, multidimensional scaling, factor
analysis, and discriminant analysis, rely on eigen-decompositions or singular
value decompositions of pre-processed numeric matrix data.  These decompositions
give rise to a set of shared coordinates along which the row and column elements
can be measured.  The overlay of their scatterplots on these axes, introduced by
Gabriel (1971) <doi:10.1093/biomet/58.3.453>, is called a biplot.  ordr provides
inspection, extraction, manipulation, and visualization tools for several
popular ordination classes supported by a set of recovery methods.  It is
inspired by and designed to integrate into tidyverse workflows provided by
Wickham et al (2019) <doi:10.21105/joss.01686>.")
    (license license:gpl3)))

(define-public r-ordpens
  (package
    (name "r-ordpens")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ordPens" version))
       (sha256
        (base32 "1837d2rz42y71yq9rzzkc5pkywvyc4zbk7s4kg4kwrvxysg0y6p1"))))
    (properties `((upstream-name . "ordPens")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlrsim
                             r-quadprog
                             r-ordinalnet
                             r-mgcv
                             r-grplasso
                             r-glmpath))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ordPens")
    (synopsis
     "Selection, Fusion, Smoothing and Principal Components Analysis for Ordinal Variables")
    (description
     "Selection, fusion, and/or smoothing of ordinally scaled independent variables
using a group lasso, fused lasso or generalized ridge penalty, as well as
non-linear principal components analysis for ordinal variables using a
second-order difference/smoothing penalty.")
    (license license:gpl2)))

(define-public r-ordnor
  (package
    (name "r-ordnor")
    (version "2.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OrdNor" version))
       (sha256
        (base32 "0yjvylp8z24w6nbwy9rjyk0y7gpzsxzsqm8x4q4fn8g87cb3314v"))))
    (properties `((upstream-name . "OrdNor")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-matrix r-genord r-corpcor))
    (home-page "https://cran.r-project.org/package=OrdNor")
    (synopsis
     "Concurrent Generation of Ordinal and Normal Data with Given Correlation Matrix and Marginal Distributions")
    (description
     "Implementation of a procedure for generating samples from a mixed distribution
of ordinal and normal random variables with a pre-specified correlation matrix
and marginal distributions.  The details of the method are explained in Demirtas
et al. (2015) <DOI:10.1080/10543406.2014.920868>.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-ordmonreg
  (package
    (name "r-ordmonreg")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OrdMonReg" version))
       (sha256
        (base32 "1xca8pvvq79j484l2rmn4nva8ncx8z51g5diljikck231y8qjqaz"))))
    (properties `((upstream-name . "OrdMonReg")))
    (build-system r-build-system)
    (home-page "http://www.ceremade.dauphine.fr/~fadoua")
    (synopsis
     "Compute least squares estimates of one bounded or two ordered isotonic regression curves")
    (description
     "We consider the problem of estimating two isotonic regression curves g1* and g2*
under the constraint that they are ordered, i.e.  g1* <= g2*.  Given two sets of
n data points y_1, ..., y_n and z_1, ..., z_n that are observed at (the same)
deterministic design points x_1, ..., x_n, the estimates are obtained by
minimizing the Least Squares criterion L(a, b) = sum_{i=1}^n (y_i - a_i)^2
w1(x_i) + sum_{i=1}^n (z_i - b_i)^2 w2(x_i) over the class of pairs of vectors
(a, b) such that a and b are isotonic and a_i <= b_i for all i = 1, ..., n.  We
offer two different approaches to compute the estimates: a projected subgradient
algorithm where the projection is calculated using a PAVA as well as Dykstra's
cyclical projection algorithm.")
    (license license:gpl2+)))

(define-public r-ordinalrr
  (package
    (name "r-ordinalrr")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ordinalRR" version))
       (sha256
        (base32 "1sfkq8gryyls22208ympw5scgb4jkd27pyc1qklw4x7cz9wfnfbp"))))
    (properties `((upstream-name . "ordinalRR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rjags))
    (home-page "https://cran.r-project.org/package=ordinalRR")
    (synopsis
     "Analysis of Repeatability and Reproducibility Studies with Ordinal Measurements")
    (description
     "This package implements Bayesian data analyses of balanced repeatability and
reproducibility studies with ordinal measurements.  Model fitting is based on
MCMC posterior sampling with rjags'.  Function @code{ordinalRR}() directly
carries out the model fitting, and this function has the flexibility to allow
the user to specify key aspects of the model, e.g., fixed versus random effects.
 Functions for preprocessing data and for the numerical and graphical display of
a fitted model are also provided.  There are also functions for displaying the
model at fixed (user-specified) parameters and for simulating a hypothetical
data set at a fixed (user-specified) set of parameters for a random-effects
rater population.  For additional technical details, refer to Culp, Ryan, Chen,
and Hamada (2018) and cite this Technometrics paper when referencing any aspect
of this work.  The demo of this package reproduces results from the
Technometrics paper.")
    (license license:gpl2)))

(define-public r-ordinalpattern
  (package
    (name "r-ordinalpattern")
    (version "0.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ordinalpattern" version))
       (sha256
        (base32 "0vczxz0z3ixn0gv694dy31ywcx0iz8x821129jisy1x79yi36f29"))))
    (properties `((upstream-name . "ordinalpattern")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm r-gtools))
    (home-page "https://cran.r-project.org/package=ordinalpattern")
    (synopsis "Tests Based on Ordinal Patterns")
    (description
     "Ordinal patterns describe the dynamics of a time series by looking at the ranks
of subsequent observations.  By comparing ordinal patterns of two times series,
Schnurr (2014) <doi:10.1007/s00362-013-0536-8> defines a robust and
non-parametric dependence measure: the ordinal pattern coefficient.  Functions
to calculate this and a method to detect a change in the pattern coefficient
proposed in Schnurr and Dehling (2017) <doi:10.1080/01621459.2016.1164706> are
provided.  Furthermore, the package contains a function for calculating the
ordinal pattern frequencies.  Generalized ordinal patterns as proposed by
Schnurr and Fischer (2022) <doi:10.1016/j.csda.2022.107472> are also considered.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-ordinalnet
  (package
    (name "r-ordinalnet")
    (version "2.12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ordinalNet" version))
       (sha256
        (base32 "0ijgxp1lh4hbgks0p5041f5s6kpfrlm6f7hdz2nm3dn1rhq6bwvi"))))
    (properties `((upstream-name . "ordinalNet")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ordinalNet")
    (synopsis "Penalized Ordinal Regression")
    (description
     "Fits ordinal regression models with elastic net penalty.  Supported model
families include cumulative probability, stopping ratio, continuation ratio, and
adjacent category.  These families are a subset of vector glm's which belong to
a model class we call the elementwise link multinomial-ordinal (ELMO) class.
Each family in this class links a vector of covariates to a vector of class
probabilities.  Each of these families has a parallel form, which is appropriate
for ordinal response data, as well as a nonparallel form that is appropriate for
an unordered categorical response, or as a more flexible model for ordinal data.
 The parallel model has a single set of coefficients, whereas the nonparallel
model has a set of coefficients for each response category except the baseline
category.  It is also possible to fit a model with both parallel and nonparallel
terms, which we call the semi-parallel model.  The semi-parallel model has the
flexibility of the nonparallel model, but the elastic net penalty shrinks it
toward the parallel model.  For details, refer to Wurm, Hanlon, and Rathouz
(2021) <doi:10.18637/jss.v099.i06>.")
    (license license:expat)))

(define-public r-ordinallbm
  (package
    (name "r-ordinallbm")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ordinalLBM" version))
       (sha256
        (base32 "1sfzkm3f9s5nbalakgk5v919wr7hdlr5p280rw2p8dy4wxr3xk3s"))))
    (properties `((upstream-name . "ordinalLBM")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2 r-rcolorbrewer))
    (home-page "https://cran.r-project.org/package=ordinalLBM")
    (synopsis
     "Co-Clustering of Ordinal Data via Latent Continuous Random Variables")
    (description
     "It implements functions for simulation and estimation of the ordinal latent
block model (OLBM), as described in Corneli, Bouveyron and Latouche (2019).")
    (license license:gpl2+)))

(define-public r-ordinalgmifs
  (package
    (name "r-ordinalgmifs")
    (version "1.0.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ordinalgmifs" version))
       (sha256
        (base32 "0c97c3zss34x9n8szr95z51qx8ix55mlrbqvg8dz128xpd3684rj"))))
    (properties `((upstream-name . "ordinalgmifs")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival))
    (home-page "https://cran.r-project.org/package=ordinalgmifs")
    (synopsis "Ordinal Regression for High-Dimensional Data")
    (description
     "This package provides a function for fitting cumulative link, adjacent category,
forward and backward continuation ratio, and stereotype ordinal response models
when the number of parameters exceeds the sample size, using the the generalized
monotone incremental forward stagewise method.")
    (license license:gpl2+)))

(define-public r-ordinalforest
  (package
    (name "r-ordinalforest")
    (version "2.4-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ordinalForest" version))
       (sha256
        (base32 "06blmwmn42dv6sri3j3473arrql5rihdlp7kgh56b2w1j2wdqq7s"))))
    (properties `((upstream-name . "ordinalForest")))
    (build-system r-build-system)
    (propagated-inputs (list r-verification r-rcpp r-nnet r-combinat))
    (home-page "https://cran.r-project.org/package=ordinalForest")
    (synopsis
     "Ordinal Forests: Prediction and Variable Ranking with Ordinal Target Variables")
    (description
     "The ordinal forest (OF) method allows ordinal regression with high-dimensional
and low-dimensional data.  After having constructed an OF prediction rule using
a training dataset, it can be used to predict the values of the ordinal target
variable for new observations.  Moreover, by means of the (permutation-based)
variable importance measure of OF, it is also possible to rank the covariates
with respect to their importance in the prediction of the values of the ordinal
target variable.  OF is presented in Hornung (2020).  NOTE: Starting with
package version 2.4, it is also possible to obtain class probability predictions
in addition to the class point predictions.  Moreover, the variable importance
values can also be based on the class probability predictions.  Preliminary
results indicate that this might lead to a better discrimination between
influential and non-influential covariates.  The main functions of the package
are: ordfor() (construction of OF) and predict.ordfor() (prediction of the
target variable values of new observations).  References: Hornung R. (2020)
Ordinal Forests.  Journal of Classification 37, 4â17.
<doi:10.1007/s00357-018-9302-x>.")
    (license license:gpl2)))

(define-public r-ordinalcont
  (package
    (name "r-ordinalcont")
    (version "2.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ordinalCont" version))
       (sha256
        (base32 "1azwcr1si3b8dxf2y59d3rxw4msfq79khzg7zgqd0kbzyka4ygl8"))))
    (properties `((upstream-name . "ordinalCont")))
    (build-system r-build-system)
    (propagated-inputs (list r-deriv r-boot))
    (home-page "https://cran.r-project.org/package=ordinalCont")
    (synopsis "Ordinal Regression Analysis for Continuous Scales")
    (description
     "This package provides a regression framework for response variables which are
continuous self-rating scales such as the Visual Analog Scale (VAS) used in pain
assessment, or the Linear Analog Self-Assessment (LASA) scales in quality of
life studies.  These scales measure subjects perception of an intangible
quantity, and cannot be handled as ratio variables because of their inherent
non-linearity.  We treat them as ordinal variables, measured on a continuous
scale.  A function (the g function) connects the scale with an underlying
continuous latent variable.  The link function is the inverse of the CDF of the
assumed underlying distribution of the latent variable.  A variety of link
functions are currently implemented.  Such models are described in Manuguerra et
al (2020) <doi:10.18637/jss.v096.i08>.")
    (license license:gpl2+)))

(define-public r-ordinalbayes
  (package
    (name "r-ordinalbayes")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ordinalbayes" version))
       (sha256
        (base32 "13f9rv6gndjr18rfk60rmginzam1xjsssjn45l6hhl6y3gglsyzh"))))
    (properties `((upstream-name . "ordinalbayes")))
    (build-system r-build-system)
    (inputs (list jags))
    (propagated-inputs (list r-summarizedexperiment
                             r-runjags
                             r-devtools
                             r-deseq2
                             r-dclone
                             r-coda))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/kelliejarcher/ordinalbayes")
    (synopsis "Bayesian Ordinal Regression for High-Dimensional Data")
    (description
     "This package provides a function for fitting various penalized Bayesian
cumulative link ordinal response models when the number of parameters exceeds
the sample size.  These models have been described in Zhang and Archer (2021)
<doi:10.1186/s12859-021-04432-w>.")
    (license license:expat)))

(define-public r-ordibreadth
  (package
    (name "r-ordibreadth")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ordiBreadth" version))
       (sha256
        (base32 "04faqhas1p9lxhghd4xq07yq1nxv7ns18avhvkql7sy5a9g7bfs1"))))
    (properties `((upstream-name . "ordiBreadth")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan))
    (home-page "https://cran.r-project.org/package=ordiBreadth")
    (synopsis "Ordinated Diet Breadth")
    (description
     "Calculates ordinated diet breadth with some plotting functions.")
    (license license:gpl3+)))

(define-public r-ordgam
  (package
    (name "r-ordgam")
    (version "0.9.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ordgam" version))
       (sha256
        (base32 "0flldxv53qyiprq44670b4b98i791si3nmi983pgkzd8s39aa68l"))))
    (properties `((upstream-name . "ordgam")))
    (build-system r-build-system)
    (propagated-inputs (list r-ucminf
                             r-sn
                             r-numderiv
                             r-mgcv
                             r-matrix
                             r-mass
                             r-marqlevalg
                             r-cubicbsplines))
    (home-page "<https://github.com/plambertULiege/ordgam>")
    (synopsis "Additive Model for Ordinal Data using Laplace P-Splines")
    (description
     "Additive proportional odds model for ordinal data using Laplace P-splines.  The
combination of Laplace approximations and P-splines enable fast and flexible
inference in a Bayesian framework.  Specific approximations are proposed to
account for the asymmetry in the marginal posterior distributions of
non-penalized parameters.  For more details, see Lambert and Gressani (2023)
<doi:10.1177/1471082X231181173> ; Preprint: <@code{arXiv:2210.01668>}).")
    (license license:gpl3)))

(define-public r-ordfacreg
  (package
    (name "r-ordfacreg")
    (version "1.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OrdFacReg" version))
       (sha256
        (base32 "16mavsmp6d8rfmimmp5ynwyzir0gycpg8rhd8cwanlrndyclqlpv"))))
    (properties `((upstream-name . "OrdFacReg")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-mass r-eha))
    (home-page "http://www.kasparrufibach.ch")
    (synopsis
     "Least Squares, Logistic, and Cox-Regression with Ordered Predictors")
    (description
     "In biomedical studies, researchers are often interested in assessing the
association between one or more ordinal explanatory variables and an outcome
variable, at the same time adjusting for covariates of any type.  The outcome
variable may be continuous, binary, or represent censored survival times.  In
the absence of a precise knowledge of the response function, using monotonicity
constraints on the ordinal variables improves efficiency in estimating
parameters, especially when sample sizes are small.  This package implements an
active set algorithm that efficiently computes such estimators.")
    (license license:gpl2+)))

(define-public r-orderstats
  (package
    (name "r-orderstats")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orderstats" version))
       (sha256
        (base32 "0a3ga0cjryvbininspsx5wzc96s3fza06s3d5fhbllbixz0rap4a"))))
    (properties `((upstream-name . "orderstats")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=orderstats")
    (synopsis "Efficiently Generates Random Order Statistic Variables")
    (description
     "All the methods in this package generate a vector of uniform order statistics
using a beta distribution and use an inverse cumulative distribution function
for some distribution to give a vector of random order statistic variables for
some distribution.  This is much more efficient than using a loop since it is
directly sampling from the order statistic distribution.")
    (license license:gpl2)))

(define-public r-orders
  (package
    (name "r-orders")
    (version "0.1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orders" version))
       (sha256
        (base32 "05fq8mvqjvm4dir7zc7dxri3n6ar08afvrg49x8hbf920yqxkmq1"))))
    (properties `((upstream-name . "orders")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam r-newdistns r-gamlss-dist r-actuar))
    (home-page "https://cran.r-project.org/package=orders")
    (synopsis
     "Sampling from k-th Order Statistics of New Families of Distributions")
    (description
     "Set of tools to generate samples of k-th order statistics and others quantities
of interest from new families of distributions.  The main references for this
package are: C. Kleiber and S. Kotz (2003) Statistical size distributions in
economics and actuarial sciences; Gentle, J. (2009), Computational Statistics,
Springer-Verlag; Naradajah, S. and Rocha, R. (2016), <DOI:10.18637/jss.v069.i10>
and Stasinopoulos, M. and Rigby, R. (2015),
<DOI:10.1111/j.1467-9876.2005.00510.x>.  The families of distributions are:
Benini distributions, Burr distributions, Dagum distributions, Feller-Pareto
distributions, Generalized Pareto distributions, Inverse Pareto distributions,
The Inverse Paralogistic distributions, Marshall-Olkin G distributions,
exponentiated G distributions, beta G distributions, gamma G distributions,
Kumaraswamy G distributions, generalized beta G distributions, beta extended G
distributions, gamma G distributions, gamma uniform G distributions, beta
exponential G distributions, Weibull G distributions, log gamma G I
distributions, log gamma G II distributions, exponentiated generalized G
distributions, exponentiated Kumaraswamy G distributions, geometric exponential
Poisson G distributions, truncated-exponential skew-symmetric G distributions,
modified beta G distributions, exponentiated exponential Poisson G
distributions, Poisson-inverse gaussian distributions, Skew normal type 1
distributions, Skew student t distributions, Singh-Maddala distributions,
Sinh-Arcsinh distributions, Sichel distributions, Zero inflated Poisson
distributions.")
    (license license:gpl3)))

(define-public r-orderly
  (package
    (name "r-orderly")
    (version "1.4.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orderly" version))
       (sha256
        (base32 "0k7xk64schhw9jdbg50hlnf6gfhlgnv1n20rz3fga02z38441xkn"))))
    (properties `((upstream-name . "orderly")))
    (build-system r-build-system)
    (inputs (list git))
    (propagated-inputs (list r-zip
                             r-yaml
                             r-withr
                             r-rsqlite
                             r-r6
                             r-ids
                             r-gert
                             r-fs
                             r-docopt
                             r-digest
                             r-dbi
                             r-crayon))
    (native-inputs (list r-knitr))
    (home-page "https://www.vaccineimpact.org/orderly/")
    (synopsis "Lightweight Reproducible Reporting")
    (description
     "Order, create and store reports from R. By defining a lightweight interface
around the inputs and outputs of an analysis, a lot of the repetitive work for
reproducible research can be automated.  We define a simple format for
organising and describing work that facilitates collaborative reproducible
research and acknowledges that all analyses are run multiple times over their
lifespans.")
    (license license:expat)))

(define-public r-ordering
  (package
    (name "r-ordering")
    (version "0.7.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ordering" version))
       (sha256
        (base32 "0sgwgcjg6sazmi11c9qvxfrzg671kcp18i2q20xbmbj4v3yqhwbh"))))
    (properties `((upstream-name . "ordering")))
    (build-system r-build-system)
    (home-page "https://github.com/decisionpatterns/ordering")
    (synopsis
     "Test, Check, Verify, Investigate the Monotonic Properties of Vectors")
    (description
     "This package provides functions to test/check/verify/investigate the ordering of
vectors.  The is_[strictly_]* family of functions test vectors for sorted',
monotonic', increasing', decreasing order; is_constant and is_incremental test
for the degree of ordering. `ordering` provides a numeric indication of ordering
-2 (strictly decreasing) to 2 (strictly increasing).")
    (license license:gpl2+)))

(define-public r-orddisp
  (package
    (name "r-orddisp")
    (version "2.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ordDisp" version))
       (sha256
        (base32 "0906y98ydiadyqhz9ad2ssw1282a10c418k20vkbwzad2xip7grg"))))
    (properties `((upstream-name . "ordDisp")))
    (build-system r-build-system)
    (propagated-inputs (list r-vgam))
    (home-page "https://cran.r-project.org/package=ordDisp")
    (synopsis
     "Separating Location and Dispersion in Ordinal Regression Models")
    (description
     "Estimate location-shift models or rating-scale models accounting for response
styles (RSRS) for the regression analysis of ordinal responses.")
    (license license:gpl2)))

(define-public r-ordcrm
  (package
    (name "r-ordcrm")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ordcrm" version))
       (sha256
        (base32 "1hy24s23l099b21w5j3p2f0748s8xmhxhslfp65fg7ycwda5qsyw"))))
    (properties `((upstream-name . "ordcrm")))
    (build-system r-build-system)
    (propagated-inputs (list r-rms))
    (home-page "https://cran.r-project.org/package=ordcrm")
    (synopsis
     "Likelihood-Based Continual Reassessment Method (CRM) Dose Finding Designs")
    (description
     "This package provides the setup and calculations needed to run a
likelihood-based continual reassessment method (CRM) dose finding trial and
performs simulations to assess design performance under various scenarios.  3
dose finding designs are included in this package: ordinal proportional odds
model (POM) CRM, ordinal continuation ratio (CR) model CRM, and the binary
2-parameter logistic model CRM. These functions allow customization of design
characteristics to vary sample size, cohort sizes, target dose-limiting toxicity
(DLT) rates, discrete or continuous dose levels, combining ordinal grades 0 and
1 into one category, and incorporate safety and/or stopping rules.  For POM and
CR model designs, ordinal toxicity grades are specified by common terminology
criteria for adverse events (CTCAE) version 4.0.  Function pseudodata creates
the necessary starting models for these 3 designs, and function nextdose
estimates the next dose to test in a cohort of patients for a target DLT rate.
We also provide the function crmsimulations to assess the performance of these 3
dose finding designs under various scenarios.")
    (license license:gpl2+)))

(define-public r-ordcd
  (package
    (name "r-ordcd")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OrdCD" version))
       (sha256
        (base32 "1wg4sxirzp8r91qzzvrx4yashg1f574ayaxbviy8hdca3iydfl1j"))))
    (properties `((upstream-name . "OrdCD")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-mass r-igraph r-grbase r-bnlearn))
    (home-page "https://github.com/nySTAT/OrdCD")
    (synopsis "Ordinal Causal Discovery")
    (description
     "Algorithms for ordinal causal discovery.  This package aims to enable users to
discover causality for observational ordinal categorical data with greedy and
exhaustive search.  See Ni, Y., & Mallick, B. (2022)
<https://proceedings.mlr.press/v180/ni22a/ni22a.pdf> \"Ordinal Causal Discovery.
Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence,
(UAI 2022), PMLR 180:1530â1540\".")
    (license license:expat)))

(define-public r-ordbetareg
  (package
    (name "r-ordbetareg")
    (version "0.7.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ordbetareg" version))
       (sha256
        (base32 "12z5ig4m62fy6j76anidj6gpy0g2xcr35yv0xv0avgi57wf4rpwv"))))
    (properties `((upstream-name . "ordbetareg")))
    (build-system r-build-system)
    (propagated-inputs (list r-transformr
                             r-tidyr
                             r-ggplot2
                             r-gganimate
                             r-dplyr
                             r-brms))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ordbetareg")
    (synopsis "Ordered Beta Regression Models with 'brms'")
    (description
     "This package implements ordered beta regression models, which are for modeling
continuous variables with upper and lower bounds, such as survey sliders,
dose-response relationships and indexes.  For more information, see Kubinec
(2022) <doi:10.31235/osf.io/2sx6y>.  The package is a front-end to the R package
brms', which facilitates a range of regression specifications, including
hierarchical, dynamic and multivariate modeling.")
    (license license:expat)))

(define-public r-orcutt
  (package
    (name "r-orcutt")
    (version "2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orcutt" version))
       (sha256
        (base32 "0pj7pqzbcg4gp35nsz3avyawmx69dgj0l2w0x8ypw5qwl4zhmnyk"))))
    (properties `((upstream-name . "orcutt")))
    (build-system r-build-system)
    (propagated-inputs (list r-lmtest))
    (home-page "https://cran.r-project.org/package=orcutt")
    (synopsis "Estimate Procedure in Case of First Order Autocorrelation")
    (description
     "Solve first order autocorrelation problems using an iterative method.  This
procedure estimates both autocorrelation and beta coefficients recursively until
we reach the convergence (8th decimal as default).  The residuals are computed
after estimating Beta using EGLS approach and Rho is estimated using the
previous residuals.")
    (license license:gpl2)))

(define-public r-orcs
  (package
    (name "r-orcs")
    (version "1.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Orcs" version))
       (sha256
        (base32 "0b2h0vyvp6hnp9i03c8yxfhrlbdq0akdlw2ik0k5c09wfiq7amq6"))))
    (properties `((upstream-name . "Orcs")))
    (build-system r-build-system)
    (inputs (list))
    (propagated-inputs (list r-terra
                             r-sp
                             r-sf
                             r-remotes
                             r-rcpp
                             r-plotrix
                             r-latticeextra
                             r-lattice
                             r-knitr
                             r-bookdown))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/fdetsch/Orcs")
    (synopsis "Omnidirectional R Code Snippets")
    (description
     "I tend to repeat the same code chunks over and over again.  At first, this was
fine for me and I paid little attention to such redundancies.  A little later,
when I got tired of manually replacing Linux filepaths with the referring
Windows versions, and vice versa, I started to stuff some very frequently used
work-steps into functions and, even later, into a proper R package.  And that's
what this package is - a hodgepodge of various R functions meant to simplify
(my) everyday-life coding work without, at the same time, being devoted to a
particular scope of application.")
    (license license:expat)))

(define-public r-orcme
  (package
    (name "r-orcme")
    (version "2.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ORCME" version))
       (sha256
        (base32 "1pm8ajj24qqj2fir0gjzq5f4mfpl1cnj6fm2z5qg6g3sbnm57ayk"))))
    (properties `((upstream-name . "ORCME")))
    (build-system r-build-system)
    (propagated-inputs (list r-iso))
    (home-page "https://cran.r-project.org/package=ORCME")
    (synopsis "Order Restricted Clustering for Microarray Experiments")
    (description
     "This package provides clustering of genes with similar dose response (or time
course) profiles.  It implements the method described by Lin et al. (2012).")
    (license license:gpl3)))

(define-public r-orclus
  (package
    (name "r-orclus")
    (version "0.2-6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orclus" version))
       (sha256
        (base32 "0d78mn2vl2yxlvdswyxkxp9zg59b8cvfksz9m56kddn79aps1ikl"))))
    (properties `((upstream-name . "orclus")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=orclus")
    (synopsis
     "Subspace Clustering Based on Arbitrarily Oriented Projected Cluster Generation")
    (description
     "This package provides functions to perform subspace clustering and
classification.")
    (license license:gpl2+)))

(define-public r-orca
  (package
    (name "r-orca")
    (version "1.1-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orca" version))
       (sha256
        (base32 "1bcksv7rrrpxjaj42ddcfn2v9gi70233p7lrik5rv0dvl4wblbhf"))))
    (properties `((upstream-name . "orca")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=orca")
    (synopsis "Computation of Graphlet Orbit Counts in Sparse Graphs")
    (description
     "This package implements orbit counting using a fast combinatorial approach.
Counts orbits of nodes and edges from edge matrix or data frame, or a graph
object from the graph package.")
    (license license:lgpl3)))

(define-public r-orbital
  (package
    (name "r-orbital")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "orbital" version))
       (sha256
        (base32 "167hpki2v1m8n0fpx3giy7pdc49lwcsn1qacgi38f7m8v0dca4ga"))))
    (properties `((upstream-name . "orbital")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-dplyr r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/tidymodels/orbital")
    (synopsis "Predict with 'tidymodels' Workflows in Databases")
    (description
     "Turn tidymodels workflows into objects containing the sufficient sequential
equations to perform predictions.  These smaller objects allow for low
dependency prediction locally or directly in databases.")
    (license license:expat)))

(define-public r-oralopioids
  (package
    (name "r-oralopioids")
    (version "2.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OralOpioids" version))
       (sha256
        (base32 "0r090bhdv221ng4acwwppzk907h3vb10nachy32zdx2nfs0dqid7"))))
    (properties `((upstream-name . "OralOpioids")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-tidyr
                             r-stringr
                             r-rvest
                             r-rlang
                             r-reshape2
                             r-readr
                             r-purrr
                             r-plyr
                             r-openxlsx
                             r-magrittr
                             r-jsonlite
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ankonahouston/OralOpioids")
    (synopsis "Retrieving Oral Opioid Information")
    (description
     "This package provides details such as Morphine Equivalent Dose (MED), brand name
and opioid content which are calculated of all oral opioids authorized for sale
by Health Canada and the FDA based on their Drug Identification Number (DIN) or
National Drug Code (NDC).  MEDs are calculated based on recommendations by
Canadian Institute for Health Information (CIHI) and Von Korff et al (2008) and
information obtained from Health Canada's Drug Product Database's monthly data
dump or FDA Daily database for Canadian and US databases respectively.  Please
note in no way should output from this package be a substitute for medical
advise.  All medications should only be consumed on prescription from a licensed
healthcare provider.")
    (license license:gpl3)))

(define-public r-opusminer
  (package
    (name "r-opusminer")
    (version "0.1-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "opusminer" version))
       (sha256
        (base32 "1vw6pbk1iiaxmfws95wmwf56p3afk10s5c3x9f0lliamckpyzkck"))))
    (properties `((upstream-name . "opusminer")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-matrix r-arules))
    (home-page "https://cran.r-project.org/package=opusminer")
    (synopsis "OPUS Miner Algorithm for Filtered Top-k Association Discovery")
    (description
     "This package provides a simple R interface to the OPUS Miner algorithm
(implemented in C++) for finding the top-k productive, non-redundant itemsets
from transaction data.  The OPUS Miner algorithm uses the OPUS search algorithm
to efficiently discover the key associations in transaction data, in the form of
self-sufficient itemsets, using either leverage or lift.  See
<http://i.giwebb.com/index.php/research/association-discovery/> for more
information in relation to the OPUS Miner algorithm.")
    (license license:gpl3)))

(define-public r-optweight
  (package
    (name "r-optweight")
    (version "0.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optweight" version))
       (sha256
        (base32 "1mfk9sp47flqq7i762wip5191j8m0q9kbyxs4a7f0pd76qwf67q2"))))
    (properties `((upstream-name . "optweight")))
    (build-system r-build-system)
    (propagated-inputs (list r-osqp r-matrix r-ggplot2))
    (home-page "https://cran.r-project.org/package=optweight")
    (synopsis "Targeted Stable Balancing Weights Using Optimization")
    (description
     "Use optimization to estimate weights that balance covariates for binary,
multinomial, and continuous treatments in the spirit of Zubizarreta (2015)
<doi:10.1080/01621459.2015.1023805>.  The degree of balance can be specified for
each covariate.  In addition, sampling weights can be estimated that allow a
sample to generalize to a population specified with given target moments of
covariates.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-opttesting
  (package
    (name "r-opttesting")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OPTtesting" version))
       (sha256
        (base32 "1d5pkvrzz5hvr764kyliyba5mgix9y340gdcvc0d0si41rz12r91"))))
    (properties `((upstream-name . "OPTtesting")))
    (build-system r-build-system)
    (propagated-inputs (list r-rspectra r-rootsolve r-quantreg))
    (home-page "https://cran.r-project.org/package=OPTtesting")
    (synopsis "Optimal Testing")
    (description
     "Optimal testing under general dependence.  The R package implements procedures
proposed in Wang, Han, and Tong (2022).  The package includes parameter
estimation procedures, the computation for the posterior probabilities, and the
testing procedure.")
    (license license:gpl2)))

(define-public r-optsig
  (package
    (name "r-optsig")
    (version "2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OptSig" version))
       (sha256
        (base32 "0fdszrblayi2hlmkgvwqxw1fh5nh2jad6sxlc788jrzjrd8nkldj"))))
    (properties `((upstream-name . "OptSig")))
    (build-system r-build-system)
    (propagated-inputs (list r-pwr))
    (home-page "https://cran.r-project.org/package=OptSig")
    (synopsis
     "Optimal Level of Significance for Regression and Other Statistical Tests")
    (description
     "The optimal level of significance is calculated based on a decision-theoretic
approach.  The optimal level is chosen so that the expected loss from hypothesis
testing is minimized.  A range of statistical tests are covered, including the
test for the population mean, population proportion, and a linear restriction in
a multiple regression model.  The details are covered in Kim and Choi (2020)
<doi:10.1111/abac.12172>, and Kim (2021) <doi:10.1080/00031305.2020.1750484>.")
    (license license:gpl2)))

(define-public r-opts
  (package
    (name "r-opts")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OPTS" version))
       (sha256
        (base32 "0h382gcjq2f4qm63xnqvhjvxyn9w01dzx8964fk6cm2izhw04bk2"))))
    (properties `((upstream-name . "OPTS")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-cvtools r-changepoint))
    (home-page "https://cran.r-project.org/package=OPTS")
    (synopsis "Optimization via Subsampling (OPTS)")
    (description
     "Subsampling based variable selection for low dimensional generalized linear
models.  The methods repeatedly subsample the data minimizing an information
criterion (AIC/BIC) over a sequence of nested models for each subsample.
Marinela Capanu, Mihai Giurcanu, Colin B Begg, Mithat Gonen, Subsampling based
variable selection for generalized linear models.")
    (license license:gpl2)))

(define-public r-optrf
  (package
    (name "r-optrf")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optRF" version))
       (sha256
        (base32 "02imgfmfigcps4z4028r7jp61153m4ircb4l1axszcaag0181gba"))))
    (properties `((upstream-name . "optRF")))
    (build-system r-build-system)
    (propagated-inputs (list r-ranger r-minpack-lm r-irr))
    (home-page "https://cran.r-project.org/package=optRF")
    (synopsis
     "Optimising Random Forest Stability Through Selection of the Optimal Number of Trees")
    (description
     "Calculating the stability of random forest with certain numbers of trees.  The
non-linear relationship between stability and numbers of trees is described
using a logistic regression model and used to estimate the optimal number of
trees.")
    (license license:gpl2+)))

(define-public r-optrefine
  (package
    (name "r-optrefine")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optrefine" version))
       (sha256
        (base32 "1ijahjraiaax0xyr1y4s3aq1b4xk8h7ablrvy2m2fr879q3xfi9i"))))
    (properties `((upstream-name . "optrefine")))
    (build-system r-build-system)
    (propagated-inputs (list r-sampling r-rglpk r-mass r-ggplot2))
    (home-page "https://github.com/kkbrum/optrefine")
    (synopsis "Optimally Refine Strata")
    (description
     "Splits initial strata into refined strata that optimize covariate balance.  For
more information, please email the author for a copy of the accompanying
manuscript.  To solve the linear program, the Gurobi commercial optimization
software is recommended, but not required.  The gurobi R package can be
installed following the instructions at
<https://www.gurobi.com/documentation/9.1/refman/ins_the_r_package.html>.")
    (license license:gpl3+)))

(define-public r-optrcdmaeat
  (package
    (name "r-optrcdmaeat")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optrcdmaeAT" version))
       (sha256
        (base32 "16g4612mwyfsckn6l71fbrjnnjv4yvnac1cccbrn3k8jh07qgb1h"))))
    (properties `((upstream-name . "optrcdmaeAT")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-mass r-igraph))
    (home-page "https://cran.r-project.org/package=optrcdmaeAT")
    (synopsis
     "Optimal Row-Column Designs for Two-Colour cDNA Microarray Experiments")
    (description
     "Computes A-, MV-, D- and E-optimal or near-optimal row-column designs for
two-colour @code{cDNA} microarray experiments using the linear fixed effects and
mixed effects models where the interest is in a comparison of all pairwise
treatment contrasts.  The algorithms used in this package are based on the array
exchange and treatment exchange algorithms adopted from Debusho, Gemechu and
Haines (2016, unpublished) algorithms after adjusting for the row-column designs
setup.  The package also provides an optional method of using the graphical user
interface (GUI) R package tcltk to ensure that it is user friendly.")
    (license license:gpl2)))

(define-public r-optr
  (package
    (name "r-optr")
    (version "1.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optR" version))
       (sha256
        (base32 "0q7jf4m0gzm11izl5lff17pvr855smqmc6zzi1bc7m6h3z865l32"))))
    (properties `((upstream-name . "optR")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=optR")
    (synopsis "Optimization Toolbox for Solving Linear Systems")
    (description
     "Solves linear systems of form Ax=b via Gauss elimination, LU decomposition,
Gauss-Seidel, Conjugate Gradient Method (CGM) and Cholesky methods.")
    (license license:gpl2+)))

(define-public r-optpart
  (package
    (name "r-optpart")
    (version "3.0-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optpart" version))
       (sha256
        (base32 "18h659gbgzflq81lcchc058xjgljkmhpsjkh51ylygwrv1qjrz2i"))))
    (properties `((upstream-name . "optpart")))
    (build-system r-build-system)
    (propagated-inputs (list r-plotrix r-mass r-labdsv r-cluster))
    (native-inputs (list gfortran))
    (home-page "http://ecology.msu.montana.edu/labdsv/R")
    (synopsis "Optimal Partitioning of Similarity Relations")
    (description
     "This package contains a set of algorithms for creating partitions and coverings
of objects largely based on operations on (dis)similarity relations (or
matrices).  There are several iterative re-assignment algorithms optimizing
different goodness-of-clustering criteria.  In addition, there are covering
algorithms clique which derives maximal cliques, and maxpact which creates a
covering of maximally compact sets.  Graphical analyses and conversion routines
are also included.")
    (license license:gpl2+)))

(define-public r-optmatch
  (package
    (name "r-optmatch")
    (version "0.10.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optmatch" version))
       (sha256
        (base32 "14a93plyhm3j009lcqwvh94zcd5i90kvp92y0kjb0ahn1bmanc2i"))))
    (properties `((upstream-name . "optmatch")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-rlemon r-rcpp r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "http://optmat.ch")
    (synopsis "Functions for Optimal Matching")
    (description
     "Distance based bipartite matching using minimum cost flow, oriented to matching
of treatment and control groups in observational studies ('Hansen and Klopfer
2006 <doi:10.1198/106186006X137047>).  Routines are provided to generate
distances from generalised linear models (propensity score matching), formulas
giving variables on which to limit matched distances, stratified or exact
matching directives, or calipers, alone or in combination.")
    (license license:expat)))

(define-public r-optm
  (package
    (name "r-optm")
    (version "0.1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OptM" version))
       (sha256
        (base32 "00xjzpfnri2k0p04cv98vwwymv16pbw79znklg1k3xc4rxg8wd25"))))
    (properties `((upstream-name . "OptM")))
    (build-system r-build-system)
    (propagated-inputs (list r-sizer))
    (home-page "https://cran.r-project.org/package=OptM")
    (synopsis
     "Estimating the Optimal Number of Migration Edges from 'Treemix'")
    (description
     "The popular population genetic software Treemix by Pickrell and Pritchard (2012)
<DOI:10.1371/journal.pgen.1002967> estimates the number of migration edges on a
population tree.  However, it can be difficult to determine the number of
migration edges to include.  Previously, it was customary to stop adding
migration edges when 99.8% of variation in the data was explained, but
@code{OptM} automates this process using an ad hoc statistic based on the
second-order rate of change in the log likelihood. @code{OptM} also has added
functionality for various threshold modeling to compare with the ad hoc
statistic.")
    (license license:gpl2+)))

(define-public r-optistock
  (package
    (name "r-optistock")
    (version "0.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optistock" version))
       (sha256
        (base32 "1wl637hgdhiyk56xv39bb8m4v6nnlqyy6vgkradf90k084m9q52p"))))
    (properties `((upstream-name . "optistock")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=optistock")
    (synopsis "Determine Optimum Stocking Times Used in Fishery Enhancements")
    (description
     "This package provides a collection of functions that aid in calculating the
optimum time to stock hatchery reared fish into a body of water given the
growth, mortality and cost of raising a particular number of individuals to a
certain length.")
    (license license:expat)))

(define-public r-optisolve
  (package
    (name "r-optisolve")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optiSolve" version))
       (sha256
        (base32 "0mhl5gdz3y3cs3p6v7z4n50na3sqj0w739gixcf4qgb1ppx0h1xa"))))
    (properties `((upstream-name . "optiSolve")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-shapes
                             r-rcpp
                             r-plyr
                             r-nloptr
                             r-matrix
                             r-mass
                             r-cccp
                             r-alabama))
    (home-page "https://cran.r-project.org/package=optiSolve")
    (synopsis "Linear, Quadratic, and Rational Optimization")
    (description
     "Solver for linear, quadratic, and rational programs with linear, quadratic, and
rational constraints.  A unified interface to different R packages is provided.
Optimization problems are transformed into equivalent formulations and solved by
the respective package.  For example, quadratic programming problems with
linear, quadratic and rational constraints can be solved by augmented Lagrangian
minimization using package alabama', or by sequential quadratic programming
using solver slsqp'.  Alternatively, they can be reformulated as optimization
problems with second order cone constraints and solved with package cccp'.")
    (license license:gpl2)))

(define-public r-optisel
  (package
    (name "r-optisel")
    (version "2.0.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optiSel" version))
       (sha256
        (base32 "0n1snxh05dsrgcgzl5xm65ghixja8yb1kbkxws9i0i1zy7qm6kzp"))))
    (properties `((upstream-name . "optiSel")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-reshape2
                             r-rcpparmadillo
                             r-rcpp
                             r-quadprog
                             r-purrr
                             r-pspline
                             r-plyr
                             r-pedigree
                             r-optisolve
                             r-nadiv
                             r-matrix
                             r-mass
                             r-magic
                             r-kinship2
                             r-foreach
                             r-ecosolver
                             r-doparallel
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=optiSel")
    (synopsis "Optimum Contribution Selection and Population Genetics")
    (description
     "This package provides a framework for the optimization of breeding programs via
optimum contribution selection and mate allocation.  An easy to use set of
function for computation of optimum contributions of selection candidates, and
of the population genetic parameters to be optimized.  These parameters can be
estimated using pedigree or genotype information, and include kinships, kinships
at native haplotype segments, and breed composition of crossbred individuals.
They are suitable for managing genetic diversity, removing introgressed genetic
material, and accelerating genetic gain.  Additionally, functions are provided
for computing genetic contributions from ancestors, inbreeding coefficients, the
native effective size, the native genome equivalent, pedigree completeness, and
for preparing and plotting pedigrees.  The methods are described in:\\n Wellmann,
R., and Pfeiffer, I. (2009) <doi:10.1017/S0016672309000202>.\\n Wellmann, R., and
Bennewitz, J. (2011) <doi:10.2527/jas.2010-3709>.\\n Wellmann, R., Hartwig, S.,
Bennewitz, J. (2012) <doi:10.1186/1297-9686-44-34>.\\n de Cara, M. A. R.,
Villanueva, B., Toro, M. A., Fernandez, J. (2013) <doi:10.1111/mec.12560>.\\n
Wellmann, R., Bennewitz, J., Meuwissen, T.H.E. (2014)
<doi:10.1017/S0016672314000196>.\\n Wellmann, R. (2019)
<doi:10.1186/s12859-018-2450-5>.")
    (license license:gpl2)))

(define-public r-optiscale
  (package
    (name "r-optiscale")
    (version "1.2.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optiscale" version))
       (sha256
        (base32 "06qx6fha6vz46bchqswkdv3blxkpv2zg21kiwnb0rzz66srfkljn"))))
    (properties `((upstream-name . "optiscale")))
    (build-system r-build-system)
    (propagated-inputs (list r-lattice))
    (home-page "https://cran.r-project.org/package=optiscale")
    (synopsis "Optimal Scaling")
    (description
     "Optimal scaling of a data vector, relative to a set of targets, is obtained
through a least-squares transformation subject to appropriate measurement
constraints.  The targets are usually predicted values from a statistical model.
 If the data are nominal level, then the transformation must be
identity-preserving.  If the data are ordinal level, then the transformation
must be monotonic.  If the data are discrete, then tied data values must remain
tied in the optimal transformation.  If the data are continuous, then tied data
values can be untied in the optimal transformation.")
    (license license:gpl2)))

(define-public r-optionstrat
  (package
    (name "r-optionstrat")
    (version "1.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optionstrat" version))
       (sha256
        (base32 "0vidaf888zdls5yxy7637fqg6r39l3rxw9bhn16s4xmag7kawljv"))))
    (properties `((upstream-name . "optionstrat")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=optionstrat")
    (synopsis
     "Utilizes the Black-Scholes Option Pricing Model to Perform Strategic Option Analysis and Plot Option Strategies")
    (description
     "Utilizes the Black-Scholes-Merton option pricing model to calculate key option
analytics and perform graphical analysis of various option strategies.  Provides
functions to calculate the option premium and option greeks of European-style
options.")
    (license license:gpl3)))

(define-public r-optionpricing
  (package
    (name "r-optionpricing")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OptionPricing" version))
       (sha256
        (base32 "0c4pq9qzbnqsfgdqq29vnkxjcb5six4xfj2djv05zw8qnyvhaljg"))))
    (properties `((upstream-name . "OptionPricing")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=OptionPricing")
    (synopsis "Option Pricing with Efficient Simulation Algorithms")
    (description
     "Efficient Monte Carlo Algorithms for the price and the sensitivities of Asian
and European Options under Geometric Brownian Motion.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-optional
  (package
    (name "r-optional")
    (version "2.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optional" version))
       (sha256
        (base32 "1q7k9rsa7m3ag7mwx88101ksy0c01gk0xl0425jfkwm0d4g5pyy0"))))
    (properties `((upstream-name . "optional")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=optional")
    (synopsis "Optional Types and Pattern Matching")
    (description
     "Introduces optional types with some() and none, as well as match_with() from
functional languages.")
    (license (license:fsdg-compatible "BSL"))))

(define-public r-optimus
  (package
    (name "r-optimus")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optimus" version))
       (sha256
        (base32 "01njyjfrm6kjwx2qq41c0hsgxzydnrmr3538cpbfdn5i0z5blgyx"))))
    (properties `((upstream-name . "optimus")))
    (build-system r-build-system)
    (propagated-inputs (list r-ordinal r-mvabund))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mitchest/optimus/")
    (synopsis "Model Based Diagnostics for Multivariate Cluster Analysis")
    (description
     "Assessment and diagnostics for comparing competing clustering solutions, using
predictive models.  The main intended use is for comparing
clustering/classification solutions of ecological data (e.g. presence/absence,
counts, ordinal scores) to 1) find an optimal partitioning solution, 2) identify
characteristic species and 3) refine a classification by merging clusters that
increase predictive performance.  However, in a more general sense, this package
can do the above for any set of clustering solutions for i observations of j
variables.")
    (license license:gpl3)))

(define-public r-optimstrat
  (package
    (name "r-optimstrat")
    (version "2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optimStrat" version))
       (sha256
        (base32 "0p52ly7yfz9jjlhd5912xdv1j01j1ccm57ygp9nz3rks7fi3b5r5"))))
    (properties `((upstream-name . "optimStrat")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-mvtnorm r-cubature))
    (home-page "https://cran.r-project.org/package=optimStrat")
    (synopsis "Choosing the Sample Strategy")
    (description
     "Intended to assist in the choice of the sampling strategy to implement in a
survey.")
    (license license:gpl2)))

(define-public r-optimsimplex
  (package
    (name "r-optimsimplex")
    (version "1.0-8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optimsimplex" version))
       (sha256
        (base32 "1q5hfbiq265q5im6wg78spaqsfj421hpzh8bz51zmi188h6xwnwr"))))
    (properties `((upstream-name . "optimsimplex")))
    (build-system r-build-system)
    (propagated-inputs (list r-optimbase))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=optimsimplex")
    (synopsis "R Port of the 'Scilab' Optimsimplex Module")
    (description
     "This package provides a building block for optimization algorithms based on a
simplex.  The optimsimplex package may be used in the following optimization
methods: the simplex method of Spendley et al. (1962)
<doi:10.1080/00401706.1962.10490033>, the method of Nelder and Mead (1965)
<doi:10.1093/comjnl/7.4.308>, Box's algorithm for constrained optimization
(1965) <doi:10.1093/comjnl/8.1.42>, the multi-dimensional search by Torczon
(1989) <https://www.cs.wm.edu/~va/research/thesis.pdf>, etc...")
    (license (license:fsdg-compatible "CeCILL-2"))))

(define-public r-optimparallel
  (package
    (name "r-optimparallel")
    (version "1.0-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optimParallel" version))
       (sha256
        (base32 "178ayfaivkbxkghxbg97lx4gl27kxkmgaaw9y8q5206r4cncd6qg"))))
    (properties `((upstream-name . "optimParallel")))
    (build-system r-build-system)
    (native-inputs (list r-r-rsp))
    (home-page "https://github.com/florafauna/optimParallel-R")
    (synopsis "Parallel Version of the L-BFGS-B Optimization Method")
    (description
     "This package provides a parallel version of the L-BFGS-B method of optim().  The
main function of the package is @code{optimParallel}(), which has the same usage
and output as optim().  Using @code{optimParallel}() can significantly reduce
the optimization time.")
    (license license:gpl2+)))

(define-public r-optimos-prime
  (package
    (name "r-optimos-prime")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optimos.prime" version))
       (sha256
        (base32 "1a76gfzpd2s4gq15cd3frndak7wc6q3xqh9sllkk665031fx6z1h"))))
    (properties `((upstream-name . "optimos.prime")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyverse r-plotly r-ggplot2))
    (home-page "https://cran.r-project.org/package=optimos.prime")
    (synopsis
     "Optimos Prime Helps Calculate Autoecological Data for Biological Species")
    (description
     "Calculates autoecological data (optima and tolerance ranges) of a biological
species given an environmental matrix.  The package calculates by weighted
averaging, using the number of occurrences to adjust the tolerance assigned to
each taxon to estimate optima and tolerance range in cases where taxa have
unequal occurrences.  See the detailed methodology by Birks et al. (1990)
<doi:10.1098/rstb.1990.0062>, and a case example by Potapova and Charles (2003)
<doi:10.1046/j.1365-2427.2003.01080.x>.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-optimmodel
  (package
    (name "r-optimmodel")
    (version "2.0-1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OptimModel" version))
       (sha256
        (base32 "1c53jryrvzjhkgjppvf8kx7fvfss2x52v6wx90sfw57710dl9wvx"))))
    (properties `((upstream-name . "OptimModel")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OptimModel")
    (synopsis
     "Perform Nonlinear Regression Using 'optim' as the Optimization Engine")
    (description
     "This package provides a wrapper for optim for nonlinear regression problems; see
Nocedal J and Write S (2006, ISBN: 978-0387-30303-1).  Performs ordinary least
squares (OLS), iterative re-weighted least squares (IRWLS), and maximum
likelihood (MLE).  Also includes the robust outlier detection (ROUT) algorithm;
see Motulsky, H and Brown, R (2006)<doi:10.1186/1471-2105-7-123>.")
    (license license:gpl2)))

(define-public r-optimlanduse
  (package
    (name "r-optimlanduse")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optimLanduse" version))
       (sha256
        (base32 "03y3cw07ya9q15aybjcaiqa2ghs1id2k55crkpf8xh0yn4mylhh4"))))
    (properties `((upstream-name . "optimLanduse")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-lpsolveapi r-future-apply r-future
                             r-dplyr))
    (home-page "https://github.com/Forest-Economics-Goettingen/optimLanduse/")
    (synopsis "Robust Land-Use Optimization")
    (description
     "Robust multi-criteria land-allocation optimization that explicitly accounts for
the uncertainty of the indicators in the objective function.  Solves the problem
of allocating scarce land to various land-use options with regard to multiple,
coequal indicators.  The method aims to find the land allocation that represents
the indicator composition with the best possible trade-off under uncertainty.
@code{optimLanduse} includes the actual optimization procedure as described by
Knoke et al. (2016) <doi:10.1038/ncomms11877> and the post-hoc calculation of
the portfolio performance as presented by Gosling et al. (2020)
<doi:10.1016/j.jenvman.2020.110248>.")
    (license license:expat)))

(define-public r-optimizer
  (package
    (name "r-optimizer")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optimizeR" version))
       (sha256
        (base32 "134828h3ibypam0k0xxmj7pj6pzx084in06rmbcxgc900ibbqgb4"))))
    (properties `((upstream-name . "optimizeR")))
    (build-system r-build-system)
    (propagated-inputs (list r-ucminf
                             r-testfunctions
                             r-r6
                             r-oeli
                             r-lbfgsb3c
                             r-cli
                             r-checkmate))
    (home-page "https://loelschlaeger.de/optimizeR/")
    (synopsis "Unified Framework for Numerical Optimizers")
    (description
     "This package provides a unified object-oriented framework for numerical
optimizers in R. Allows for both minimization and maximization with any
optimizer, optimization over more than one function argument, measuring of
computation time, setting a time limit for long optimization tasks.")
    (license license:gpl3+)))

(define-public r-optimization
  (package
    (name "r-optimization")
    (version "1.0-9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optimization" version))
       (sha256
        (base32 "1pg9a78hhm0h4pfagj13r1dmynv714knhw2dxhzhcvlgk9inpam8"))))
    (properties `((upstream-name . "optimization")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-colorspace))
    (native-inputs (list r-r-rsp))
    (home-page "https://github.com/kaihusmann/optimization")
    (synopsis
     "Flexible Optimization of Complex Loss Functions with State and Parameter Space Constraints")
    (description
     "Flexible optimizer with numerous input specifications for detailed
parameterisation.  Designed for complex loss functions with state and parameter
space constraints.  Visualization tools for validation and analysis of the
convergence are included.")
    (license license:gpl2+)))

(define-public r-optimg
  (package
    (name "r-optimg")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optimg" version))
       (sha256
        (base32 "0fc7d3g5nxjjcbwh6v5m0ryhanw80v250j8m7j2gv4c9ql4g650d"))))
    (properties `((upstream-name . "optimg")))
    (build-system r-build-system)
    (propagated-inputs (list r-ucminf))
    (home-page "https://github.com/vthorrf/optimg")
    (synopsis "General-Purpose Gradient-Based Optimization")
    (description
     "This package provides general purpose tools for helping users to implement
steepest gradient descent methods for function optimization; for details see
Ruder (2016) <@code{arXiv:1609.04747v2>}.  Currently, the Steepest 2-Groups
Gradient Descent and the Adaptive Moment Estimation (Adam) are the methods
implemented.  Other methods will be implemented in the future.")
    (license license:gpl3)))

(define-public r-optimcheck
  (package
    (name "r-optimcheck")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optimCheck" version))
       (sha256
        (base32 "0nxvq6xmcgfdnmlva65swi519vysa1dya14r5vna4ma006229ncy"))))
    (properties `((upstream-name . "optimCheck")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mlysy/optimCheck")
    (synopsis "Graphical and Numerical Checks for Mode-Finding Routines")
    (description
     "This package provides tools for checking that the output of an optimization
algorithm is indeed at a local mode of the objective function.  This is
accomplished graphically by calculating all one-dimensional \"projection plots\"
of the objective function, i.e., varying each input variable one at a time with
all other elements of the potential solution being fixed.  The numerical values
in these plots can be readily extracted for the purpose of automated and
systematic unit-testing of optimization routines.")
    (license license:gpl3)))

(define-public r-optimbase
  (package
    (name "r-optimbase")
    (version "1.0-10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optimbase" version))
       (sha256
        (base32 "0hdzbqr03jwy1vz3q9iw0kvii5p9g1vm4c3hs3jxszcj1rgrfm12"))))
    (properties `((upstream-name . "optimbase")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=optimbase")
    (synopsis "R Port of the 'Scilab' Optimbase Module")
    (description
     "This package provides a set of commands to manage an abstract optimization
method.  The goal is to provide a building block for a large class of
specialized optimization methods.  This package manages: the number of
variables, the minimum and maximum bounds, the number of non linear inequality
constraints, the cost function, the logging system, various termination
criteria, etc...")
    (license (license:fsdg-compatible "CeCILL-2"))))

(define-public r-optimaregion
  (package
    (name "r-optimaregion")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OptimaRegion" version))
       (sha256
        (base32 "01nbisv45amv5pfnl0hmbc751qjkjvw8xsva50q8ypm02p2jw07f"))))
    (properties `((upstream-name . "OptimaRegion")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-spam
                             r-rsm
                             r-rdsdp
                             r-rdpack
                             r-nloptr
                             r-magrittr
                             r-fields
                             r-depthproc
                             r-boot))
    (home-page "https://cran.r-project.org/package=OptimaRegion")
    (synopsis "Confidence Regions for Optima of Response Surfaces")
    (description
     "Computes confidence regions on the location of response surface optima.
Response surface models can be up to cubic polynomial models in up to 5
controllable factors, or Thin Plate Spline models in 2 controllable factors.")
    (license license:gpl3)))

(define-public r-optimaltiming
  (package
    (name "r-optimaltiming")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OptimalTiming" version))
       (sha256
        (base32 "1mchb7wdk1v56la30ivi40aq6zma64lrdb94d64d0s7x67m8315w"))))
    (properties `((upstream-name . "OptimalTiming")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-mstate))
    (home-page "https://cran.r-project.org/package=OptimalTiming")
    (synopsis "Optimal Timing Identification")
    (description
     "Identify the optimal timing for new treatment initiation during multiple state
disease transition, including multistate model fitting, simulation of mean
residual lifetime for a given transition state, and estimation of confidence
interval.  The method is referred to de Wreede, L., Fiocco, M., & Putter, H.
(2011) <doi:10.18637/jss.v038.i07>.")
    (license license:gpl2+)))

(define-public r-optimalthreshold
  (package
    (name "r-optimalthreshold")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optimalThreshold" version))
       (sha256
        (base32 "1m39q36p7i7z31b90awriq5jf9rfybyw5lj3m1w33v2ssipkzp1n"))))
    (properties `((upstream-name . "optimalThreshold")))
    (build-system r-build-system)
    (propagated-inputs (list r-rjags r-mgcv r-hdinterval r-coda r-ars))
    (home-page "https://cran.r-project.org/package=optimalThreshold")
    (synopsis "Bayesian Methods for Optimal Threshold Estimation")
    (description
     "This package provides functions to estimate the optimal threshold of diagnostic
markers or treatment selection markers.  The optimal threshold is the marker
value that maximizes the utility of the marker based-strategy (for diagnostic or
treatment selection) in a given population.  The utility function depends on the
type of marker (diagnostic or treatment selection), but always takes into
account the preferences of the patients or the physician in the decision
process.  For estimating the optimal threshold, ones must specify the
distributions of the marker in different groups (defined according to the type
of marker, diagnostic or treatment selection) and provides data to estimate the
parameters of these distributions.  Ones must also provide some features of the
target populations (disease prevalence or treatment efficacies) as well as the
preferences of patients or physicians.  The functions rely on Bayesian inference
which helps producing several indicators derived from the optimal threshold.
See Blangero, Y, Rabilloud, M, Ecochard, R, and Subtil, F (2019)
<doi:10.1177/0962280218821394> for the original article that describes the
estimation method for treatment selection markers and Subtil, F, and Rabilloud,
M (2019) <doi:10.1002/bimj.200900242> for diagnostic markers.")
    (license license:gpl2+)))

(define-public r-optimalsurrogate
  (package
    (name "r-optimalsurrogate")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OptimalSurrogate" version))
       (sha256
        (base32 "1kw87h6im3s1xzj0va22w0av67s0qz59vmf36lkh2mi5x1mi7gws"))))
    (properties `((upstream-name . "OptimalSurrogate")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=OptimalSurrogate")
    (synopsis "Model Free Approach to Quantifying Surrogacy")
    (description
     "Identifies an optimal transformation of a surrogate marker such that the
proportion of treatment effect explained can be inferred based on the
transformation of the surrogate and nonparametrically estimates two model-free
quantities of this proportion.  Details are described in Wang et al (2020)
<doi:10.1093/biomet/asz065>.")
    (license license:gpl3)))

(define-public r-optimalrerandexpdesigns
  (package
    (name "r-optimalrerandexpdesigns")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OptimalRerandExpDesigns" version))
       (sha256
        (base32 "033qwzglpzjk302dr19yak34j2k19k6vihd3vlj9c8xsiikmrfmj"))))
    (properties `((upstream-name . "OptimalRerandExpDesigns")))
    (build-system r-build-system)
    (propagated-inputs (list r-momentchi2 r-greedyexperimentaldesign r-ggplot2))
    (home-page "https://github.com/kapelner/OptimalRerandExpDesigns")
    (synopsis "Optimal Rerandomization Experimental Designs")
    (description
     "This is a tool to find the optimal rerandomization threshold in non-sequential
experiments.  We offer three procedures based on assumptions made on the
residuals distribution: (1) normality assumed (2) excess kurtosis assumed (3)
entire distribution assumed.  Illustrations are included.  Also included is a
routine to unbiasedly estimate Frobenius norms of variance-covariance matrices.
Details of the method can be found in \"Optimal Rerandomization via a Criterion
that Provides Insurance Against Failed Experiments\" Adam Kapelner, Abba M.
Krieger, Michael Sklar and David Azriel (2020) <@code{arXiv:1905.03337>}.")
    (license license:gpl3)))

(define-public r-optimall
  (package
    (name "r-optimall")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optimall" version))
       (sha256
        (base32 "0pc7bswfaz0fc9mjr8m29xvm9a1015fb80sr7si65zkkmjhxwldz"))))
    (properties `((upstream-name . "optimall")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-rlang r-magrittr r-glue r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/yangjasp/optimall")
    (synopsis "Allocate Samples Among Strata")
    (description
     "This package provides functions for the design process of survey sampling, with
specific tools for multi-wave and multi-phase designs.  Perform optimum
allocation using Neyman (1934) <doi:10.2307/2342192> or Wright (2012)
<doi:10.1080/00031305.2012.733679> allocation, split strata based on quantiles
or values of known variables, randomly select samples from strata, allocate
sampling waves iteratively, and organize a complex survey design.  Also includes
a Shiny application for observing the effects of different strata splits.")
    (license license:gpl3)))

(define-public r-optimalgoldstandarddesigns
  (package
    (name "r-optimalgoldstandarddesigns")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OptimalGoldstandardDesigns" version))
       (sha256
        (base32 "1rw3syj5wb1v8ryqc9vkchi62pf02460f5i5zapq2azgfg99l66y"))))
    (properties `((upstream-name . "OptimalGoldstandardDesigns")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-rdpack
                             r-nloptr
                             r-mvtnorm
                             r-dplyr
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/jan-imbi/OptimalGoldstandardDesigns")
    (synopsis
     "Design Parameter Optimization for Gold-Standard Non-Inferiority Trials")
    (description
     "This package provides methods to calculate optimal design parameters for one-
and two-stage three-arm group-sequential gold-standard non-inferiority trial
designs with or without binding or nonbinding futility boundaries, as described
in Meis et al. (2023) <doi:10.1002/sim.9630>.")
    (license license:gpl3+)))

(define-public r-optimaldesign
  (package
    (name "r-optimaldesign")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OptimalDesign" version))
       (sha256
        (base32 "02vxxb25q7fl73y7zq0a89ra0s88wji4mrql7p88014p073lj2as"))))
    (properties `((upstream-name . "OptimalDesign")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgl
                             r-quadprog
                             r-plyr
                             r-matrixstats
                             r-matrixcalc
                             r-matrix
                             r-lpsolve))
    (home-page "https://cran.r-project.org/package=OptimalDesign")
    (synopsis "Toolbox for Computing Efficient Designs of Experiments")
    (description
     "Algorithms for D-, A-, I-, and c-optimal designs.  Some of the functions in this
package require the gurobi software and its accompanying R package.  For their
installation, please follow the instructions at <https://www.gurobi.com> and the
file gurobi_inst.txt, respectively.")
    (license license:gpl3)))

(define-public r-optimalcutpoints
  (package
    (name "r-optimalcutpoints")
    (version "1.1-5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OptimalCutpoints" version))
       (sha256
        (base32 "07lgh3maxvz8vmw3zd02bfy7yp4jn0krflnqpp5bax3zhy6kmmbi"))))
    (properties `((upstream-name . "OptimalCutpoints")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=OptimalCutpoints")
    (synopsis "Computing Optimal Cutpoints in Diagnostic Tests")
    (description
     "Computes optimal cutpoints for diagnostic tests or continuous markers.  Various
approaches for selecting optimal cutoffs have been implemented, including
methods based on cost-benefit analysis and diagnostic test accuracy measures
(Sensitivity/Specificity, Predictive Values and Diagnostic Likelihood Ratios).
Numerical and graphical output for all methods is easily obtained.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-optim-functions
  (package
    (name "r-optim-functions")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optim.functions" version))
       (sha256
        (base32 "1la3v8yd9cdichp3mka4x86hr9lynh6qfg7h9ab6cwijw6kzkn6g"))))
    (properties `((upstream-name . "optim.functions")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-randtoolbox r-lhs))
    (home-page "https://cran.r-project.org/package=optim.functions")
    (synopsis "Standard Benchmark Optimization Functions")
    (description
     "This package provides a set of standard benchmark optimization functions for R
and a common interface to sample them.")
    (license license:expat)))

(define-public r-optigrab
  (package
    (name "r-optigrab")
    (version "0.9.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optigrab" version))
       (sha256
        (base32 "1c3q4kx8rkgpjsy0hy2w2dd9kv51avnw1ab82hzmjgngfnvaig0n"))))
    (properties `((upstream-name . "optigrab")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringi r-magrittr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/decisionpatterns/optigrab")
    (synopsis "Command-Line Parsing for an R World")
    (description
     "Parse options from the command-line using a simple, clean syntax.  It requires
little or no specification and supports short and long options, GNU-, Java- or
Microsoft- style syntaxes, verb commands and more.")
    (license (list license:gpl3+
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-optifunset
  (package
    (name "r-optifunset")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optifunset" version))
       (sha256
        (base32 "18pvdl04ln1i0w30ljdb3k86j27zg2nvrn3ws54c1g6zg9haqhbg"))))
    (properties `((upstream-name . "optifunset")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=optifunset")
    (synopsis "Set Options if Unset")
    (description
     "This package provides a single function options.ifunset(...) is contained
herewith, which allows the user to set a global option ONLY if it is not already
set.  By this token, for package maintainers this function can be used in
preference to the standard options(...) function, making provision for THEIR end
user to place options(...) directives within their .Rprofile file, which will
not be overridden at the point when a package is loaded.")
    (license license:gpl2)))

(define-public r-opticut
  (package
    (name "r-opticut")
    (version "0.1-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "opticut" version))
       (sha256
        (base32 "1knjxfz52gisnkz62m885zf4gn73dnkhc0q2wfvmhj02vqq0sfhf"))))
    (properties `((upstream-name . "opticut")))
    (build-system r-build-system)
    (propagated-inputs (list r-resourceselection
                             r-pscl
                             r-pbapply
                             r-mefa4
                             r-mass
                             r-betareg))
    (home-page "https://github.com/psolymos/opticut")
    (synopsis
     "Likelihood Based Optimal Partitioning and Indicator Species Analysis")
    (description
     "Likelihood based optimal partitioning and indicator species analysis.  Finding
the best binary partition for each species based on model selection, with the
possibility to take into account modifying/confounding variables as described in
Kemencei et al. (2014) <doi:10.1556/@code{ComEc.15.2014.2.6>}.  The package
implements binary and multi-level response models, various measures of
uncertainty, Lorenz-curve based thresholding, with native support for parallel
computations.")
    (license license:gpl2)))

(define-public r-opticskxi
  (package
    (name "r-opticskxi")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "opticskxi" version))
       (sha256
        (base32 "1vdz5sgjgyh2nj034w87d2yxcbbg97f1b0vijlwzwjkrfz5knfhl"))))
    (properties `((upstream-name . "opticskxi")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=opticskxi")
    (synopsis "OPTICS K-Xi Density-Based Clustering")
    (description
     "This package provides a novel density-based cluster extraction method, OPTICS
k-Xi, and a framework to compare k-Xi models using distance-based metrics to
investigate datasets with unknown number of clusters.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-optical
  (package
    (name "r-optical")
    (version "1.7.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optical" version))
       (sha256
        (base32 "1g400s4xbf9c8ss02qhm6q31sv7mrki4a9x1fdjjsyrgmclv9q2s"))))
    (properties `((upstream-name . "optical")))
    (build-system r-build-system)
    (home-page "https://scenic555.github.io/optical/")
    (synopsis "Optimal Item Calibration")
    (description
     "The restricted optimal design method is implemented to optimally allocate a set
of items that require calibration to a group of examinees.  The optimization
process is based on the method described in detail by Ul Hassan and Miller in
their works published in (2019) <doi:10.1177/0146621618824854> and (2021)
<doi:10.1016/j.csda.2021.107177>.  To use the method, preliminary item
characteristics must be provided as input.  These characteristics can either be
expert guesses or based on previous calibration with a small number of
examinees.  The item characteristics should be described in the form of
parameters for an Item Response Theory (IRT) model.  These models can include
the Rasch model, the 2-parameter logistic model, the 3-parameter logistic model,
or a mixture of these models.  The output consists of a set of rules for each
item that determine which examinees should be assigned to each item.  The
efficiency or gain achieved through the optimal design is quantified by
comparing it to a random allocation.  This comparison allows for an assessment
of how much improvement or advantage is gained by using the optimal design
approach.  This work was supported by the Swedish Research Council
(VetenskapsrÃ¥det) Grant 2019-02706.")
    (license license:gpl3+)))

(define-public r-optic
  (package
    (name "r-optic")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optic" version))
       (sha256
        (base32 "166ngas1zp1ln951n26kmyfj9jcpi2fm2g2yxs9vs4as6fl1yf2n"))))
    (properties `((upstream-name . "optic")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-sandwich
                             r-rlang
                             r-r6
                             r-purrr
                             r-mass
                             r-magrittr
                             r-lmtest
                             r-future-apply
                             r-dplyr
                             r-did))
    (native-inputs (list r-knitr))
    (home-page "https://randcorporation.github.io/optic/")
    (synopsis "Simulation Tool for Causal Inference Using Longitudinal Data")
    (description
     "This package implements a simulation study to assess the strengths and
weaknesses of causal inference methods for estimating policy effects using panel
data.  See Griffin et al. (2021) <doi:10.1007/s10742-022-00284-w> and Griffin et
al. (2022) <doi:10.1186/s12874-021-01471-y> for a description of our methods.")
    (license license:gpl3)))

(define-public r-optholdoutsize
  (package
    (name "r-optholdoutsize")
    (version "0.1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OptHoldoutSize" version))
       (sha256
        (base32 "0ab0vvbg1nmpbbhq5a5nkwv7ap0fq4542l5da7g8qlwc23h6sfs5"))))
    (properties `((upstream-name . "OptHoldoutSize")))
    (build-system r-build-system)
    (propagated-inputs (list r-ranger r-mvtnorm r-mnormt r-mle-tools
                             r-matrixstats))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OptHoldoutSize")
    (synopsis
     "Estimation of Optimal Size for a Holdout Set for Updating a Predictive Score")
    (description
     "Predictive scores must be updated with care, because actions taken on the basis
of existing risk scores causes bias in risk estimates from the updated score.  A
holdout set is a straightforward way to manage this problem: a proportion of the
population is held-out from computation of the previous risk score.  This
package provides tools to estimate a size for this holdout set and associated
errors.  Comprehensive vignettes are included.  Please see: Haidar-Wehbe S,
Emerson SR, Aslett LJM, Liley J (2022) <@code{arXiv:2202.06374>} for details of
methods.")
    (license license:gpl3+)))

(define-public r-opthedging
  (package
    (name "r-opthedging")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OptHedging" version))
       (sha256
        (base32 "0g7qaf5abvbcqv2h1dciwn3gwpz084ryqjjk0yabdm4ym0y38ddm"))))
    (properties `((upstream-name . "OptHedging")))
    (build-system r-build-system)
    (home-page "http://www.r-project.org")
    (synopsis
     "Estimation of value and hedging strategy of call and put options")
    (description
     "Estimation of value and hedging strategy of call and put options, based on
optimal hedging and Monte Carlo method, from Chapter 3 of Statistical Methods
for Financial Engineering', by Bruno Remillard, CRC Press, (2013).")
    (license license:gpl2+)))

(define-public r-optgs
  (package
    (name "r-optgs")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OptGS" version))
       (sha256
        (base32 "0rpnn38w3a15agv0hkr77w6jpdb75ahnxq487vy35yxv9mvh75nn"))))
    (properties `((upstream-name . "OptGS")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=OptGS")
    (synopsis "Near-Optimal Group-Sequential Designs for Continuous Outcomes")
    (description
     "Optimal group-sequential designs minimise some function of the expected and
maximum sample size whilst controlling the type I error rate and power at a
specified level. @code{OptGS} provides functions to quickly search for
near-optimal group-sequential designs for normally distributed outcomes.  The
methods used are described in Wason, JMS (2015) <doi:10.18637/jss.v066.i02>.")
    (license license:gpl2)))

(define-public r-optextras
  (package
    (name "r-optextras")
    (version "2019-12.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optextras" version))
       (sha256
        (base32 "1sqkid6h13h8i8wzri26s828ycwlxlwpwxd85r8bw9h8hs1n602r"))))
    (properties `((upstream-name . "optextras")))
    (build-system r-build-system)
    (propagated-inputs (list r-numderiv))
    (home-page "https://cran.r-project.org/package=optextras")
    (synopsis "Tools to Support Optimization Possibly with Bounds and Masks")
    (description
     "This package provides tools to assist in safely applying user generated
objective and derivative function to optimization programs.  These are primarily
function minimization methods with at most bounds and masks on the parameters.
Provides a way to check the basic computation of objective functions that the
user provides, along with proposed gradient and Hessian functions, as well as to
wrap such functions to avoid failures when inadmissible parameters are provided.
 Check bounds and masks.  Check scaling or optimality conditions.  Perform an
axial search to seek lower points on the objective function surface.  Includes
forward, central and backward gradient approximation codes.")
    (license license:gpl2)))

(define-public r-optedr
  (package
    (name "r-optedr")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optedr" version))
       (sha256
        (base32 "17r0axfh7yjv5xj9060vi5vysnmi38pz5dsvm0fazfcpzzlxnld7"))))
    (properties `((upstream-name . "optedr")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny
                             r-rlang
                             r-purrr
                             r-nleqslv
                             r-ggplot2
                             r-dplyr
                             r-crayon
                             r-cli))
    (home-page "https://github.com/kezrael/optedr")
    (synopsis "Calculating Optimal and D-Augmented Designs")
    (description
     "Calculates D-, Ds-, A- and I-optimal designs for non-linear models, via an
implementation of the cocktail algorithm (Yu, 2011,
<doi:10.1007/s11222-010-9183-2>).  Compares designs via their efficiency, and
D-augments any design with a controlled efficiency.  An efficient rounding
function has been provided to transform approximate designs to exact designs.")
    (license license:gpl3)))

(define-public r-optdesignslopeint
  (package
    (name "r-optdesignslopeint")
    (version "1.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optDesignSlopeInt" version))
       (sha256
        (base32 "0kjfhy1ccdxgb2sxa3928m1pqpbvl1rxz0kajqf9yvga451l5ddd"))))
    (properties `((upstream-name . "optDesignSlopeInt")))
    (build-system r-build-system)
    (propagated-inputs (list r-mcmcpack))
    (home-page "https://cran.r-project.org/package=optDesignSlopeInt")
    (synopsis
     "Optimal Designs for Estimating the Slope Divided by the Intercept")
    (description
     "Aids practitioners to optimally design experiments that measure the slope
divided by the intercept and provides confidence intervals for the ratio.")
    (license license:gpl3)))

(define-public r-optcirclust
  (package
    (name "r-optcirclust")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OptCirClust" version))
       (sha256
        (base32 "0g34kn2gmvy9r4ph0vbssc9gl8bcpw6d72b8zpf38iml4zh52b0n"))))
    (properties `((upstream-name . "OptCirClust")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2 r-rdpack r-rcpp r-plotrix
                             r-ckmeans-1d-dp))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OptCirClust")
    (synopsis
     "Circular, Periodic, or Framed Data Clustering: Fast, Optimal, and Reproducible")
    (description
     "Fast, optimal, and reproducible clustering algorithms for circular, periodic, or
framed data.  The algorithms introduced here are based on a core algorithm for
optimal framed clustering the authors have developed (Debnath & Song 2021)
<doi:10.1109/TCBB.2021.3077573>.  The runtime of these algorithms is O(K N log^2
N), where K is the number of clusters and N is the number of circular data
points.  On a desktop computer using a single processor core, millions of data
points can be grouped into a few clusters within seconds.  One can apply the
algorithms to characterize events along circular DNA molecules, circular RNA
molecules, and circular genomes of bacteria, chloroplast, and mitochondria.  One
can also cluster climate data along any given longitude or latitude.  Periodic
data clustering can be formulated as circular clustering.  The algorithms offer
a general high-performance solution to circular, periodic, or framed data
clustering.")
    (license license:lgpl3+)))

(define-public r-optbiomarker
  (package
    (name "r-optbiomarker")
    (version "1.0-28")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optBiomarker" version))
       (sha256
        (base32 "10i9ir0056qxyiayg10v6v25m1b94m1wd7c8ssigiqjhjncpddw5"))))
    (properties `((upstream-name . "optBiomarker")))
    (build-system r-build-system)
    (propagated-inputs (list r-rpanel
                             r-rgl
                             r-randomforest
                             r-msm
                             r-matrix
                             r-mass
                             r-ipred
                             r-e1071))
    (home-page "https://cran.r-project.org/package=optBiomarker")
    (synopsis
     "Estimation of Optimal Number of Biomarkers for Two-Group Microarray Based Classifications at a Given Error Tolerance Level for Various Classification Rules")
    (description
     "Estimates optimal number of biomarkers for two-group classification based on
microarray data.")
    (license license:gpl2+)))

(define-public r-optbin
  (package
    (name "r-optbin")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optbin" version))
       (sha256
        (base32 "09pdmbvhwj7g13bqcql70x1c6l1islyasbhxcbqdf1cr7r6ylysz"))))
    (properties `((upstream-name . "optbin")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=optbin")
    (synopsis "Optimal Binning of Data")
    (description
     "Defines thresholds for breaking data into a number of discrete levels,
minimizing the (mean) squared error within all bins.")
    (license license:bsd-3)))

(define-public r-optbdmaeat
  (package
    (name "r-optbdmaeat")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optbdmaeAT" version))
       (sha256
        (base32 "1y1mvcyjihpj1wgjmifhmd10717wr1srp7h87azs4gfypgsiqchn"))))
    (properties `((upstream-name . "optbdmaeAT")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-mass r-igraph))
    (home-page "https://cran.r-project.org/package=optbdmaeAT")
    (synopsis
     "Optimal Block Designs for Two-Colour cDNA Microarray Experiments")
    (description
     "Computes A-, MV-, D- and E-optimal or near-optimal block designs for two-colour
@code{cDNA} microarray experiments using the linear fixed effects and mixed
effects models where the interest is in a comparison of all possible elementary
treatment contrasts.  The algorithms used in this package are based on the
treatment exchange and array exchange algorithms of Debusho, Gemechu and Haines
(2016, unpublished).  The package also provides an optional method of using the
graphical user interface (GUI) R package tcltk to ensure that it is user
friendly.")
    (license license:gpl2)))

(define-public r-optband
  (package
    (name "r-optband")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "optband" version))
       (sha256
        (base32 "0mg6awg1vgnbqrbkf9vnyj5jfbakna0jsclhi0w3v1rh0rsd5jlp"))))
    (properties `((upstream-name . "optband")))
    (build-system r-build-system)
    (propagated-inputs (list r-lambertw))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://github.com/seasamgo/optband")
    (synopsis "'surv' Object Confidence Bands Optimized by Area")
    (description
     "Given a certain coverage level, obtains simultaneous confidence bands for the
survival and cumulative hazard functions such that the area between is
minimized.  Produces an approximate solution based on local time arguments.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-opt5pl
  (package
    (name "r-opt5pl")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Opt5PL" version))
       (sha256
        (base32 "0v3ibfzmkfnkhxylhaqcd3yqygsk7027ga12vb6gj4h4zcccf17f"))))
    (properties `((upstream-name . "Opt5PL")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-matrixcalc))
    (home-page "https://cran.r-project.org/package=Opt5PL")
    (synopsis "Optimal Designs for the 5-Parameter Logistic Model")
    (description
     "Obtain and evaluate various optimal designs for the 3, 4, and 5-parameter
logistic models.  The optimal designs are obtained based on the numerical
algorithm in Hyun, Wong, Yang (2018) <doi:10.18637/jss.v083.i05>.")
    (license license:gpl2)))

(define-public r-oppr
  (package
    (name "r-oppr")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oppr" version))
       (sha256
        (base32 "1kyzrpr09fmx7rhbgwy5d1s8ggl7avcrs4vjb9s6m03w756zbb3a"))))
    (properties `((upstream-name . "oppr")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr
                             r-viridislite
                             r-uuid
                             r-tidytree
                             r-tibble
                             r-rcppprogress
                             r-rcpparmadillo
                             r-rcpp
                             r-proto
                             r-matrix
                             r-magrittr
                             r-lpsolveapi
                             r-ggplot2
                             r-cli
                             r-assertthat
                             r-ape))
    (native-inputs (list r-knitr))
    (home-page "https://prioritizr.github.io/oppr/")
    (synopsis "Optimal Project Prioritization")
    (description
     "This package provides a decision support tool for prioritizing conservation
projects.  Prioritizations can be developed by maximizing expected feature
richness, expected phylogenetic diversity, the number of features that meet
persistence targets, or identifying a set of projects that meet persistence
targets for minimal cost.  Constraints (e.g. lock in specific actions) and
feature weights can also be specified to further customize prioritizations.
After defining a project prioritization problem, solutions can be obtained using
exact algorithms, heuristic algorithms, or random processes.  In particular, it
is recommended to install the Gurobi optimizer (available from
<https://www.gurobi.com>) because it can identify optimal solutions very
quickly.  Finally, methods are provided for comparing different prioritizations
and evaluating their benefits.  For more information, see Hanson et al. (2019)
<doi:10.1111/2041-210X.13264>.")
    (license license:gpl3)))

(define-public r-opportunistic
  (package
    (name "r-opportunistic")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Opportunistic" version))
       (sha256
        (base32 "0kaj11ziij1v65l972x4kbr7vzkx4dwa27ymabiip4dg57a976wr"))))
    (properties `((upstream-name . "Opportunistic")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=Opportunistic")
    (synopsis
     "Routing Distribution, Broadcasts, Transmissions and Receptions in an Opportunistic Network")
    (description
     "Computes the routing distribution, the expectation of the number of broadcasts,
transmissions and receptions considering an Opportunistic transport model.  It
provides theoretical results and also estimated values based on Monte Carlo
simulations.")
    (license license:gpl2+)))

(define-public r-opitools
  (package
    (name "r-opitools")
    (version "1.8.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "opitools" version))
       (sha256
        (base32 "1w5s78dxz03asxc46mn5vy9y21dr6km12ms563cgcaf9g9rw9dqc"))))
    (properties `((upstream-name . "opitools")))
    (build-system r-build-system)
    (propagated-inputs (list r-wordcloud2
                             r-tm
                             r-tidytext
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-purrr
                             r-magrittr
                             r-likert
                             r-ggplot2
                             r-forcats
                             r-dplyr
                             r-cowplot))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/MAnalytics/opitools")
    (synopsis "Analyzing the Opinions in a Big Text Document")
    (description
     "Designed for performing impact analysis of opinions in a digital text document
(DTD).  The package allows a user to assess the extent to which a theme or
subject within a document impacts the overall opinion expressed in the document.
 The package can be applied to a wide range of opinion-based DTD, including
commentaries on social media platforms (such as Facebook', Twitter and
Youtube'), online products reviews, and so on.  The utility of opitools was
originally demonstrated in Adepeju and Jimoh (2021) <doi:10.31235/osf.io/c32qh>
in the assessment of COVID-19 impacts on neighbourhood policing using Twitter
data.  Further examples can be found in the vignette of the package.")
    (license license:gpl3)))

(define-public r-opinar
  (package
    (name "r-opinar")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "opinAr" version))
       (sha256
        (base32 "0xvzjkkqcd058br32cnva8pif0rgpfwk2qbq5q3wyjhfqqv3bwxq"))))
    (properties `((upstream-name . "opinAr")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-sjplot
                             r-rvest
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-lubridate
                             r-janitor
                             r-haven
                             r-gt
                             r-glue
                             r-dplyr
                             r-assertthat))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/PoliticaArgentina/opinAr")
    (synopsis "Argentina's Public Opinion Toolbox")
    (description
     "This package provides a toolbox for working with public opinion data from
Argentina.  It facilitates access to microdata and the calculation of indicators
of the Trust in Government Index (ICG), prepared by the Torcuato Di Tella
University.  Although we will try to document everything possible in English, by
its very nature Spanish will be the main language.  El paquete fue pensado como
una caja de herramientas para el trabajo con datos de opiniÃ³n pÃºblica de
Argentina.  El mismo facilita el acceso a los microdatos y el cÃ¡lculos de
indicadores del Ãndice de Confianza en el Gobierno (ICG), elaborado por la
Universidad Torcuato Di Tella.")
    (license license:expat)))

(define-public r-opi
  (package
    (name "r-opi")
    (version "3.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OPI" version))
       (sha256
        (base32 "19fgfkd8zf8r7cqmkqvhzkv8lwnbg33cvm8kapqp7sb6g4i3qk1x"))))
    (properties `((upstream-name . "OPI")))
    (build-system r-build-system)
    (propagated-inputs (list r-rfast r-openssl r-jsonlite r-abind))
    (home-page "https://opi.lei.org.au/")
    (synopsis "Open Perimetry Interface")
    (description
     "Implementation of the Open Perimetry Interface (OPI) for simulating and
controlling visual field machines using R. The OPI is a standard for interfacing
with visual field testing machines (perimeters) first started as an open source
project with support of Haag-Streit in 2010.  It specifies basic functions that
allow many visual field tests to be constructed.  As of February 2022 it is
fully implemented on the Haag-Streit Octopus 900 and @code{CrewT} @code{ImoVifa}
('Topcon Tempo') with partial implementations on the Centervue Compass, Kowa AP
7000 and Android phones.  It also has a cousin: the R package
@code{visualFields}', which has tools for analysing and manipulating visual
field data.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-opgmmassessment
  (package
    (name "r-opgmmassessment")
    (version "0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "opGMMassessment" version))
       (sha256
        (base32 "0qnxq9i0spygz2lmjb23y94r9cgvkkariv0v8llqdb6l89bhfdqm"))))
    (properties `((upstream-name . "opGMMassessment")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-nbclust
                             r-multimode
                             r-mixtools
                             r-mixak
                             r-mclust
                             r-ggplot2
                             r-foreach
                             r-dplyr
                             r-doparallel
                             r-distributionoptimization
                             r-datavisualizations
                             r-clusterr
                             r-cluster
                             r-catools
                             r-adaptgauss))
    (home-page "https://cran.r-project.org/package=opGMMassessment")
    (synopsis "Optimized Automated Gaussian Mixture Assessment")
    (description
     "Necessary functions for optimized automated evaluation of the number and
parameters of Gaussian mixtures in one-dimensional data.  Various methods are
available for parameter estimation and for determining the number of modes in
the mixture.  A detailed description of the methods ca ben found in Lotsch, J.,
Malkusch, S. and A. Ultsch. (2022) <doi:10.1016/j.imu.2022.101113>.")
    (license license:gpl3)))

(define-public r-operators
  (package
    (name "r-operators")
    (version "0.1-8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "operators" version))
       (sha256
        (base32 "0zgcv2q46qyqv4dhbd33s4044zjw38w8dqfpzs0c1lxjpkil3dnx"))))
    (properties `((upstream-name . "operators")))
    (build-system r-build-system)
    (home-page "https://github.com/romainfrancois/operators")
    (synopsis "Additional Binary Operators")
    (description
     "This package provides a set of binary operators for common tasks such as regex
manipulation.")
    (license license:expat)))

(define-public r-opera
  (package
    (name "r-opera")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "opera" version))
       (sha256
        (base32 "09gh0c74y3n25f9p1rya8ybql5mfaqkcnr8i8wwwzfm67vqdfrnh"))))
    (properties `((upstream-name . "opera")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack
                             r-rcppeigen
                             r-rcpp
                             r-ramcharts
                             r-piper
                             r-htmlwidgets
                             r-htmltools
                             r-alabama))
    (native-inputs (list r-knitr))
    (home-page "http://pierre.gaillard.me/opera.html")
    (synopsis "Online Prediction by Expert Aggregation")
    (description
     "Misc methods to form online predictions, for regression-oriented time-series, by
combining a finite set of forecasts provided by the user.  See Cesa-Bianchi and
Lugosi (2006) <doi:10.1017/CBO9780511546921> for an overview.")
    (license license:lgpl2.0+)))

(define-public r-openxlsx2
  (package
    (name "r-openxlsx2")
    (version "1.10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openxlsx2" version))
       (sha256
        (base32 "0wras02gv7yxkjb75clxbf7wpn2vrnvwhk57birn79cz4ix9drhx"))))
    (properties `((upstream-name . "openxlsx2")))
    (build-system r-build-system)
    (propagated-inputs (list r-zip r-stringi r-rcpp r-r6 r-magrittr))
    (native-inputs (list r-knitr))
    (home-page "https://janmarvin.github.io/openxlsx2/")
    (synopsis "Read, Write and Edit 'xlsx' Files")
    (description
     "Simplifies the creation of xlsx files by providing a high level interface to
writing, styling and editing worksheets.")
    (license license:expat)))

(define-public r-openva
  (package
    (name "r-openva")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openVA" version))
       (sha256
        (base32 "0ywf9hh4liz992ym1xdqpk4pnywy9azasyvqdy3ih8idmj3y5h0d"))))
    (properties `((upstream-name . "openVA")))
    (build-system r-build-system)
    (propagated-inputs (list r-tariff
                             r-interva5
                             r-interva4
                             r-insilicova
                             r-ggplot2
                             r-crayon
                             r-cli))
    (native-inputs (list r-r-rsp r-knitr))
    (home-page "https://github.com/verbal-autopsy-software/openVA")
    (synopsis "Automated Method for Verbal Autopsy")
    (description
     "This package implements multiple existing open-source algorithms for coding
cause of death from verbal autopsies.  The methods implemented include
@code{InterVA4} by Byass et al (2012) <doi:10.3402/gha.v5i0.19281>,
@code{InterVA5} by Byass at al (2019) <doi:10.1186/s12916-019-1333-6>,
@code{InSilicoVA} by @code{McCormick} et al (2016)
<doi:10.1080/01621459.2016.1152191>, NBC by Miasnikof et al (2015)
<doi:10.1186/s12916-015-0521-2>, and a replication of Tariff method by James et
al (2011) <doi:10.1186/1478-7954-9-31> and Serina, et al. (2015)
<doi:10.1186/s12916-015-0527-9>.  It also provides tools for data manipulation
tasks commonly used in Verbal Autopsy analysis and implements easy graphical
visualization of individual and population level statistics.  The NBC method is
implemented by the nbc4va package that can be installed from
<https://github.com/rrwen/nbc4va>.  Note that this package was not developed by
authors affiliated with the Institute for Health Metrics and Evaluation and thus
unintentional discrepancies may exist in the implementation of the Tariff
method.")
    (license license:gpl2)))

(define-public r-opentripplanner
  (package
    (name "r-opentripplanner")
    (version "0.5.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "opentripplanner" version))
       (sha256
        (base32 "0h0dq72gfiyhnl9j8pdr295a93xcd59mqag4ca5hnvq8v93hn0cc"))))
    (properties `((upstream-name . "opentripplanner")))
    (build-system r-build-system)
    (propagated-inputs (list r-sfheaders
                             r-sf
                             r-rjson
                             r-rcppsimdjson
                             r-purrr
                             r-progressr
                             r-googlepolylines
                             r-geodist
                             r-data-table
                             r-curl
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/ropensci/opentripplanner")
    (synopsis "Setup and connect to 'OpenTripPlanner'")
    (description
     "Setup and connect to @code{OpenTripPlanner} (OTP)
<http://www.opentripplanner.org/>.  OTP is an open source platform for
multi-modal and multi-agency journey planning written in Java'.  The package
allows you to manage a local version or connect to remote OTP server to find
walking, cycling, driving, or transit routes.  This package has been
peer-reviewed by @code{rOpenSci} (v.  0.2.0.0).")
    (license license:gpl3)))

(define-public r-openstreetmap
  (package
    (name "r-openstreetmap")
    (version "0.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OpenStreetMap" version))
       (sha256
        (base32 "0iq3y3331rjppc8nfx9krrrfybyn1spwfp15hf3vz8mnmcg86dkf"))))
    (properties `((upstream-name . "OpenStreetMap")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (propagated-inputs (list r-sp r-rjava r-raster r-ggplot2))
    (home-page "https://cran.r-project.org/package=OpenStreetMap")
    (synopsis "Access to Open Street Map Raster Images")
    (description
     "Accesses high resolution raster maps using the @code{OpenStreetMap} protocol.
Dozens of road, satellite, and topographic map servers are directly supported,
including Apple, Mapnik, Bing, and stamen.  Additionally raster maps may be
constructed using custom tile servers.  Maps can be plotted using either base
graphics, or ggplot2.  This package is not affiliated with the
@code{OpenStreetMap.org} mapping project.")
    (license (list license:gpl2
                   (license:fsdg-compatible "file LICENCE")))))

(define-public r-openspecy
  (package
    (name "r-openspecy")
    (version "1.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OpenSpecy" version))
       (sha256
        (base32 "1vg3z7rqwlx4dfab8ka8a4mvpvrdp2mmh86xxlhiyqcgabycm6ry"))))
    (properties `((upstream-name . "OpenSpecy")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-signal
                             r-shiny
                             r-plotly
                             r-mmand
                             r-jsonlite
                             r-jpeg
                             r-hyperspec
                             r-glmnet
                             r-digest
                             r-data-table
                             r-catools))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/wincowgerDEV/OpenSpecy-package/")
    (synopsis "Analyze, Process, Identify, and Share Raman and (FT)IR Spectra")
    (description
     "Raman and (FT)IR spectral analysis tool for plastic particles and other
environmental samples (Cowger et al.  2021, <doi:10.1021/acs.analchem.1c00123>).
 With read_any(), Open Specy provides a single function for reading individual,
batch, or map spectral data files like .asp, .csv, .jdx, .spc, .spa, .0, and
.zip.  process_spec() simplifies processing spectra, including smoothing,
baseline correction, range restriction and flattening, intensity conversions,
wavenumber alignment, and min-max normalization.  Spectra can be identified in
batch using an onboard reference library (Cowger et al.  2020,
<doi:10.1177/0003702820929064>) using match_spec().  A Shiny app is available
via run_app() or online at <https://openanalysis.org/openspecy/>.")
    (license (license:fsdg-compatible "CC BY 4.0"))))

(define-public r-openskies
  (package
    (name "r-openskies")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openSkies" version))
       (sha256
        (base32 "0ky11gpgnf2afv6kzhwbzwzrmril99ixxxzzmav3h9hzcig3igyj"))))
    (properties `((upstream-name . "openSkies")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-ssh
                             r-rpresto
                             r-r6
                             r-magick
                             r-httr
                             r-ggplot2
                             r-ggmap
                             r-dbscan
                             r-dbi
                             r-cluster))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=openSkies")
    (synopsis "Retrieval, Analysis and Visualization of Air Traffic Data")
    (description
     "This package provides functionalities and data structures to retrieve, analyze
and visualize aviation data.  It includes a client interface to the
@code{OpenSky} API <https://opensky-network.org>.  It allows retrieval of flight
information, as well as aircraft state vectors.")
    (license (license:fsdg-compatible "CC BY-NC 4.0"))))

(define-public r-openscoring
  (package
    (name "r-openscoring")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openscoring" version))
       (sha256
        (base32 "0y7yfqk0bqj03fvzni8dwvv0dhis1dp3h0gzbnfky9kmw43iinjv"))))
    (properties `((upstream-name . "openscoring")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-rlang
                             r-purrr
                             r-lifecycle
                             r-jsonlite
                             r-httr
                             r-glue
                             r-dplyr
                             r-cli))
    (home-page "https://github.com/jakub-jedrusiak/openscoring")
    (synopsis "'Open Scoring' API Client")
    (description
     "Creativity research involves the need to score open-ended problems.  Usually
done by humans, automatic scoring using AI becomes more and more accurate.  This
package provides a simple interface to the Open Scoring API
<https://openscoring.du.edu/docs>, leading creativity scoring technology by
Organiscak et al. (2023) <doi:10.1016/j.tsc.2023.101356>.  With it, you can
score your own data directly from an R script.")
    (license license:expat)))

(define-public r-openrouteservice
  (package
    (name "r-openrouteservice")
    (version "0.5.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openrouteservice" version))
       (sha256
        (base32 "195bd7admszp1x0kyha9bxdqw2913qwj4ax7lxmkbq1ky3pjgnbp"))))
    (properties `((upstream-name . "openrouteservice")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-v8
                             r-leaflet
                             r-keyring
                             r-jsonvalidate
                             r-jsonlite
                             r-httr
                             r-geojsonsf))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/GIScience/openrouteservice-r")
    (synopsis "An 'openrouteservice' API Client")
    (description
     "The client streamlines access to the services provided by
<https://api.openrouteservice.org>.  It allows you to painlessly query for
directions, isochrones, time-distance matrices, geocoding, elevation, points of
interest, and more.")
    (license license:asl2.0)))

(define-public r-openrepgrid-ic
  (package
    (name "r-openrepgrid-ic")
    (version "0.6.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OpenRepGrid.ic" version))
       (sha256
        (base32 "1v8sqlid97xnp0nddn4yr6im8zah1pclirvmz1n7qmc91656plx6"))))
    (properties `((upstream-name . "OpenRepGrid.ic")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr
                             r-tidyverse
                             r-tidyr
                             r-stringr
                             r-shinywidgets
                             r-shinythemes
                             r-shinyjs
                             r-shinyfeedback
                             r-shinydashboardplus
                             r-shinydashboard
                             r-shinycssloaders
                             r-shinybs
                             r-shiny
                             r-scales
                             r-rintrojs
                             r-reshape2
                             r-rcolorbrewer
                             r-openxlsx
                             r-magrittr
                             r-igraph
                             r-formattable
                             r-dt
                             r-dplyr))
    (home-page "https://github.com/markheckmann/OpenRepGrid.ic")
    (synopsis "Interpretive Clustering for Repertory Grids")
    (description
     "Shiny UI to identify cliques of related constructs in repertory grid data.  See
Burr, King, & Heckmann (2020) <doi:10.1080/14780887.2020.1794088> for a
description of the interpretive clustering (IC) method.")
    (license license:expat)))

(define-public r-openrepgrid
  (package
    (name "r-openrepgrid")
    (version "0.1.15")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OpenRepGrid" version))
       (sha256
        (base32 "0sdqz9bhwfqcpggd2yw4inlfzn4qkzv1vxnri6mxqmjpkb7arysw"))))
    (properties `((upstream-name . "OpenRepGrid")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml
                             r-tidyr
                             r-stringr
                             r-scales
                             r-pvclust
                             r-psych
                             r-plyr
                             r-openxlsx
                             r-igraph
                             r-dplyr
                             r-crayon
                             r-colorspace
                             r-abind))
    (home-page "https://github.com/markheckmann/OpenRepGrid")
    (synopsis "Tools to Analyze Repertory Grid Data")
    (description
     "Analyze repertory grids, a qualitative-quantitative data collection technique
devised by George A. Kelly in the 1950s.  Today, grids are used across various
domains ranging from clinical psychology to marketing.  The package contains
functions to quantitatively analyze and visualize repertory grid data (e.g.
Fransella', Bell', & Bannister', 2004, ISBN: 978-0-470-09080-0).  The package is
part of the The package is part of the <https://openrepgrid.org/> project.")
    (license license:gpl2+)))

(define-public r-opennlpdata
  (package
    (name "r-opennlpdata")
    (version "1.5.3-5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openNLPdata" version))
       (sha256
        (base32 "03a194yjzlxymq64c6pd28ja71gv2z5465hb7qmxbw0gqpirz3l0"))))
    (properties `((upstream-name . "openNLPdata")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (propagated-inputs (list r-rjava))
    (home-page "https://opennlp.apache.org/")
    (synopsis "Apache OpenNLP Jars and Basic English Language Models")
    (description
     "Apache @code{OpenNLP} jars and basic English language models.")
    (license license:gpl3)))

(define-public r-opennlp
  (package
    (name "r-opennlp")
    (version "0.2-7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openNLP" version))
       (sha256
        (base32 "15yl74wv6w1d2wwpn1xlkkpam3c62977gnqal651fv623v29gg35"))))
    (properties `((upstream-name . "openNLP")))
    (build-system r-build-system)
    (inputs (list openjdk))
    (propagated-inputs (list r-rjava r-opennlpdata r-nlp))
    (home-page "https://cran.r-project.org/package=openNLP")
    (synopsis "Apache OpenNLP Tools Interface")
    (description
     "An interface to the Apache @code{OpenNLP} tools (version 1.5.3).  The Apache
@code{OpenNLP} library is a machine learning based toolkit for the processing of
natural language text written in Java.  It supports the most common NLP tasks,
such as tokenization, sentence segmentation, part-of-speech tagging, named
entity extraction, chunking, parsing, and coreference resolution.  See
<https://opennlp.apache.org/> for more information.")
    (license license:gpl3)))

(define-public r-openmse
  (package
    (name "r-openmse")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openMSE" version))
       (sha256
        (base32 "1yd5p92w9l4vag591slnxvj8zzljilv7idv52978z2gsrihy5lsb"))))
    (properties `((upstream-name . "openMSE")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-samtool
                             r-purrr
                             r-msetool
                             r-ggplot2
                             r-dplyr
                             r-dlmtool
                             r-crayon))
    (home-page "https://openmse.com/")
    (synopsis "Easily Install and Load the 'openMSE' Packages")
    (description
     "The @code{openMSE} package is designed for building operating models, doing
simulation modelling and management strategy evaluation for fisheries.
@code{openMSE} is an umbrella package for the MSEtool (Management Strategy
Evaluation toolkit), DLMtool (Data-Limited Methods toolkit), and SAMtool (Stock
Assessment Methods toolkit) packages.  By loading and installing
@code{openMSE}', users have access to the full functionality contained within
these packages.  Learn more about @code{openMSE} at <https://openmse.com/>.")
    (license license:gpl3)))

(define-public r-openml
  (package
    (name "r-openml")
    (version "1.12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OpenML" version))
       (sha256
        (base32 "0ij4mnbfkckidv9f414fclyhrbbkgmpz5zsjiqa3zlckr3pfaxg7"))))
    (properties `((upstream-name . "OpenML")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml
                             r-stringi
                             r-memoise
                             r-jsonlite
                             r-httr
                             r-digest
                             r-data-table
                             r-curl
                             r-checkmate
                             r-bbmisc
                             r-backports))
    (native-inputs (list r-r-rsp))
    (home-page "https://github.com/openml/openml-r")
    (synopsis "Open Machine Learning and Open Data Platform")
    (description
     "We provide an R interface to @code{OpenML.org} which is an online machine
learning platform where researchers can access open data, download and upload
data sets, share their machine learning tasks and experiments and organize them
online to work and collaborate with other researchers.  The R interface allows
to query for data sets with specific properties, and allows the downloading and
uploading of data sets, tasks, flows and runs.  See
<https://www.openml.org/guide/api> for more information.")
    (license license:bsd-3)))

(define-public r-openmindat
  (package
    (name "r-openmindat")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OpenMindat" version))
       (sha256
        (base32 "1y9f358yn1d2xfqcgmmhcnyxr29fd2frh6ka70pzk63szswszs50"))))
    (properties `((upstream-name . "OpenMindat")))
    (build-system r-build-system)
    (propagated-inputs (list r-usethis
                             r-stringr
                             r-stringi
                             r-readxl
                             r-jsonlite
                             r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/quexiang/OpenMindat")
    (synopsis "Quickly Retrieve Datasets from the 'mindat.org' API")
    (description
     "Mindat ('mindat.org') is one of the world's most widely used databases of
mineral species and their distribution.  Many scientists in mineralogy,
geochemistry, petrology, and other Earth and planetary disciplines have been
using the Mindat data.  Still, an open data service and the machine interface
have never been fully established.  To meet the overwhelming data needs, the
Mindat team has built an API (<https://api.mindat.org/schema/redoc/>) for data
access.'@code{OpenMindat} R package provides valuable functions to bridge the
data highway, connecting users data requirements to the Mindat API server and
assist with retrieval and initial processing to improve efficiency further and
lower the barrier of data query and access to scientists. @code{OpenMindat}
provides friendly and extensible data retrieval functions, including the
subjects of geomaterials (e.g., rocks, minerals, synonyms, variety, mixture, and
commodity), localities, and the IMA (International Mineralogical
Association)-approved mineral list. @code{OpenMindat} R package will accelerate
the process of data-intensive studies in mineral informatics and lead to more
scientific discoveries.")
    (license license:expat)))

(define-public r-openmetrics
  (package
    (name "r-openmetrics")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openmetrics" version))
       (sha256
        (base32 "0bcljsirlkxn0h87j2g2jb6spcik84h7nms06mcj40ckx188yr82"))))
    (properties `((upstream-name . "openmetrics")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6))
    (home-page "https://github.com/atheriel/openmetrics")
    (synopsis "'Prometheus' Client for R Using the 'OpenMetrics' Format")
    (description
     "This package provides a client for the open-source monitoring and alerting
toolkit, Prometheus', that emits metrics in the @code{OpenMetrics} format.
Allows users to automatically instrument Plumber and Shiny applications, collect
standard process metrics, as well as define custom counter, gauge, and histogram
metrics of their own.")
    (license license:expat)))

(define-public r-openmeteo
  (package
    (name "r-openmeteo")
    (version "0.2.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openmeteo" version))
       (sha256
        (base32 "147zc2mn9ma6rkdz5czkmq8pp9slkvz44vf00mi64jkq2gp9kfpx"))))
    (properties `((upstream-name . "openmeteo")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-tidyr
                             r-tibblify
                             r-tibble
                             r-testthat
                             r-httr
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=openmeteo")
    (synopsis "Retrieve Weather Data from the Open-Meteo API")
    (description
     "This package provides a client for the Open-Meteo API that retrieves Open-Meteo
weather data in a tidy format.  No API key is required.  The API specification
is located at <https://open-meteo.com/en/docs>.")
    (license license:gpl3+)))

(define-public r-openland
  (package
    (name "r-openland")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OpenLand" version))
       (sha256
        (base32 "0qm08j12yrh3kyz3azpgp3w9pwvf4i8ymwisks8iqz05k2kw1r36"))))
    (properties `((upstream-name . "OpenLand")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-raster
                             r-networkd3
                             r-gridextra
                             r-ggplot2
                             r-dplyr
                             r-circlize))
    (native-inputs (list r-knitr))
    (home-page "https://reginalexavier.github.io/OpenLand/")
    (synopsis "Quantitative Analysis and Visualization of LUCC")
    (description
     "This package provides tools for the analysis of land use and cover (LUC) time
series.  It includes support for loading spatiotemporal raster data and
synthesized spatial plotting.  Several LUC change (LUCC) metrics in regular or
irregular time intervals can be extracted and visualized through one- and
multistep sankey and chord diagrams.  A complete intensity analysis according to
Aldwaik and Pontius (2012) <doi:10.1016/j.landurbplan.2012.02.010> is
implemented, including tools for the generation of standardized multilevel
output graphics.")
    (license license:gpl3)))

(define-public r-openintro
  (package
    (name "r-openintro")
    (version "2.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openintro" version))
       (sha256
        (base32 "0d9x109806ylay80ih6zrfqqjylbi0ralr9k7rz6xar40rimzb5z"))))
    (properties `((upstream-name . "openintro")))
    (build-system r-build-system)
    (propagated-inputs (list r-usdata
                             r-tibble
                             r-rmarkdown
                             r-readr
                             r-ggplot2
                             r-cherryblossom
                             r-airports))
    (native-inputs (list r-knitr))
    (home-page "http://openintrostat.github.io/openintro/")
    (synopsis
     "Datasets and Supplemental Functions from 'OpenIntro' Textbooks and Labs")
    (description
     "Supplemental functions and data for @code{OpenIntro} resources, which includes
open-source textbooks and resources for introductory statistics
(<https://www.openintro.org/>).  The package contains datasets used in our
open-source textbooks along with custom plotting functions for reproducing book
figures.  Note that many functions and examples include color transparency; some
plotting elements may not show up properly (or at all) when run in some versions
of Windows operating system.")
    (license license:gpl3)))

(define-public r-openimager
  (package
    (name "r-openimager")
    (version "1.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OpenImageR" version))
       (sha256
        (base32 "0j15kwhjazr35yqs9lhw0pfqmrd9rm75gs160dn3xcyc3nw2is56"))))
    (properties `((upstream-name . "OpenImageR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tiff
                             r-shiny
                             r-rcpparmadillo
                             r-rcpp
                             r-r6
                             r-png
                             r-lifecycle
                             r-jpeg))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mlampros/OpenImageR")
    (synopsis "An Image Processing Toolkit")
    (description
     "Incorporates functions for image preprocessing, filtering and image recognition.
 The package takes advantage of @code{RcppArmadillo} to speed up computationally
intensive functions.  The histogram of oriented gradients descriptor is a
modification of the @code{findHOGFeatures} function of the @code{SimpleCV}
computer vision platform, the average_hash(), dhash() and phash() functions are
based on the @code{ImageHash} python library.  The Gabor Feature Extraction
functions are based on Matlab code of the paper, \"@code{CloudID}: Trustworthy
cloud-based and cross-enterprise biometric identification\" by M. Haghighat, S.
Zonouz, M. Abdel-Mottaleb, Expert Systems with Applications, vol.  42, no.  21,
pp.  7905-7916, 2015, <doi:10.1016/j.eswa.2015.06.025>.  The SLIC and SLICO
superpixel algorithms were explained in detail in (i) \"SLIC Superpixels Compared
to State-of-the-art Superpixel Methods\", Radhakrishna Achanta, Appu Shaji, Kevin
Smith, Aurelien Lucchi, Pascal Fua, and Sabine Suesstrunk, IEEE Transactions on
Pattern Analysis and Machine Intelligence, vol.  34, num.  11, p.  2274-2282,
May 2012, <doi:10.1109/TPAMI.2012.120> and (ii) \"SLIC Superpixels\", Radhakrishna
Achanta, Appu Shaji, Kevin Smith, Aurelien Lucchi, Pascal Fua, and Sabine
Suesstrunk, EPFL Technical Report no.  149300, June 2010.")
    (license license:gpl3)))

(define-public r-openhimr
  (package
    (name "r-openhimr")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OpEnHiMR" version))
       (sha256
        (base32 "0wgjihdfjvsf3p97ll496ixwv2xzlgsr138pzgalw5hq0p1kmld6"))))
    (properties `((upstream-name . "OpEnHiMR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyverse
                             r-stringr
                             r-splitstackshape
                             r-seqinr
                             r-rcurl
                             r-randomforest
                             r-party
                             r-gbm
                             r-ftrcool
                             r-entropy
                             r-e1071
                             r-dplyr
                             r-devtools
                             r-caret
                             r-biostrings))
    (home-page "https://cran.r-project.org/package=OpEnHiMR")
    (synopsis
     "Optimization Based Ensemble Model for Prediction of Histone Modifications in Rice")
    (description
     "The comprehensive knowledge of epigenetic modifications in plants, encompassing
histone modifications in regulating gene expression, is not completely
ingrained.  It is noteworthy that histone deacetylation and histone H3 lysine 27
trimethylation (H3K27me3) play a role in repressing transcription in eukaryotes.
 In contrast, histone acetylation (H3K9ac) and H3K4me3 have been inevitably
linked to the stimulation of gene expression, which significantly influences
plant development and plays a role in plant responses to biotic and abiotic
stresses.  To our knowledge this the first multiclass classifier for predicting
histone modification in plants. <doi:10.1186/s12864-019-5489-4>.")
    (license license:gpl3)))

(define-public r-openfda
  (package
    (name "r-openfda")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openFDA" version))
       (sha256
        (base32 "1z5mljnn4f6hasc207spiz5yvhrssb09mfnbnfdi8p7di0wg8szw"))))
    (properties `((upstream-name . "openFDA")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-rlang
                             r-purrr
                             r-httr2
                             r-cli
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/simpar1471/openFDA")
    (synopsis "'openFDA' API")
    (description
     "The @code{openFDA} API facilitates access to Federal Drug Agency (FDA) data on
drugs, devices, foodstuffs, tobacco, and more with httr2'.  This package makes
the API easily accessible, returning objects which the user can convert to JSON
data and parse.  Kass-Hout TA, Xu Z, Mohebbi M et al. (2016)
<doi:10.1093/jamia/ocv153>.")
    (license license:gpl3+)))

(define-public r-openeo
  (package
    (name "r-openeo")
    (version "1.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openeo" version))
       (sha256
        (base32 "02rm34mgjhcb3pp71x0rspyz7cmpmj4g5rs93xnly304il8v0rx2"))))
    (properties `((upstream-name . "openeo")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf
                             r-rlang
                             r-r6
                             r-lubridate
                             r-jsonlite
                             r-irdisplay
                             r-httr2
                             r-htmltools
                             r-base64enc))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Open-EO/openeo-r-client")
    (synopsis "Client Interface for 'openEO' Servers")
    (description
     "Access data and processing functionalities of @code{openEO} compliant back-ends
in R.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-openebgm
  (package
    (name "r-openebgm")
    (version "0.9.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openEBGM" version))
       (sha256
        (base32 "19q5xlvgc91mcr6sjzppgkmvdlfb6cr7rs952i2yys3w7ylwk3bj"))))
    (properties `((upstream-name . "openEBGM")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2 r-data-table))
    (native-inputs (list r-knitr))
    (home-page
     "https://journal.r-project.org/archive/2017/RJ-2017-063/index.html")
    (synopsis "EBGM Disproportionality Scores for Adverse Event Data Mining")
    (description
     "An implementation of @code{DuMouchel's} (1999)
<doi:10.1080/00031305.1999.10474456> Bayesian data mining method for the market
basket problem.  Calculates Empirical Bayes Geometric Mean (EBGM) and posterior
quantile scores using the Gamma-Poisson Shrinker (GPS) model to find unusually
large cell counts in large, sparse contingency tables.  Can be used to find
unusually high reporting rates of adverse events associated with products.  In
general, can be used to mine any database where the co-occurrence of two
variables or items is of interest.  Also calculates relative and proportional
reporting ratios.  Builds on the work of the @code{PhViD} package, from which
much of the code is derived.  Some of the added features include stratification
to adjust for confounding variables and data squashing to improve computational
efficiency.  Includes an implementation of the EM algorithm for hyperparameter
estimation loosely derived from the @code{mederrRank} package.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-opendotar
  (package
    (name "r-opendotar")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "opendotaR" version))
       (sha256
        (base32 "17cygsw3nkg6zincfrcdh1509rlz3n5zrv9wvv7mjngm61sn79nf"))))
    (properties `((upstream-name . "opendotaR")))
    (build-system r-build-system)
    (propagated-inputs (list r-lubridate r-jsonlite r-dplyr))
    (home-page "https://cran.r-project.org/package=opendotaR")
    (synopsis "Interface for OpenDota API")
    (description
     "Enables the usage of the @code{OpenDota} API from <https://www.opendota.com/>,
get game lists, and download JSON's of parsed replays from the @code{OpenDota}
API. Also has functionality to execute own code to extract the specific parts of
the JSON file.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-opendatatoronto
  (package
    (name "r-opendatatoronto")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "opendatatoronto" version))
       (sha256
        (base32 "1fiviazs0ydxvmsqaayhwnxf4wl4sx1psn8i5mpis7218d9ihagy"))))
    (properties `((upstream-name . "opendatatoronto")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-tibble
                             r-sf
                             r-readxl
                             r-magrittr
                             r-curl
                             r-ckanr))
    (native-inputs (list r-knitr))
    (home-page "https://sharlagelfand.github.io/opendatatoronto/")
    (synopsis "Access the City of Toronto Open Data Portal")
    (description "Access data from the \"City of Toronto Open Data Portal\"
(<https://open.toronto.ca>) directly from R.")
    (license license:expat)))

(define-public r-opendataformat
  (package
    (name "r-opendataformat")
    (version "1.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "opendataformat" version))
       (sha256
        (base32 "14j1wpi9kmyms6ag0zdirfjqq7xbkj89ynffnhybkg8pfj4rh8pw"))))
    (properties `((upstream-name . "opendataformat")))
    (build-system r-build-system)
    (propagated-inputs (list r-zip r-xml2 r-magrittr r-data-table r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/opendataformat/r-package-opendataformat")
    (synopsis "Reading and Writing Open Data Format Files")
    (description
     "The Open Data Format (ODF) is a new, non-proprietary, multilingual, metadata
enriched, and zip-compressed data format with metadata structured in the Data
Documentation Initiative (DDI) Codebook standard.  This package allows reading
and writing of data files in the Open Data Format (ODF) in R, and displaying
metadata in different languages.  For further information on the Open Data
Format, see <https://opendataformat.github.io/>.")
    (license license:expat)))

(define-public r-opencv
  (package
    (name "r-opencv")
    (version "0.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "opencv" version))
       (sha256
        (base32 "087vjygs446lw10nizl14kq27n668wqky3jr6ks28mqmcvk1wgqx"))))
    (properties `((upstream-name . "opencv")))
    (build-system r-build-system)
    (inputs (list zlib))
    (propagated-inputs (list r-rcpp r-magrittr))
    (native-inputs (list pkg-config))
    (home-page "https://cran.r-project.org/package=opencv")
    (synopsis "Bindings to 'OpenCV' Computer Vision Library")
    (description
     "Exposes some of the available @code{OpenCV} <https://opencv.org/> algorithms,
such as a QR code scanner, and edge, body or face detection.  These can either
be applied to analyze static images, or to filter live video footage from a
camera device.")
    (license license:expat)))

(define-public r-opencr
  (package
    (name "r-opencr")
    (version "2.2.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openCR" version))
       (sha256
        (base32 "08cqv6xxv35hzllab0glb42h54racgqk0x3dvam6lk7c561kbas4"))))
    (properties `((upstream-name . "openCR")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-secr
                             r-rcppparallel
                             r-rcpp
                             r-plyr
                             r-nlme
                             r-mass
                             r-bh
                             r-abind))
    (native-inputs (list r-knitr))
    (home-page "https://www.otago.ac.nz/density/")
    (synopsis "Open Population Capture-Recapture")
    (description
     "Non-spatial and spatial open-population capture-recapture analysis.")
    (license license:gpl2+)))

(define-public r-opencl
  (package
    (name "r-opencl")
    (version "0.2-10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OpenCL" version))
       (sha256
        (base32 "0nkf1rfplzpwf722xiswvvjqla0aysaga5g6r1whx6ksy21xbhpi"))))
    (properties `((upstream-name . "OpenCL")))
    (build-system r-build-system)
    (home-page "http://www.rforge.net/OpenCL/")
    (synopsis "Interface allowing R to use OpenCL")
    (description
     "This package provides an interface to @code{OpenCL}, allowing R to leverage
computing power of GPUs and other HPC accelerator devices.")
    (license license:bsd-3)))

(define-public r-opencage
  (package
    (name "r-opencage")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "opencage" version))
       (sha256
        (base32 "1sjkpp6cj6ivd68p6ql6vwgdvy0fwfkjv84wgwgb4i7f4mnxgnff"))))
    (properties `((upstream-name . "opencage")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr
                             r-tidyr
                             r-tibble
                             r-rlang
                             r-ratelimitr
                             r-purrr
                             r-progress
                             r-memoise
                             r-lifecycle
                             r-jsonlite
                             r-dplyr
                             r-crul))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/opencage/")
    (synopsis "Geocode with the OpenCage API")
    (description
     "Geocode with the @code{OpenCage} API, either from place name to longitude and
latitude (forward geocoding) or from longitude and latitude to the name and
address of a location (reverse geocoding), see <https://opencagedata.com/>.")
    (license license:gpl2+)))

(define-public r-openblender
  (package
    (name "r-openblender")
    (version "0.5.81")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openblender" version))
       (sha256
        (base32 "01akixxj04kgrxhv04icrivfpnipnpg9j62i3y19q3jkl9846lh1"))))
    (properties `((upstream-name . "openblender")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-httr))
    (home-page "https://cran.r-project.org/package=openblender")
    (synopsis "Request <https://openblender.io> API Services")
    (description
     "Interface to make HTTP requests to @code{OpenBlender} API services.  Go to
<https://openblender.io> for more information.")
    (license license:expat)))

(define-public r-openbanker
  (package
    (name "r-openbanker")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openbankeR" version))
       (sha256
        (base32 "04jh3nnp53dzbk96dcz0xi67jqmp66mzbj81cy8mhhd2rl5ry9cj"))))
    (properties `((upstream-name . "openbankeR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-magrittr
                             r-jsonlite
                             r-httr
                             r-httpcode
                             r-glue
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/nik01010/openbankeR")
    (synopsis "R Client for Querying the UK 'Open Banking' ('Open Data') API")
    (description
     "This package creates a client with queries for the UK Open Banking ('Open Data')
API.")
    (license license:gpl3)))

(define-public r-openappr
  (package
    (name "r-openappr")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openappr" version))
       (sha256
        (base32 "1icdv5cr39xrv0nyqaz6727ffzh7zc84j1lb9jbz7bai8ky9k3w1"))))
    (properties `((upstream-name . "openappr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-rsqlite
                             r-rpostgres
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-jsonlite
                             r-dplyr
                             r-dbi))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=openappr")
    (synopsis "Retrieve App Data from 'OpenAppBuilder'")
    (description
     "This package provides an interface to connect R with the
<https://github.com/IDEMSInternational/open-app-builder> @code{OpenAppBuilder}
platform, enabling users to retrieve and work with user and notification data
for analysis and processing.  It is designed for developers and analysts to
seamlessly integrate data from @code{OpenAppBuilder} into R workflows via a
Postgres database connection, allowing direct querying and import of app data
into R.")
    (license license:lgpl3+)))

(define-public r-openalexr
  (package
    (name "r-openalexr")
    (version "1.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openalexR" version))
       (sha256
        (base32 "14bhwbkwxaj8vjrix7klhqqxrfkaybd83dxkvxhpnsfr7yqhls3q"))))
    (properties `((upstream-name . "openalexR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-progress r-jsonlite r-httr))
    (home-page "https://github.com/ropensci/openalexR")
    (synopsis
     "Getting Bibliographic Records from 'OpenAlex' Database Using 'DSL' API")
    (description
     "This package provides a set of tools to extract bibliographic content from
@code{OpenAlex} database using API <https://docs.openalex.org>.")
    (license license:expat)))

(define-public r-openaistream
  (package
    (name "r-openaistream")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openaistream" version))
       (sha256
        (base32 "0zihkpq6p7a3n0qdwpazds4qbpagk7zh6ziflm9194vbygyskv2z"))))
    (properties `((upstream-name . "openaistream")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6 r-jsonlite r-iterators r-httr2 r-curl))
    (home-page "https://github.com/libingfei/openaistream")
    (synopsis "Streaming Capabilities for 'OpenAI API' Interactions")
    (description
     "Based on the httr2 framework, the @code{OpenAI} interface supports streaming
calls and model training.  For more details on the API methods implemented, see
the @code{OpenAI} platform documentation at
<https://platform.openai.com/docs/api-reference>.")
    (license license:expat)))

(define-public r-openairmaps
  (package
    (name "r-openairmaps")
    (version "0.9.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openairmaps" version))
       (sha256
        (base32 "1g3jxks2qvys3rv5z4lz0889fq5b5wyjmzfgcj6pl3l67lgy5yj1"))))
    (properties `((upstream-name . "openairmaps")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-sf
                             r-rosm
                             r-rlang
                             r-purrr
                             r-prettymapr
                             r-openair
                             r-mgcv
                             r-magrittr
                             r-lubridate
                             r-lifecycle
                             r-leaflet
                             r-ggtext
                             r-ggspatial
                             r-ggplot2
                             r-forcats
                             r-dplyr
                             r-cli))
    (home-page "https://davidcarslaw.github.io/openairmaps/")
    (synopsis "Create Maps of Air Pollution Data")
    (description
     "Combine the air quality data analysis methods of openair with the
@code{JavaScript} Leaflet (<https://leafletjs.com/>) library.  Functionality
includes plotting site maps, \"directional analysis\" figures such as polar plots,
and air mass trajectories.")
    (license license:gpl3+)))

(define-public r-openair
  (package
    (name "r-openair")
    (version "2.18-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "openair" version))
       (sha256
        (base32 "1pw4bdqkd515n7fdcjavjmanhpaywxamzywgiaz4nk5bqq5mh84b"))))
    (properties `((upstream-name . "openair")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-rlang
                             r-readr
                             r-rcpp
                             r-purrr
                             r-mgcv
                             r-mass
                             r-mapproj
                             r-lubridate
                             r-latticeextra
                             r-lattice
                             r-hexbin
                             r-dplyr
                             r-cluster
                             r-cli))
    (home-page "https://davidcarslaw.github.io/openair/")
    (synopsis "Tools for the Analysis of Air Pollution Data")
    (description
     "This package provides tools to analyse, interpret and understand air pollution
data.  Data are typically regular time series and air quality measurement,
meteorological data and dispersion model output can be analysed.  The package is
described in Carslaw and Ropkins (2012, <doi:10.1016/j.envsoft.2011.09.008>) and
subsequent papers.")
    (license license:gpl2+)))

(define-public r-opdoe
  (package
    (name "r-opdoe")
    (version "1.0-10")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OPDOE" version))
       (sha256
        (base32 "04z944i4f3i0cjnxh32wf7n2dfyynnvkz4lxdkn90flam2np58yv"))))
    (properties `((upstream-name . "OPDOE")))
    (build-system r-build-system)
    (propagated-inputs (list r-polynom
                             r-orthopolynom
                             r-nlme
                             r-mvtnorm
                             r-gmp
                             r-crossdes))
    (home-page "https://cran.r-project.org/package=OPDOE")
    (synopsis "Optimal Design of Experiments")
    (description
     "Several function related to Experimental Design are implemented here, see
\"Optimal Experimental Design with R\" by Rasch D. et.  al (ISBN 9781439816974).")
    (license license:gpl2+)))

(define-public r-opdisdownsampling
  (package
    (name "r-opdisdownsampling")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "opdisDownsampling" version))
       (sha256
        (base32 "10r6s87ffxzdcrwfwxwikxilpd4ccksma9g9sbz80l3mhlakvskl"))))
    (properties `((upstream-name . "opdisDownsampling")))
    (build-system r-build-system)
    (propagated-inputs (list r-twosamples
                             r-pracma
                             r-pbmcapply
                             r-foreach
                             r-doparallel
                             r-catools))
    (home-page "https://cran.r-project.org/package=opdisDownsampling")
    (synopsis
     "Optimal Distribution Preserving Down-Sampling of Bio-Medical Data")
    (description
     "An optimized method for distribution-preserving class-proportional down-sampling
of bio-medical data.")
    (license license:gpl3)))

(define-public r-opc
  (package
    (name "r-opc")
    (version "0.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OPC" version))
       (sha256
        (base32 "01ljrczj9ds18x40fas4rsca4phqsjaz8w8nvbr7xprf4fp8zpcj"))))
    (properties `((upstream-name . "OPC")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (home-page "https://cran.r-project.org/package=OPC")
    (synopsis "The Online Principal Component Estimation Method")
    (description
     "The online principal component method can process the online data set.  The
philosophy of the package is described in Guo G. (2018)
<doi:10.1080/10485252.2018.1531130>.")
    (license license:expat)))

(define-public r-opalr
  (package
    (name "r-opalr")
    (version "3.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "opalr" version))
       (sha256
        (base32 "08jh04m6bpcfidibgl6qb01fii6smb5wvjxji6fp19iahcl9wn6h"))))
    (properties `((upstream-name . "opalr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-readr
                             r-progress
                             r-mime
                             r-labelled
                             r-jsonlite
                             r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/obiba/opalr/")
    (synopsis "'Opal' Data Repository Client and 'DataSHIELD' Utils")
    (description
     "Data integration Web application for biobanks by O@code{BiBa}'.  Opal is the
core database application for biobanks.  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 typically
used in a research center to analyze the data acquired at assessment centres.
Its ultimate purpose is to achieve seamless data-sharing among biobanks.  This
Opal client allows to interact with Opal web services and to perform operations
on the R server side. @code{DataSHIELD} administration tools are also provided.")
    (license license:gpl3)))

(define-public r-opa
  (package
    (name "r-opa")
    (version "0.8.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "opa" version))
       (sha256
        (base32 "09k3bkh2glkl0sf5pcbii9cxq6ijpdsayncb02dm0ing2bh9kh0m"))))
    (properties `((upstream-name . "opa")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-lattice))
    (native-inputs (list r-knitr))
    (home-page "https://timbeechey.github.io/opa/")
    (synopsis "An Implementation of Ordinal Pattern Analysis")
    (description
     "Quantifies hypothesis to data fit for repeated measures and longitudinal data,
as described by Thorngate (1987) <doi:10.1016/S0166-4115(08)60083-7> and Grice
et al., (2015) <doi:10.1177/2158244015604192>.  Hypothesis and data are encoded
as pairwise relative orderings which are then compared to determine the
percentage of orderings in the data that are matched by the hypothesis.")
    (license license:gpl3+)))

(define-public r-oottest
  (package
    (name "r-oottest")
    (version "0.9.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oottest" version))
       (sha256
        (base32 "1y0k0jcncjkcgfxybs2yyfcc7ywa49jnalrw8mn7m04h58gqg77x"))))
    (properties `((upstream-name . "oottest")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/PhilippKuelpmann/oottest")
    (synopsis "Out-of-Treatment Testing")
    (description
     "This package implements the out-of-treatment testing from Kuelpmann and Kuzmics
(2020) <doi:10.2139/ssrn.3441675> based on the Vuong Test introduced in Vuong
(1989) <doi:10.2307/1912557>.  Out-of treatment testing allows for a direct,
pairwise likelihood comparison of theories, calibrated with pre-existing data.")
    (license license:expat)))

(define-public r-oosse
  (package
    (name "r-oosse")
    (version "1.0.11")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oosse" version))
       (sha256
        (base32 "08nx25j5m6vqg9hqns6psldfdmsb81ixjlzdhxpx392ad0j4yfbx"))))
    (properties `((upstream-name . "oosse")))
    (build-system r-build-system)
    (propagated-inputs (list r-rdpack r-matrix r-doparallel r-biocparallel))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=oosse")
    (synopsis "Out-of-Sample RÂ² with Standard Error Estimation")
    (description
     "Estimates out-of-sample RÂ² through bootstrap or cross-validation as a measure
of predictive performance.  In addition, a standard error for this point
estimate is provided, and confidence intervals are constructed.")
    (license license:gpl2)))

(define-public r-oos
  (package
    (name "r-oos")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OOS" version))
       (sha256
        (base32 "0jnj5y26rv0i2561mywcxb7aavmpq16ippq6rblb8jiqjd05nhib"))))
    (properties `((upstream-name . "OOS")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo
                             r-xts
                             r-vars
                             r-tidyr
                             r-sandwich
                             r-purrr
                             r-magrittr
                             r-lubridate
                             r-lmtest
                             r-imputets
                             r-glmnet
                             r-ggplot2
                             r-future
                             r-furrr
                             r-forecast
                             r-dplyr
                             r-caret))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/tylerJPike/OOS")
    (synopsis "Out-of-Sample Time Series Forecasting")
    (description
     "This package provides a comprehensive and cohesive API for the out-of-sample
forecasting workflow: data preparation, forecasting - including both traditional
econometric time series models and modern machine learning techniques - forecast
combination, model and error analysis, and forecast visualization.")
    (license license:gpl3)))

(define-public r-oor
  (package
    (name "r-oor")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OOR" version))
       (sha256
        (base32 "0p5bi4z6q2kz1hkn12hy7qsn1sdb336y8phmznd8cayyfil7hjvh"))))
    (properties `((upstream-name . "OOR")))
    (build-system r-build-system)
    (home-page "https://github.com/mbinois/OOR")
    (synopsis "Optimistic Optimization in R")
    (description
     "Implementation of optimistic optimization methods for global optimization of
deterministic or stochastic functions.  The algorithms feature guarantees of the
convergence to a global optimum.  They require minimal assumptions on the (only
local) smoothness, where the smoothness parameter does not need to be known.
They are expected to be useful for the most difficult functions when we have no
information on smoothness and the gradients are unknown or do not exist.  Due to
the weak assumptions, however, they can be mostly effective only in small
dimensions, for example, for hyperparameter tuning.")
    (license license:lgpl2.0+)))

(define-public r-ooplah
  (package
    (name "r-ooplah")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ooplah" version))
       (sha256
        (base32 "1p74jh9g62yicrw0lhpbn0diqi2myl24z28kpd2b3mglyffadr0b"))))
    (properties `((upstream-name . "ooplah")))
    (build-system r-build-system)
    (propagated-inputs (list r-r6))
    (home-page "https://xoopR.github.io/ooplah/")
    (synopsis "Helper Functions for Class Object-Oriented Programming")
    (description
     "Helper functions for coding object-oriented programming with a focus on R6.
Includes functions for assertions and testing, looping, and re-usable design
patterns including Abstract and Decorator classes.")
    (license license:expat)))

(define-public r-oolong
  (package
    (name "r-oolong")
    (version "0.6.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oolong" version))
       (sha256
        (base32 "10fn3llypnglz6i02pii7i4lki0hrh46b76y8wd7df8j4bcixnn5"))))
    (properties `((upstream-name . "oolong")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-shiny
                             r-seededlda
                             r-r6
                             r-quanteda
                             r-purrr
                             r-irr
                             r-ggplot2
                             r-digest
                             r-cowplot
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://gesistsa.github.io/oolong/")
    (synopsis "Create Validation Tests for Automated Content Analysis")
    (description
     "Intended to create standard human-in-the-loop validity tests for typical
automated content analysis such as topic modeling and dictionary-based methods.
This package offers a standard workflow with functions to prepare, administer
and evaluate a human-in-the-loop validity test.  This package provides functions
for validating topic models using word intrusion, topic intrusion (Chang et al.
2009,
<https://papers.nips.cc/paper/3700-reading-tea-leaves-how-humans-interpret-topic-models>)
and word set intrusion (Ying et al.  2021) <doi:10.1017/pan.2021.33> tests.
This package also provides functions for generating gold-standard data which are
useful for validating dictionary-based methods.  The default settings of all
generated tests match those suggested in Chang et al. (2009) and Song et al.
(2020) <doi:10.1080/10584609.2020.1723752>.")
    (license license:lgpl2.1+)))

(define-public r-oobcurve
  (package
    (name "r-oobcurve")
    (version "0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OOBCurve" version))
       (sha256
        (base32 "1i7prybs3b60ipl34zrq6mcr6w9kc1d44b14mxcd752k42k6xs2r"))))
    (properties `((upstream-name . "OOBCurve")))
    (build-system r-build-system)
    (propagated-inputs (list r-ranger r-randomforest r-mlr))
    (home-page "https://github.com/PhilippPro/OOBCurve")
    (synopsis "Out of Bag Learning Curve")
    (description
     "This package provides functions to calculate the out-of-bag learning curve for
random forests for any measure that is available in the mlr package.  Supported
random forest packages are @code{randomForest} and ranger and trained models of
these packages with the train function of mlr'.  The main function is OOBCurve()
that calculates the out-of-bag curve depending on the number of trees.  With the
OOB@code{CurvePars}() function out-of-bag curves can also be calculated for
mtry', sample.fraction and min.node.size for the ranger package.")
    (license license:gpl3)))

(define-public r-ontophylo
  (package
    (name "r-ontophylo")
    (version "1.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ontophylo" version))
       (sha256
        (base32 "1pb8w39ckx2ffchrrxp1jqs555b5bfz7cv5kbwgyzpfshv9s0ca4"))))
    (properties `((upstream-name . "ontophylo")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncnorm
                             r-tidyr
                             r-tibble
                             r-stringdist
                             r-rcolorbrewer
                             r-purrr
                             r-phytools
                             r-ontologyindex
                             r-magrittr
                             r-grimport
                             r-ggplot2
                             r-fancova
                             r-dplyr
                             r-ape))
    (home-page "https://github.com/diegosasso/ontophylo")
    (synopsis "Ontology-Informed Phylogenetic Comparative Analyses")
    (description
     "This package provides new tools for analyzing discrete trait data integrating
bio-ontologies and phylogenetics.  It expands on the previous work of Tarasov et
al. (2019) <doi:10.1093/isd/ixz009>.  The PARAMO pipeline allows to reconstruct
ancestral phenomes treating groups of morphological traits as a single complex
character.  The pipeline incorporates knowledge from ontologies during the
amalgamation of individual character stochastic maps.  Here we expand the
current PARAMO functionality by adding new statistical methods for inferring
evolutionary phenome dynamics using non-homogeneous Poisson process (NHPP).  The
new functionalities include: (1) reconstruction of evolutionary rate shifts of
phenomes across lineages and time; (2) reconstruction of morphospace dynamics
through time; and (3) estimation of rates of phenome evolution at different
levels of anatomical hierarchy (e.g., entire body or specific regions only).
The package also includes user-friendly tools for visualizing evolutionary rates
of different anatomical regions using vector images of the organisms of
interest.")
    (license license:expat)))

(define-public r-ontologysimilarity
  (package
    (name "r-ontologysimilarity")
    (version "2.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ontologySimilarity" version))
       (sha256
        (base32 "03fga6xqvxpa3hwf5pb0dzyz4scz2szvbgm8bsj1wl35gl477cjp"))))
    (properties `((upstream-name . "ontologySimilarity")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-ontologyindex))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ontologySimilarity")
    (synopsis "Calculating Ontological Similarities")
    (description
     "Calculate similarity between ontological terms and sets of ontological terms
based on term information content and assess statistical significance of
similarity in the context of a collection of terms sets - Greene et al.  2017
<doi:10.1093/bioinformatics/btw763>.")
    (license license:gpl2+)))

(define-public r-ontologyplot
  (package
    (name "r-ontologyplot")
    (version "1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ontologyPlot" version))
       (sha256
        (base32 "06ynryr4yx2mg85v12vhggx795hwwwfniskv3dgmb5nmrxhvh26m"))))
    (properties `((upstream-name . "ontologyPlot")))
    (build-system r-build-system)
    (propagated-inputs (list r-rgraphviz r-paintmap r-ontologyindex))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ontologyPlot")
    (synopsis "Visualising Sets of Ontological Terms")
    (description
     "Create R plots visualising ontological terms and the relationships between them
with various graphical options - Greene et al.  2017
<doi:10.1093/bioinformatics/btw763>.")
    (license license:gpl2+)))

(define-public r-ontologics
  (package
    (name "r-ontologics")
    (version "0.7.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ontologics" version))
       (sha256
        (base32 "1ggdnydxl5xdh8vjjxna778d3c3wvw1rcvvjdcnrllms8i30cvga"))))
    (properties `((upstream-name . "ontologics")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-readr
                             r-rdflib
                             r-purrr
                             r-magrittr
                             r-httr
                             r-fuzzyjoin
                             r-dplyr
                             r-checkmate
                             r-beepr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/luckinet/ontologics")
    (synopsis "Code-Logics to Handle Ontologies")
    (description
     "This package provides tools to build and work with an ontology of linked (open)
data in a tidy workflow.  It is inspired by the Food and Agrilculture
Organizations (FAO) caliper platform
<https://www.fao.org/statistics/caliper/web/> and makes use of the Simple
Knowledge Organisation System (SKOS).")
    (license license:gpl3+)))

(define-public r-ontofast
  (package
    (name "r-ontofast")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ontoFAST" version))
       (sha256
        (base32 "0l3d8bp86849rp0qrs1dfv7bjmrfdqvahb1x656vk69fi20722ma"))))
    (properties `((upstream-name . "ontoFAST")))
    (build-system r-build-system)
    (propagated-inputs (list r-visnetwork
                             r-usethis
                             r-sunburstr
                             r-stringr
                             r-shinydashboard
                             r-shiny
                             r-plyr
                             r-pbapply
                             r-ontologyindex
                             r-dplyr))
    (home-page "https://github.com/sergeitarasov/ontoFAST")
    (synopsis
     "Interactive Annotation of Characters with Biological Ontologies")
    (description
     "This package provides tools for annotating characters (character matrices) with
anatomical and phenotype ontologies.  Includes functions for visualising
character annotations and creating simple queries using ontological
relationships.")
    (license license:gpl2+)))

(define-public r-onsvtables
  (package
    (name "r-onsvtables")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onsvtables" version))
       (sha256
        (base32 "181z69m5ws74wzrka6xb9cxz3yr1m7z57yyr401mxiz4cd466xlw"))))
    (properties `((upstream-name . "onsvtables")))
    (build-system r-build-system)
    (propagated-inputs (list r-gt))
    (home-page "https://github.com/ONSV/onsvtables")
    (synopsis "National Road Safety Observatory (ONSV) Styles for 'gt' Tables")
    (description
     "Wrapper functions for customizing HTML tables from the gt package to the ONSV
style.")
    (license license:expat)))

(define-public r-onsvplot
  (package
    (name "r-onsvplot")
    (version "0.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onsvplot" version))
       (sha256
        (base32 "06jkq25ivi8qn3c46616a7z47g2qfjpvnfwlzjx8shw4c36j5737"))))
    (properties `((upstream-name . "onsvplot")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggplot2))
    (home-page "https://github.com/pabsantos/onsvplot/")
    (synopsis
     "National Road Safety Observatory (ONSV) Style for 'ggplot2' Graphics")
    (description
     "Helps to create ggplot2 charts in the style used by the National Road Safety
Observatory (ONSV).  The package includes functions to customize ggplot2 objects
with new theme and colors.")
    (license license:expat)))

(define-public r-onsr
  (package
    (name "r-onsr")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onsr" version))
       (sha256
        (base32 "07aa0rq41vw4xy76fwwjwcvl2bv15phh5bsk4xb3j7gahy6g9xxi"))))
    (properties `((upstream-name . "onsr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-readr r-jsonlite r-httr))
    (home-page "https://kvasilopoulos.github.io/onsr/")
    (synopsis "Client for the 'ONS' API")
    (description "Client for the Office of National Statistics ('ONS') API
<https://api.beta.ons.gov.uk/v1>.")
    (license license:gpl3+)))

(define-public r-onpoint
  (package
    (name "r-onpoint")
    (version "1.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onpoint" version))
       (sha256
        (base32 "0v45r1sjlhh17xcrw5498k3g82ar2y83b83qp1hfpv5hybghvr5x"))))
    (properties `((upstream-name . "onpoint")))
    (build-system r-build-system)
    (propagated-inputs (list r-spatstat-random r-spatstat-geom
                             r-spatstat-explore r-ggplot2))
    (home-page "https://r-spatialecology.github.io/onpoint/")
    (synopsis "Helper Functions for Point Pattern Analysis")
    (description
     "Growing collection of helper functions for point pattern analysis.  Most
functions are designed to work with the spatstat (<http://spatstat.org>)
package.  The focus of most functions are either null models or summary
functions for spatial point patterns.  For a detailed description of all null
models and summary functions, see Wiegand and Moloney (2014,
ISBN:9781420082548).")
    (license license:gpl3+)))

(define-public r-onomasticdiversity
  (package
    (name "r-onomasticdiversity")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OnomasticDiversity" version))
       (sha256
        (base32 "11v8zk4xvy7a3mfglj7d96d03nsnc2i23ms73v9dci8wdnwnskp1"))))
    (properties `((upstream-name . "OnomasticDiversity")))
    (build-system r-build-system)
    (propagated-inputs (list r-sqldf))
    (home-page "https://cran.r-project.org/package=OnomasticDiversity")
    (synopsis "Onomastic Diversity Measures")
    (description
     "Different measures which can be used to quantify similarities between regions.
These measures are isonymy, isonymy between, Lasker distance, coefficients of
Hedrick and Nei.  In addition, it calculates biodiversity indices such as
Margalef, Menhinick, Simpson, Shannon, Shannon-Wiener, Sheldon, Heip, Hill
Numbers, Geometric Mean and Cressie and Read statistics.")
    (license license:gpl2)))

(define-public r-onnx
  (package
    (name "r-onnx")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onnx" version))
       (sha256
        (base32 "1s0swrcff9v9ffbjkraahmb398gh2jrca2wf5k6gs8037frnl8wd"))))
    (properties `((upstream-name . "onnx")))
    (build-system r-build-system)
    (propagated-inputs (list r-reticulate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/onnx/onnx-r")
    (synopsis "R Interface to 'ONNX'")
    (description
     "R Interface to ONNX - Open Neural Network Exchange <https://onnx.ai/>.  ONNX
provides an open source format for machine learning models.  It defines an
extensible computation graph model, as well as definitions of built-in operators
and standard data types.")
    (license (license:fsdg-compatible "MIT License + file LICENSE"))))

(define-public r-onmarg
  (package
    (name "r-onmarg")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onmaRg" version))
       (sha256
        (base32 "0n4gf8fx6c4abwxcajz8bpsfvgl42dflb99wfn4632csag1a50rl"))))
    (properties `((upstream-name . "onmaRg")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr r-sf r-readxl r-httr r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=onmaRg")
    (synopsis "Import Public Health Ontario's Ontario Marginalization Index")
    (description
     "The Ontario Marginalization Index is a socioeconomic model that is built on
Statistics Canada census data.  The model consists of four dimensions: In 2021,
these dimensions were updated to \"Material Resources\" (previously called
\"Material Deprivation\"), \"Households and Dwellings\" (previously called
\"Residential Instability\"), \"Age and Labour Force\" (previously called
\"Dependency\"), and \"Racialized and Newcomer Populations\" (previously called
\"Ethnic Concentration\").  This update reflects a movement away from
deficit-based language.  2021 data will load with these new dimension names,
wheras 2011 and 2016 data will load with the historical dimension names.  Each
of these dimensions are imported for a variety of geographic levels (DA, CD,
etc.) for the 2021, 2011 and 2016 administrations of the census.  These data
sets contribute to community analysis of equity with respect to Ontario's
Anti-Racism Act.  The Ontario Marginalization Index data is retrieved from the
Public Health Ontario website:
<https://www.publichealthontario.ca/en/data-and-analysis/health-equity/ontario-marginalization-index>.
 The shapefile data is retrieved from the Statistics Canada website:
<https://www12.statcan.gc.ca/census-recensement/2011/geo/bound-limit/bound-limit-eng.cfm>.")
    (license license:gpl3)))

(define-public r-onls
  (package
    (name "r-onls")
    (version "0.1-2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onls" version))
       (sha256
        (base32 "19pgrhr7xzas4s592l4sgv1dfynf3s3d227zwcdv6z6wrxh40hyj"))))
    (properties `((upstream-name . "onls")))
    (build-system r-build-system)
    (propagated-inputs (list r-minpack-lm))
    (home-page "https://cran.r-project.org/package=onls")
    (synopsis "Orthogonal Nonlinear Least-Squares Regression")
    (description
     "Fits two-dimensional data by means of orthogonal nonlinear least-squares using
Levenberg-Marquardt minimization and provides functionality for fit diagnostics
and plotting.")
    (license license:gpl2+)))

(define-public r-onlineretail
  (package
    (name "r-onlineretail")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onlineretail" version))
       (sha256
        (base32 "0lid3g4v51c664304cxgjm209qxv88hqglv89frmj4afc0y6k7sc"))))
    (properties `((upstream-name . "onlineretail")))
    (build-system r-build-system)
    (home-page "https://github.com/allanvc/onlineretail/")
    (synopsis "Online Retail Dataset")
    (description
     "Transactions occurring for a UK-based and registered, non-store online retail
between 01/12/2010 and 09/12/2011 (Chen et.  al., 2012,
<doi:10.1145/1835804.1835882>).  This dataset is included in this package with
the donor's permission, Dr. Daqing Chen.")
    (license license:cc0)))

(define-public r-onlinepca
  (package
    (name "r-onlinepca")
    (version "1.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onlinePCA" version))
       (sha256
        (base32 "1xc9kjqvpspymywzaykw4nw14y43fi4ydwj4jfhvx5ws51f7y9i8"))))
    (properties `((upstream-name . "onlinePCA")))
    (build-system r-build-system)
    (propagated-inputs (list r-rspectra r-rcpparmadillo r-rcpp))
    (home-page "https://cran.r-project.org/package=onlinePCA")
    (synopsis "Online Principal Component Analysis")
    (description
     "Online PCA for multivariate and functional data using perturbation methods,
low-rank incremental methods, and stochastic optimization methods.")
    (license license:gpl3)))

(define-public r-onlineforecast
  (package
    (name "r-onlineforecast")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onlineforecast" version))
       (sha256
        (base32 "0qj9943hmcf584b7czf877zg5rxz8byg97dkk3gnb57q5ar60f3z"))))
    (properties `((upstream-name . "onlineforecast")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp r-r6 r-pbs r-digest))
    (native-inputs (list r-knitr))
    (home-page "https://onlineforecasting.org")
    (synopsis "Forecast Modelling for Online Applications")
    (description
     "This package provides a framework for fitting adaptive forecasting models.
Provides a way to use forecasts as input to models, e.g. weather forecasts for
energy related forecasting.  The models can be fitted recursively and can easily
be setup for updating parameters when new data arrives.  See the included
vignettes, the website <https://onlineforecasting.org> and the paper
\"onlineforecast: An R package for adaptive and recursive forecasting\"
<https://journal.r-project.org/articles/RJ-2023-031/>.")
    (license license:gpl3)))

(define-public r-onlinecov
  (package
    (name "r-onlinecov")
    (version "1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onlineCOV" version))
       (sha256
        (base32 "04ikvsd76f6xhja7djyv433m88lfj2vf0y9qi6x1s4i9kh8xkbz9"))))
    (properties `((upstream-name . "onlineCOV")))
    (build-system r-build-system)
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=onlineCOV")
    (synopsis
     "Online Change Point Detection in High-Dimensional Covariance Structure")
    (description
     "Implement a new stopping rule to detect anomaly in the covariance structure of
high-dimensional online data.  The detection procedure can be applied to
Gaussian or non-Gaussian data with a large number of components.  Moreover, it
allows both spatial and temporal dependence in data.  The dependence can be
estimated by a data-driven procedure.  The level of threshold in the stopping
rule can be determined at a pre-selected average run length.  More detail can be
seen in Li, L. and Li, J. (2020) \"Online Change-Point Detection in
High-Dimensional Covariance Structure with Application to Dynamic Networks.\"
<@code{arXiv:1911.07762>}.")
    (license license:gpl2+)))

(define-public r-onlinebcp
  (package
    (name "r-onlinebcp")
    (version "0.1.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onlineBcp" version))
       (sha256
        (base32 "1pwpnmpgh3hl8mv1pbn577dn832nxbsfaxn3hqghvs4dn06lwngf"))))
    (properties `((upstream-name . "onlineBcp")))
    (build-system r-build-system)
    (propagated-inputs (list r-vim))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=onlineBcp")
    (synopsis "Online Bayesian Methods for Change Point Analysis")
    (description
     "It implements the online Bayesian methods for change point analysis.  It can
also perform missing data imputation with methods from VIM'.  The reference is
Yigiter A, Chen J, An L, Danacioglu N (2015)
<doi:10.1080/02664763.2014.1001330>.  The link to the package is
<https://CRAN.R-project.org/package=@code{onlineBcp>}.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-onion
  (package
    (name "r-onion")
    (version "1.5-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onion" version))
       (sha256
        (base32 "0ja3nqi684c314hh9y5lp59bdfi01vycz17ridw1xlzh89na8c60"))))
    (properties `((upstream-name . "onion")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrix r-mathjaxr r-freealg r-emulator))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/RobinHankin/onion")
    (synopsis "Octonions and Quaternions")
    (description
     "Quaternions and Octonions are four- and eight- dimensional extensions of the
complex numbers.  They are normed division algebras over the real numbers and
find applications in spatial rotations (quaternions), and string theory and
relativity (octonions).  The quaternions are noncommutative and the octonions
nonassociative.  See the package vignette for more details.")
    (license license:gpl2)))

(define-public r-onewaytests
  (package
    (name "r-onewaytests")
    (version "3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onewaytests" version))
       (sha256
        (base32 "0qmzgg869pdj3sfi8znd02z62px9n04fxl1psrfw8mxl4ainp0v7"))))
    (properties `((upstream-name . "onewaytests")))
    (build-system r-build-system)
    (propagated-inputs (list r-wesanderson r-nortest r-moments r-ggplot2 r-car))
    (home-page "https://cran.r-project.org/package=onewaytests")
    (synopsis "One-Way Tests in Independent Groups Designs")
    (description
     "This package performs one-way tests in independent groups designs including
homoscedastic and heteroscedastic tests.  These are one-way analysis of variance
(ANOVA), Welch's heteroscedastic F test, Welch's heteroscedastic F test with
trimmed means and Winsorized variances, Brown-Forsythe test, Alexander-Govern
test, James second order test, Kruskal-Wallis test, Scott-Smith test, Box F
test, Johansen F test, Generalized tests equivalent to Parametric Bootstrap and
Fiducial tests, Alvandi's F test, Alvandi's generalized p-value, approximate F
test, B square test, Cochran test, Weerahandi's generalized F test, modified
Brown-Forsythe test, adjusted Welch's heteroscedastic F test, Welch-Aspin test,
Permutation F test.  The package performs pairwise comparisons and graphical
approaches.  Also, the package includes Student's t test, Welch's t test and
Mann-Whitney U test for two samples.  Moreover, it assesses variance homogeneity
and normality of data in each group via tests and plots (Dag et al., 2018,
<https://journal.r-project.org/archive/2018/RJ-2018-022/RJ-2018-022.pdf>).")
    (license license:gpl2+)))

(define-public r-onetwosamples
  (package
    (name "r-onetwosamples")
    (version "1.1-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OneTwoSamples" version))
       (sha256
        (base32 "0qa5v3c1f5mckvgmw8zbxqkk1q8k8dig1xg9k8pfyvfxqjard1ny"))))
    (properties `((upstream-name . "OneTwoSamples")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=OneTwoSamples")
    (synopsis "Deal with One and Two (Normal) Samples")
    (description
     "We introduce an R function one_two_sample() which can deal with one and two
(normal) samples, Ying-Ying Zhang, Yi Wei (2012) <doi:10.2991/asshm-13.2013.29>.
 For one normal sample x, the function reports descriptive statistics, plot,
interval estimation and test of hypothesis of x.  For two normal samples x and
y, the function reports descriptive statistics, plot, interval estimation and
test of hypothesis of x and y, respectively.  It also reports interval
estimation and test of hypothesis of mu1-mu2 (the difference of the means of x
and y) and sigma1^2 / sigma2^2 (the ratio of the variances of x and y), tests
whether x and y are from the same population, finds the correlation coefficient
of x and y if x and y have the same length.")
    (license license:gpl2+)))

(define-public r-onetime
  (package
    (name "r-onetime")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onetime" version))
       (sha256
        (base32 "1yyi8r8dniavsjlqmj5z9x52av2qz0iz01i2r7qx69apqbkwd57b"))))
    (properties `((upstream-name . "onetime")))
    (build-system r-build-system)
    (propagated-inputs (list r-rappdirs r-filelock))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/hughjonesd/onetime")
    (synopsis "Run Code Only Once")
    (description
     "Allows code to be run only once on a given computer, using lockfiles.  Typical
use cases include startup messages shown only when a package is loaded for the
very first time.")
    (license license:expat)))

(define-public r-onestep
  (package
    (name "r-onestep")
    (version "0.9.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OneStep" version))
       (sha256
        (base32 "0fm8gpdwzdx4s23gg615a6r58mrjrx2k3pcbh8dq4z4067lr880w"))))
    (properties `((upstream-name . "OneStep")))
    (build-system r-build-system)
    (propagated-inputs (list r-numderiv r-fitdistrplus r-extradistr))
    (home-page "https://journal.r-project.org/archive/2021/RJ-2021-044/")
    (synopsis "One-Step Estimation")
    (description
     "Provide principally an eponymic function that numerically computes the Le Cam's
one-step estimator for an independent and identically distributed sample.
One-step estimation is asymptotically efficient (see L. Le Cam (1956)
<https://projecteuclid.org/euclid.bsmsp/1200501652>) and can be computed faster
than the maximum likelihood estimator for large observation samples, see e.g.
Brouste et al. (2021) <doi:10.32614/RJ-2021-044>.")
    (license license:gpl2+)))

(define-public r-onest
  (package
    (name "r-onest")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ONEST" version))
       (sha256
        (base32 "07mfykpkcgcqafw1w3qr9x83zpy2p0q7v1zkgwpd69g79j0r3yap"))))
    (properties `((upstream-name . "ONEST")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/hangangtrue/ONEST")
    (synopsis "Observers Needed to Evaluate Subjective Tests")
    (description
     "This ONEST software implements the method of assessing the pathologist agreement
in reading PD-L1 assays (Reisenbichler et al. (2020
<doi:10.1038/s41379-020-0544-x>)), to determine the minimum number of evaluators
needed to estimate agreement involving a large number of raters.  Input to the
program should be binary(1/0) pathology data, where â0â may stand for
negative and â1â for positive.  Additional examples were given using the
data from Rimm et al. (2017 <doi:10.1001/jamaoncol.2017.0013>).")
    (license license:gpl3)))

(define-public r-onesamplemr
  (package
    (name "r-onesamplemr")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OneSampleMR" version))
       (sha256
        (base32 "1swjc1gsddihdcx9c219vzh9xn379fp8jlvvs5jhikixkk1frqdq"))))
    (properties `((upstream-name . "OneSampleMR")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-msm
                             r-lmtest
                             r-ivreg
                             r-gmm
                             r-formula))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/remlapmot/OneSampleMR")
    (synopsis
     "One Sample Mendelian Randomization and Instrumental Variable Analyses")
    (description
     "Useful functions for one-sample (individual level data) Mendelian randomization
and instrumental variable analyses.  The package includes implementations of;
the Sanderson and Windmeijer (2016) <doi:10.1016/j.jeconom.2015.06.004>
conditional F-statistic, the multiplicative structural mean model HernÃ¡n and
Robins (2006) <doi:10.1097/01.ede.0000222409.00878.37>, and two-stage predictor
substitution and two-stage residual inclusion estimators explained by Terza et
al. (2008) <doi:10.1016/j.jhealeco.2007.09.009>.")
    (license license:gpl3+)))

(define-public r-onesamplelogranktest
  (package
    (name "r-onesamplelogranktest")
    (version "0.9.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OneSampleLogRankTest" version))
       (sha256
        (base32 "1z09nmwp4v4rhr5aqx7k4dg9xvp9nm4djr2kbkivd7hph4fks0qs"))))
    (properties `((upstream-name . "OneSampleLogRankTest")))
    (build-system r-build-system)
    (propagated-inputs (list r-survminer
                             r-survival
                             r-rlang
                             r-magrittr
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OneSampleLogRankTest")
    (synopsis "One-Sample Log-Rank Test")
    (description
     "The log-rank test is performed to assess the survival outcomes between two
group.  When there is no proper control group or obtaining such data is
cumbersome, one sample log-rank test can be applied.  This package performs one
sample log-rank test as described in Finkelstein et al.
(2003)<doi:10.1093/jnci/djt227> and variation of the test for small sample sizes
which is detailed in FD Liddell (1984)<doi:10.1136/jech.38.1.85> paper.
Visualization function in the package generates Kaplan-Meier Curve comparing
survival curve of the general population against that of the population of
interest.")
    (license license:gpl3+)))

(define-public r-oner
  (package
    (name "r-oner")
    (version "2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OneR" version))
       (sha256
        (base32 "1k7rzhcwq5b2yi4zfsc1r0yb6w65gxj9835d2a1dclallja3zav2"))))
    (properties `((upstream-name . "OneR")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/vonjd/OneR")
    (synopsis
     "One Rule Machine Learning Classification Algorithm with Enhancements")
    (description
     "This package implements the One Rule (@code{OneR}) Machine Learning
classification algorithm (Holte, R.C. (1993) <doi:10.1023/A:1022631118932>) with
enhancements for sophisticated handling of numeric data and missing values
together with extensive diagnostic functions.  It is useful as a baseline for
machine learning models and the rules are often helpful heuristics.")
    (license license:expat)))

(define-public r-onemap
  (package
    (name "r-onemap")
    (version "3.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onemap" version))
       (sha256
        (base32 "0h5bi4zyiglic60msrkfny28k1rb7avqbs87ipzwwayb452b970c"))))
    (properties `((upstream-name . "onemap")))
    (build-system r-build-system)
    (propagated-inputs (list r-vcfr
                             r-tidyr
                             r-smacof
                             r-reshape2
                             r-rebus
                             r-rcpp
                             r-rcolorbrewer
                             r-princurve
                             r-plotly
                             r-htmlwidgets
                             r-ggpubr
                             r-ggplot2
                             r-dplyr
                             r-dendextend))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/augusto-garcia/onemap")
    (synopsis "Construction of Genetic Maps in Experimental Crosses")
    (description
     "Analysis of molecular marker data from model (backcrosses, F2 and recombinant
inbred lines) and non-model systems (i.  e.  outcrossing species).  For the
later, it allows statistical analysis by simultaneously estimating linkage and
linkage phases (genetic map construction) according to Wu et al. (2002)
<doi:10.1006/tpbi.2002.1577>.  All analysis are based on multipoint approaches
using hidden Markov models.")
    (license license:gpl3)))

(define-public r-onelogin
  (package
    (name "r-onelogin")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onelogin" version))
       (sha256
        (base32 "06p3a8kaxmvsj8nn7dy8w6wv1jjw67is991hqg9q0fa20ifym3dl"))))
    (properties `((upstream-name . "onelogin")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-safer
                             r-r6
                             r-magrittr
                             r-jsonlite
                             r-glue))
    (home-page "https://cran.r-project.org/package=onelogin")
    (synopsis "Interact with the 'OneLogin' API")
    (description
     "The identity provider ['@code{OneLogin']<http://onelogin.com>} is used for
authentication via Single Sign On (SSO).  This package provides an R interface
to their API.")
    (license license:expat)))

(define-public r-onehot
  (package
    (name "r-onehot")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onehot" version))
       (sha256
        (base32 "1cdsz007wr054k5phvihhg4qx0fc039k2s6484m92kws8mb2ziix"))))
    (properties `((upstream-name . "onehot")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=onehot")
    (synopsis "Fast Onehot Encoding for Data.frames")
    (description
     "Quickly create numeric matrices for machine learning algorithms that require
them.  It converts factor columns into onehot vectors.")
    (license license:expat)))

(define-public r-oneclust
  (package
    (name "r-oneclust")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oneclust" version))
       (sha256
        (base32 "1hwvk3fkjad9z3c9rbwx3v2n4zvjjyrjcl1nxwk9yj6zgrlxbibk"))))
    (properties `((upstream-name . "oneclust")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://nanx.me/oneclust/")
    (synopsis "Maximum Homogeneity Clustering for Univariate Data")
    (description
     "Maximum homogeneity clustering algorithm for one-dimensional data described in
W. D. Fisher (1958) <doi:10.1080/01621459.1958.10501479> via dynamic
programming.")
    (license license:gpl3)))

(define-public r-onearmtte
  (package
    (name "r-onearmtte")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OneArmTTE" version))
       (sha256
        (base32 "186386pjjvlfq38950n1sdx0wq31q8ggjlqlrn07v68bcqjl70y6"))))
    (properties `((upstream-name . "OneArmTTE")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-tibble r-survival r-dplyr))
    (home-page "https://cran.r-project.org/package=OneArmTTE")
    (synopsis "One-Arm Clinical Trial Designs for Time-to-Event Endpoint")
    (description
     "Get operating characteristics of one-arm clinical trial designs for
time-to-event endpoint through simulation and perform analysis with
time-to-event data.")
    (license license:gpl3)))

(define-public r-onearm2stage
  (package
    (name "r-onearm2stage")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OneArm2stage" version))
       (sha256
        (base32 "040yv2bl6s7b1bgma7z1hgrsj8iynzayjc77ncp401nd1ng5wmw5"))))
    (properties `((upstream-name . "OneArm2stage")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-ipdfromkm r-flexsurv))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OneArm2stage")
    (synopsis
     "Phase II Single-Arm Two-Stage Designs with Time-to-Event Outcomes")
    (description
     "Two-stage design for single-arm phase II trials with time-to-event endpoints
(e.g., clinical trials on immunotherapies among cancer patients) can be
calculated using this package.  Two notable advantages of the package: 1) It
provides flexible choices from three design methods (optimal, minmax, and
admissible), and 2) the power of the design is more accurately calculated using
the exact variance in the one-sample log-rank test.  The package can be used for
1) planning the sample sizes and other design parameters, and 2) conducting the
interim and final analyses for the Go/No-go decisions.  More details about the
design method can be found in: Wu, J, Chen L, Wei J, Weiss H, Chauhan A. (2020).
<doi:10.1002/pst.1983>.")
    (license license:gpl3+)))

(define-public r-one4all
  (package
    (name "r-one4all")
    (version "0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "One4All" version))
       (sha256
        (base32 "081d40n8whvhykzdpm2crwmpr3mlczd6svhcpr48nxdhh56pyhjf"))))
    (properties `((upstream-name . "One4All")))
    (build-system r-build-system)
    (propagated-inputs (list r-validate
                             r-tibble
                             r-shiny
                             r-rlang
                             r-readxl
                             r-readr
                             r-openxlsx
                             r-mongolite
                             r-lexicon
                             r-jsonlite
                             r-httr
                             r-dplyr
                             r-digest
                             r-data-table
                             r-ckanr
                             r-aws-s3))
    (native-inputs (list r-knitr))
    (home-page
     "https://github.com/Moore-Institute-4-Plastic-Pollution-Res/One4All")
    (synopsis "Validate, Share, and Download Data")
    (description
     "Designed to enhance data validation and management processes by employing a set
of functions that read a set of rules from a CSV or Excel file and apply them to
a dataset.  Funded by the National Renewable Energy Laboratory and Possibility
Lab, maintained by the Moore Institute for Plastic Pollution Research.")
    (license license:expat)))

(define-public r-ondisc
  (package
    (name "r-ondisc")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ondisc" version))
       (sha256
        (base32 "071jrldclkaz5lfp3k5fh1ilpgvvcnakh2vvnr69n3pri9dl3fls"))))
    (properties `((upstream-name . "ondisc")))
    (build-system r-build-system)
    (propagated-inputs (list r-rhdf5lib
                             r-rhdf5
                             r-readr
                             r-rcpp
                             r-matrix
                             r-magrittr
                             r-dplyr
                             r-data-table
                             r-crayon))
    (native-inputs (list r-knitr))
    (home-page "https://timothy-barry.github.io/ondisc/")
    (synopsis
     "Fast, Universal, and Intuitive Computing on Large-Scale Single-Cell Data")
    (description
     "Single-cell datasets are growing in size, posing challenges as well as
opportunities for biology researchers.  ondisc (short for \"on-disk single cell\")
enables users to easily and efficiently analyze large-scale single-cell data.
ondisc makes computing on large-scale single-cell data FUN: Fast, Universal, and
@code{iNtuitive}.")
    (license license:expat)))

(define-public r-oncrawlr
  (package
    (name "r-oncrawlr")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oncrawlR" version))
       (sha256
        (base32 "0cm26diaf3jlzfrpgh13q0hakakmj6vy41wk9z0w81az4jcg9sn9"))))
    (properties `((upstream-name . "oncrawlR")))
    (build-system r-build-system)
    (propagated-inputs (list r-xgboost
                             r-webshot
                             r-tidyr
                             r-sparkline
                             r-scales
                             r-rlist
                             r-rlang
                             r-rjson
                             r-readr
                             r-rcurl
                             r-proc
                             r-pdp
                             r-jsonlite
                             r-htmltools
                             r-ggplot2
                             r-fs
                             r-formattable
                             r-e1071
                             r-dplyr
                             r-dalex
                             r-caret))
    (home-page "https://cran.r-project.org/package=oncrawlR")
    (synopsis "Machine Learning for S.E.O")
    (description
     "Measures different aspects of page content, structure and performance for SEO
(Search Engine Optimization).  Aspects covered include HTML tags used in SEO,
duplicate and near-duplicate content, structured data, on-site linking structure
and popularity transfer, and many other amazing things.  This package can be
used to generate a real, full SEO audit report, which serves to detect errors or
inefficiencies on a page that can be corrected in order to optimise its
performance on search engines.")
    (license license:expat)))

(define-public r-oncotree
  (package
    (name "r-oncotree")
    (version "0.3.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Oncotree" version))
       (sha256
        (base32 "1c40xggz3ldgma73ik0m10asamd9kns4i30w3zgw4hvpyzalbvm4"))))
    (properties `((upstream-name . "Oncotree")))
    (build-system r-build-system)
    (propagated-inputs (list r-boot))
    (home-page "https://github.com/anikoszabo/Oncotree")
    (synopsis "Estimating Oncogenetic Trees")
    (description
     "Construct and evaluate directed tree structures that model the process of
occurrence of genetic alterations during carcinogenesis as described in Szabo,
A. and Boucher, K (2002) <doi:10.1016/S0025-5564(02)00086-X>.")
    (license license:gpl2+)))

(define-public r-oncosubtype
  (package
    (name "r-oncosubtype")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OncoSubtype" version))
       (sha256
        (base32 "12d32i8q4j0hlkxlk6s8r5ycib6lx5jdsp8g404zmjrsd96aadr2"))))
    (properties `((upstream-name . "OncoSubtype")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-summarizedexperiment
                             r-rlang
                             r-rdpack
                             r-randomforest
                             r-pheatmap
                             r-limma
                             r-e1071
                             r-dplyr
                             r-caret))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/DadongZ/OncoSubtype")
    (synopsis
     "Predict Cancer Subtypes Based on TCGA Data using Machine Learning Method")
    (description
     "Provide functionality for cancer subtyping using nearest centroids or machine
learning methods based on TCGA data.")
    (license license:gpl3)))

(define-public r-oncopredict
  (package
    (name "r-oncopredict")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oncoPredict" version))
       (sha256
        (base32 "0cp0b0d5nbanflp1jrkvdcybjii4lzv275d880wbadsx960rax2l"))))
    (properties `((upstream-name . "oncoPredict")))
    (build-system r-build-system)
    (propagated-inputs (list r-txdb-hsapiens-ucsc-hg19-knowngene
                             r-tidyverse
                             r-tcgabiolinks
                             r-sva
                             r-s4vectors
                             r-ridge
                             r-preprocesscore
                             r-pls
                             r-org-hs-eg-db
                             r-iranges
                             r-glmnet
                             r-genomicranges
                             r-genomicfeatures
                             r-car
                             r-biocgenerics))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/HuangLabUMN/oncoPredict")
    (synopsis "Drug Response Modeling and Biomarker Discovery")
    (description
     "Allows for building drug response models using screening data between bulk
RNA-Seq and a drug response metric and two additional tools for biomarker
discovery that have been developed by the Huang Laboratory at University of
Minnesota.  There are 3 main functions within this package. (1)
@code{calcPhenotype} is used to build drug response models on RNA-Seq data and
impute them on any other RNA-Seq dataset given to the model. (2) GLDS is used to
calculate the general level of drug sensitivity, which can improve biomarker
discovery. (3) IDWAS can take the results from @code{calcPhenotype} and link the
imputed response back to available genomic (mutation and CNV alterations) to
identify biomarkers.  Each of these functions comes from a paper from the Huang
research laboratory.  Below gives the relevant paper for each function.
@code{calcPhenotype} - Geeleher et al, Clinical drug response can be predicted
using baseline gene expression levels and in vitro drug sensitivity in cell
lines.  GLDS - Geeleher et al, Cancer biomarker discovery is improved by
accounting for variability in general levels of drug sensitivity in pre-clinical
models.  IDWAS - Geeleher et al, Discovering novel pharmacogenomic biomarkers by
imputing drug response in cancer patients from large genomics studies.")
    (license license:gpl2)))

(define-public r-oncomsm
  (package
    (name "r-oncomsm")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oncomsm" version))
       (sha256
        (base32 "1crjpfa7yxcafnhsxs2sbf153lsr9ffaqdxjxp0zkd7hiash0mfm"))))
    (properties `((upstream-name . "oncomsm")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-stringr
                             r-stanheaders
                             r-rstantools
                             r-rstan
                             r-rlang
                             r-rcppparallel
                             r-rcppnumerical
                             r-rcppeigen
                             r-rcpp
                             r-purrr
                             r-magrittr
                             r-ggplot2
                             r-furrr
                             r-dplyr
                             r-checkmate
                             r-bh))
    (native-inputs (list r-knitr))
    (home-page "https://boehringer-ingelheim.github.io/oncomsm/")
    (synopsis "Bayesian Multi-State Models for Early Oncology")
    (description
     "This package implements methods to fit a parametric Bayesian multi-state model
to tumor response data.  The model can be used to sample from the predictive
distribution to impute missing data and calculate probability of success for
custom decision criteria in early clinical trials during an ongoing trial.  The
inference is implemented using stan'.")
    (license license:asl2.0)))

(define-public r-oncofilterfast
  (package
    (name "r-oncofilterfast")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Oncofilterfast" version))
       (sha256
        (base32 "1ns39r8ljzykpxy5cy4wvgsgiwqpdrida26641av7z3arr1f4kd1"))))
    (properties `((upstream-name . "Oncofilterfast")))
    (build-system r-build-system)
    (propagated-inputs (list r-survminer r-survival))
    (home-page "https://cran.r-project.org/package=Oncofilterfast")
    (synopsis "Aids in the Analysis of Genes Influencing Cancer Survival")
    (description
     "Aids in the analysis of genes influencing cancer survival by including a
principal function, calculator(), which calculates the P-value for each provided
gene under the optimal cutoff in cancer survival studies.  Grounded in
methodologies from significant works, this package references Therneau's
survival package (Therneau, 2024; <https://CRAN.R-project.org/package=survival>)
and the survival analysis extensions by Therneau and Grambsch (2000, ISBN
0-387-98784-3).  It also integrates the survminer package by Kassambara et al.
(2021; <https://CRAN.R-project.org/package=survminer>), enhancing survival curve
visualizations with ggplot2'.")
    (license license:asl2.0)))

(define-public r-oncobayes2
  (package
    (name "r-oncobayes2")
    (version "0.8-9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OncoBayes2" version))
       (sha256
        (base32 "06k0lbriyx6b1nlvpyjhf5g8dp8wa37wi1pmlpfqq7ryivp39v38"))))
    (properties `((upstream-name . "OncoBayes2")))
    (build-system r-build-system)
    (inputs (list pandoc pandoc))
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-stanheaders
                             r-scales
                             r-rstantools
                             r-rstan
                             r-rlang
                             r-rcppparallel
                             r-rcppeigen
                             r-rcpp
                             r-posterior
                             r-matrixstats
                             r-ggplot2
                             r-formula
                             r-dplyr
                             r-checkmate
                             r-bh
                             r-bayesplot
                             r-assertthat
                             r-abind))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OncoBayes2")
    (synopsis
     "Bayesian Logistic Regression for Oncology Dose-Escalation Trials")
    (description
     "Bayesian logistic regression model with optional
EXchangeability-@code{NonEXchangeability} parameter modelling for flexible
borrowing from historical or concurrent data-sources.  The safety model can
guide dose-escalation decisions for adaptive oncology Phase I dose-escalation
trials which involve an arbitrary number of drugs.  Please refer to
Neuenschwander et al. (2008) <doi:10.1002/sim.3230> and Neuenschwander et al.
(2016) <doi:10.1080/19466315.2016.1174149> for details on the methodology.")
    (license license:gpl3+)))

(define-public r-once
  (package
    (name "r-once")
    (version "0.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "once" version))
       (sha256
        (base32 "0yshpww3rq68m0qx7kid3zlcxi1nf81vmziclyvpg61aikj8fhx5"))))
    (properties `((upstream-name . "once")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr))
    (home-page "https://gdmcdonald.github.io/once/")
    (synopsis "Execute Expensive Operations Only Once")
    (description
     "Allows you to easily execute expensive compute operations only once, and save
the resulting object to disk.")
    (license license:expat)))

(define-public r-onc-api
  (package
    (name "r-onc-api")
    (version "2.0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onc.api" version))
       (sha256
        (base32 "10scbhg6aniqzrbkblhfhz9ni710xzppbzfrr4wrhsy1z5y2nfwc"))))
    (properties `((upstream-name . "onc.api")))
    (build-system r-build-system)
    (propagated-inputs (list r-tictoc
                             r-testthat
                             r-stringi
                             r-lubridate
                             r-humanize
                             r-httr
                             r-crayon
                             r-anytime))
    (home-page "https://wiki.oceannetworks.ca/display/O2A/Oceans+2.0+API+Home")
    (synopsis "Oceans 2.0 API Client Library")
    (description
     "Allows users to discover and retrieve Ocean Networks Canada's oceanographic data
in raw, text, image, audio, video or any other format available.  Provides a
class that wraps web service calls and business logic so that users can download
data with a single line of code.")
    (license license:expat)))

(define-public r-onbrand
  (package
    (name "r-onbrand")
    (version "1.0.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onbrand" version))
       (sha256
        (base32 "1hnhnhzfmd3cjl9ibkydzcy9i7if1f1ykqj0a74wmawh37cv4iiv"))))
    (properties `((upstream-name . "onbrand")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-stringr
                             r-rlang
                             r-officer
                             r-magrittr
                             r-ggplot2
                             r-flextable
                             r-dplyr
                             r-digest))
    (native-inputs (list r-knitr))
    (home-page "https://onbrand.ubiquity.tools/")
    (synopsis "Templated Reporting Workflows in Word and PowerPoint")
    (description
     "Automated reporting in Word and @code{PowerPoint} can require customization for
each organizational template.  This package works around this by adding standard
reporting functions and an abstraction layer to facilitate automated reporting
workflows that can be replicated across different organizational templates.")
    (license license:bsd-2)))

(define-public r-onboardclient
  (package
    (name "r-onboardclient")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OnboardClient" version))
       (sha256
        (base32 "15ymf163a80s4yvi5z884irvkb1ivnxpr505z96s23hs8ibhk2bh"))))
    (properties `((upstream-name . "OnboardClient")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rstudioapi
                             r-rrapply
                             r-plyr
                             r-lubridate
                             r-jsonlite
                             r-httr
                             r-dplyr
                             r-data-table))
    (home-page "https://cran.r-project.org/package=OnboardClient")
    (synopsis "Bindings for Onboard Data's Building Data API")
    (description
     "This package provides a wrapper for the Onboard Data building data API
<https://api.onboarddata.io/swagger>.  Along with streamlining access to the
API, this package simplifies access to sensor time series data, metadata
(sensors, equipment, and buildings), and details about the Onboard data
model/ontology.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-onbabynames
  (package
    (name "r-onbabynames")
    (version "0.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onbabynames" version))
       (sha256
        (base32 "13sp9gnqnsx2b8dq13qnkin813clnanh6hzv3vi7bxy514pvmisj"))))
    (properties `((upstream-name . "onbabynames")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble))
    (home-page "<https://github.com/desautm/onbabynames>")
    (synopsis "Names Given to Babies in Ontario Between 1917 and 2018")
    (description
     "This package provides a database containing the names of the babies born in
Ontario between 1917 and 2018.  Counts of fewer than 5 names were suppressed for
privacy.")
    (license license:expat)))

(define-public r-onage
  (package
    (name "r-onage")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OnAge" version))
       (sha256
        (base32 "1zby5sf92c185b5m19jv4ndgbv6mz107nc47zn1d6bijrypzpc20"))))
    (properties `((upstream-name . "OnAge")))
    (build-system r-build-system)
    (home-page "https://lbbe.univ-lyon1.fr/OnAge.html")
    (synopsis "Test of Between-Group Differences in the Onset of Senescence")
    (description
     "Implementation of a likelihood ratio test of differential onset of senescence
between two groups.  Given two groups with measures of age and of an individual
trait likely to be subjected to senescence (e.g. body mass), @code{OnAge}
provides an asymptotic p-value for the null hypothesis that senescence starts at
the same age in both groups.  The package implements the procedure used in
Douhard et al. (2017) <doi:10.1111/oik.04421>.")
    (license license:gpl3)))

(define-public r-onadata
  (package
    (name "r-onadata")
    (version "0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "onadata" version))
       (sha256
        (base32 "0l7fqskgqm421mcijmbbb1xgi99y1j673qil5r9whwfdxk78xgqc"))))
    (properties `((upstream-name . "onadata")))
    (build-system r-build-system)
    (home-page "https://ona-book.org")
    (synopsis
     "Data Sets for Keith McNulty's Handbook of Graphs and Networks in People Analytics")
    (description
     "Data sets for network analysis related to People Analytics.  Contains various
data sets from the book Handbook of Graphs and Networks in People Analytics by
Keith @code{McNulty} (2021).")
    (license license:expat)))

(define-public r-omu
  (package
    (name "r-omu")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "omu" version))
       (sha256
        (base32 "19kfk5pcwdkdb41irw9dz34gibhnc8r1amm0mnvk4kbk7y3c1809"))))
    (properties `((upstream-name . "omu")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-stringr
                             r-rstatix
                             r-randomforest
                             r-plyr
                             r-magrittr
                             r-httr
                             r-ggplot2
                             r-ggfortify
                             r-fsa
                             r-dplyr
                             r-caret
                             r-broom))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/connor-reid-tiffany/Omu")
    (synopsis
     "Metabolomics Analysis Tool for Intuitive Figures and Convenient Metadata Collection")
    (description
     "Facilitates the creation of intuitive figures to describe metabolomics data by
utilizing Kyoto Encyclopedia of Genes and Genomes (KEGG) hierarchy data, and
gathers functional orthology and gene data from the KEGG-REST API.")
    (license license:gpl2)))

(define-public r-omsvg
  (package
    (name "r-omsvg")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "omsvg" version))
       (sha256
        (base32 "018sphpmmgpq5alag0il83q51f3r3jx3pnnzjrvg4gn6691nkwvz"))))
    (properties `((upstream-name . "omsvg")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-sass
                             r-rlang
                             r-magrittr
                             r-htmltools
                             r-gt
                             r-dplyr))
    (home-page "https://github.com/rich-iannone/omsvg")
    (synopsis "Build and Transform 'SVG' Objects")
    (description
     "Build SVG components using element-based functions.  With an svg object, we can
modify its graphical elements with a suite of transform functions.")
    (license license:expat)))

(define-public r-ompr-roi
  (package
    (name "r-ompr-roi")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ompr.roi" version))
       (sha256
        (base32 "1w0cyw5ixkri8523vdcfrlaf49farhgdf1bxiizwk5gppb3w5ibl"))))
    (properties `((upstream-name . "ompr.roi")))
    (build-system r-build-system)
    (propagated-inputs (list r-slam r-roi r-ompr r-matrix))
    (home-page "https://github.com/dirkschumacher/ompr.roi")
    (synopsis
     "Solver for 'ompr' that Uses the R Optimization Infrastructure ('ROI')")
    (description
     "This package provides a solver for ompr based on the R Optimization
Infrastructure ('ROI').  The package makes all solvers in ROI available to solve
ompr models.  Please see the ompr website
<https://dirkschumacher.github.io/ompr/> and package docs for more information
and examples on how to use it.")
    (license license:expat)))

(define-public r-ompr
  (package
    (name "r-ompr")
    (version "1.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ompr" version))
       (sha256
        (base32 "02glc09yrdvwls0i8ik1wh6fp3qa9ry55xd3yy3xk0rav8r3hcj3"))))
    (properties `((upstream-name . "ompr")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-matrix
                             r-listcomp
                             r-lazyeval
                             r-fastmap
                             r-data-table))
    (home-page "https://github.com/dirkschumacher/ompr")
    (synopsis "Model and Solve Mixed Integer Linear Programs")
    (description
     "Model mixed integer linear programs in an algebraic way directly in R. The model
is solver-independent and thus offers the possibility to solve a model with
different solvers.  It currently only supports linear constraints and objective
functions.  See the ompr website <https://dirkschumacher.github.io/ompr/> for
more information, documentation and examples.")
    (license license:expat)))

(define-public r-omopsketch
  (package
    (name "r-omopsketch")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OmopSketch" version))
       (sha256
        (base32 "173j68hc6wbr4893sfmjhp2lahkhzvsa058zgny03ryygi42c55v"))))
    (properties `((upstream-name . "OmopSketch")))
    (build-system r-build-system)
    (propagated-inputs (list r-visomopresults
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rlang
                             r-purrr
                             r-patientprofiles
                             r-omopgenerics
                             r-omock
                             r-ggplot2
                             r-dplyr
                             r-cohortconstructor
                             r-cohortcharacteristics
                             r-clock
                             r-cli
                             r-cdmconnector))
    (native-inputs (list r-knitr))
    (home-page "https://OHDSI.github.io/OmopSketch/")
    (synopsis "Characterise Tables of an OMOP Common Data Model Instance")
    (description
     "Summarises key information in data mapped to the Observational Medical Outcomes
Partnership (OMOP) common data model.  Assess suitability to perform specific
epidemiological studies and explore the different domains to obtain feasibility
counts and trends.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-omopgenerics
  (package
    (name "r-omopgenerics")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "omopgenerics" version))
       (sha256
        (base32 "0k98m4ibj4m2rqkirwkqkx91p08adjm3qqj86mhdalp4vhz9x3kg"))))
    (properties `((upstream-name . "omopgenerics")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs
                             r-tidyr
                             r-stringr
                             r-snakecase
                             r-rlang
                             r-purrr
                             r-lifecycle
                             r-glue
                             r-dplyr
                             r-dbplyr
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://darwin-eu-dev.github.io/omopgenerics/")
    (synopsis "Methods and Classes for the OMOP Common Data Model")
    (description
     "This package provides definitions of core classes and methods used by analytic
pipelines that query the OMOP (Observational Medical Outcomes Partnership)
common data model.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-omock
  (package
    (name "r-omock")
    (version "0.3.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "omock" version))
       (sha256
        (base32 "13p5ms9c3lpbc8n2a4vjx6pfayv6pfllspyifxsq53pn9cfm2z6z"))))
    (properties `((upstream-name . "omock")))
    (build-system r-build-system)
    (propagated-inputs (list r-snakecase
                             r-rlang
                             r-purrr
                             r-omopgenerics
                             r-lubridate
                             r-dplyr
                             r-cli))
    (native-inputs (list r-knitr))
    (home-page "https://ohdsi.github.io/omock/")
    (synopsis
     "Creation of Mock Observational Medical Outcomes Partnership Common Data Model")
    (description
     "This package creates mock data for testing and package development for the
Observational Medical Outcomes Partnership common data model.  The package
offers functions crafted with pipeline-friendly implementation, enabling users
to effortlessly include only the necessary tables for their testing needs.")
    (license (license:fsdg-compatible "Apache License (>= 2)"))))

(define-public r-omnibusfisher
  (package
    (name "r-omnibusfisher")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OmnibusFisher" version))
       (sha256
        (base32 "0x3q04g45nixgsrl4biqqi6bk4kx79spq5whm3n4ppr0nkv8dw4h"))))
    (properties `((upstream-name . "OmnibusFisher")))
    (build-system r-build-system)
    (propagated-inputs (list r-survey r-stringr r-compquadform))
    (home-page "https://cran.r-project.org/package=OmnibusFisher")
    (synopsis "Modified Fisherâs Method to Test Overall Gene-Level Effect")
    (description
     "The separate p-values of SNPs, RNA expressions and DNA methylations are
calculated by KM regression.  The correlation between different omics data are
taken into account.  This method can be applied to either samples with all three
types of omics data or samples with two types.")
    (license license:gpl2+)))

(define-public r-omnibus
  (package
    (name "r-omnibus")
    (version "1.2.14")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "omnibus" version))
       (sha256
        (base32 "16lzx1acbl6nbjg21dv2g3n934bvial7nkbbs15pm00aliclws7p"))))
    (properties `((upstream-name . "omnibus")))
    (build-system r-build-system)
    (home-page "https://github.com/adamlilith/omnibus")
    (synopsis
     "Helper Tools for Managing Data, Dates, Missing Values, and Text")
    (description
     "An assortment of helper functions for managing data (e.g., rotating values in
matrices by a user-defined angle, switching from row- to column-indexing), dates
(e.g., intuiting year from messy date strings), handling missing values (e.g.,
removing elements/rows across multiple vectors or matrices if any have an NA),
text (e.g., flushing reports to the console in real-time); and combining data
frames with different schema (copying, filling, or concatenating columns or
applying functions before combining).")
    (license license:gpl3+)))

(define-public r-omisc
  (package
    (name "r-omisc")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Omisc" version))
       (sha256
        (base32 "0p0iraascyx16y05rpc2c9k25s4crc0wrxy58dpj7jd47g2360ar"))))
    (properties `((upstream-name . "Omisc")))
    (build-system r-build-system)
    (propagated-inputs (list r-psych r-mass r-copula))
    (home-page "https://cran.r-project.org/package=Omisc")
    (synopsis "Univariate Bootstrapping and Other Things")
    (description
     "Primarily devoted to implementing the Univariate Bootstrap (as well as the
Traditional Bootstrap).  In addition there are multiple functions for
@code{DeFries-Fulker} behavioral genetics models.  The univariate bootstrapping
functions, @code{DeFries-Fulker} functions, regression and traditional
bootstrapping functions form the original core.  Additional features may come
online later, however this software is a work in progress.  For more information
about univariate bootstrapping see: Lee and Rodgers (1998) and Beasley et al
(2007) <doi:10.1037/1082-989X.12.4.414>.")
    (license license:gpl3)))

(define-public r-omicwas
  (package
    (name "r-omicwas")
    (version "0.8.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "omicwas" version))
       (sha256
        (base32 "03l53vbsard0hpaffcaa9l1aa3nh3w16j00k2jz2jqrrg02z0d7h"))))
    (properties `((upstream-name . "omicwas")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-rlang
                             r-purrr
                             r-matrixstats
                             r-mass
                             r-magrittr
                             r-glmnet
                             r-ff
                             r-dplyr
                             r-data-table
                             r-broom))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/fumi-github/omicwas")
    (synopsis
     "Cell-Type-Specific Association Testing in Bulk Omics Experiments")
    (description
     "In bulk epigenome/transcriptome experiments, molecular expression is measured in
a tissue, which is a mixture of multiple types of cells.  This package tests
association of a disease/phenotype with a molecular marker for each cell type.
The proportion of cell types in each sample needs to be given as input.  The
package is applicable to epigenome-wide association study (EWAS) and
differential gene expression analysis.  Takeuchi and Kato (submitted) \"omicwas:
cell-type-specific epigenome-wide and transcriptome association study\".")
    (license license:gpl3)))

(define-public r-omicstools
  (package
    (name "r-omicstools")
    (version "1.0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "omicsTools" version))
       (sha256
        (base32 "0k6cpdxafz6x5360m97x8mvvi09mb36yx42slkq6nr4axpm089pf"))))
    (properties `((upstream-name . "omicsTools")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-shiny
                             r-readr
                             r-magrittr
                             r-golem
                             r-dt
                             r-dplyr
                             r-config
                             r-bs4dash))
    (home-page "https://github.com/YaoxiangLi/omicsTools")
    (synopsis "Omics Data Process Toolbox")
    (description
     "Processing and analyzing omics data from genomics, transcriptomics, proteomics,
and metabolomics platforms.  It provides functions for preprocessing,
normalization, visualization, and statistical analysis, as well as machine
learning algorithms for predictive modeling. @code{omicsTools} is an essential
tool for researchers working with high-throughput omics data in fields such as
biology, bioinformatics, and medicine.The QC-RLSC (quality controlâbased
robust LOESS signal correction) algorithm is used for normalization.  Dunn et
al. (2011) <doi:10.1038/nprot.2011.335>.")
    (license license:expat)))

(define-public r-omicsqc
  (package
    (name "r-omicsqc")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OmicsQC" version))
       (sha256
        (base32 "1hfdv3cv1ws03x93vah3alpv619dwq40sbl35b2nra3wsix8zcan"))))
    (properties `((upstream-name . "OmicsQC")))
    (build-system r-build-system)
    (propagated-inputs (list r-lsa r-fitdistrplus
                             r-boutroslab-plotting-general))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OmicsQC")
    (synopsis
     "Nominating Quality Control Outliers in Genomic Profiling Studies")
    (description
     "This package provides a method that analyzes quality control metrics from
multi-sample genomic sequencing studies and nominates poor quality samples for
exclusion.  Per sample quality control data are transformed into z-scores and
aggregated.  The distribution of aggregated z-scores are modelled using
parametric distributions.  The parameters of the optimal model, selected either
by goodness-of-fit statistics or user-designation, are used for outlier
nomination.  Two implementations of the Cosine Similarity Outlier Detection
algorithm are provided with flexible parameters for dataset customization.")
    (license license:gpl2)))

(define-public r-omicspls
  (package
    (name "r-omicspls")
    (version "2.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OmicsPLS" version))
       (sha256
        (base32 "08vx4925j5ln366h7nzhf1ra5ciplrqw911258chi9di7gpm8g50"))))
    (properties `((upstream-name . "OmicsPLS")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-softimpute r-magrittr r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OmicsPLS")
    (synopsis "Data Integration with Two-Way Orthogonal Partial Least Squares")
    (description
     "This package performs the O2PLS data integration method for two datasets,
yielding joint and data-specific parts for each dataset.  The algorithm
automatically switches to a memory-efficient approach to fit O2PLS to high
dimensional data.  It provides a rigorous and a faster alternative
cross-validation method to select the number of components, as well as functions
to report proportions of explained variation and to construct plots of the
results.  See the software article by el Bouhaddani et al (2018)
<doi:10.1186/s12859-018-2371-3>, and Trygg and Wold (2003)
<doi:10.1002/cem.775>.  It also performs Sparse Group (Penalized) O2PLS, see Gu
et al (2020) <doi:10.1186/s12859-021-03958-3> and cross-validation for the
degree of sparsity.")
    (license license:gpl3)))

(define-public r-omicsense
  (package
    (name "r-omicsense")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OmicSense" version))
       (sha256
        (base32 "0nac0ahciyajsicrs4rkn54xiwgvdm4m2kbg6icbsygwzzp2w14z"))))
    (properties `((upstream-name . "OmicSense")))
    (build-system r-build-system)
    (propagated-inputs (list r-kernlab r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "<https://github.com/takakoizumi/OmicSense>")
    (synopsis "Biosensor Development using Omics Data")
    (description
     "This package provides a method for the quantitative prediction using omics data.
 This package provides functions to construct the quantitative prediction model
using omics data.")
    (license license:gpl3+)))

(define-public r-omics
  (package
    (name "r-omics")
    (version "0.1-5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "omics" version))
       (sha256
        (base32 "1y2x33mfgq98nglhvpr1wq1v6nfiq4njy2yac47x72rpwxsj9vb1"))))
    (properties `((upstream-name . "omics")))
    (build-system r-build-system)
    (propagated-inputs (list r-pheatmap r-lme4))
    (home-page "https://cran.r-project.org/package=omics")
    (synopsis "'--omics' Data Analysis Toolbox")
    (description
     "This package provides a collection of functions to analyse --omics datasets such
as DNA methylation and gene expression profiles.")
    (license license:gpl2+)))

(define-public r-omicnavigator
  (package
    (name "r-omicnavigator")
    (version "1.13.13")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OmicNavigator" version))
       (sha256
        (base32 "0dfc3v5n7sms0fjgm8g0f1r810q139378ha0i86hv1s88psxy08x"))))
    (properties `((upstream-name . "OmicNavigator")))
    (build-system r-build-system)
    (propagated-inputs (list r-jsonlite r-data-table))
    (home-page "https://github.com/abbvie-external/OmicNavigator")
    (synopsis
     "Open-Source Software for 'Omic' Data Analysis and Visualization")
    (description
     "This package provides a tool for interactive exploration of the results from
omics experiments to facilitate novel discoveries from high-throughput biology.
The software includes R functions for the bioinformatician to deposit study
metadata and the outputs from statistical analyses (e.g. differential
expression, enrichment).  These results are then exported to an interactive
@code{JavaScript} dashboard that can be interrogated on the user's local machine
or deployed online to be explored by collaborators.  The dashboard includes
sortable tables, interactive plots including network visualization, and
fine-grained filtering based on statistical significance.")
    (license license:expat)))

(define-public r-omickriging
  (package
    (name "r-omickriging")
    (version "1.4.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OmicKriging" version))
       (sha256
        (base32 "08frr38yf5d0l3zwkbq9465xrbyzsn8sx9icqc3yvfnxrkhrpzig"))))
    (properties `((upstream-name . "OmicKriging")))
    (build-system r-build-system)
    (propagated-inputs (list r-rocr r-irlba r-foreach r-doparallel))
    (home-page "https://cran.r-project.org/package=OmicKriging")
    (synopsis "Poly-Omic Prediction of Complex TRaits")
    (description
     "It provides functions to generate a correlation matrix from a genetic dataset
and to use this matrix to predict the phenotype of an individual by using the
phenotypes of the remaining individuals through kriging.  Kriging is a
geostatistical method for optimal prediction or best unbiased linear prediction.
 It consists of predicting the value of a variable at an unobserved location as
a weighted sum of the variable at observed locations.  Intuitively, it works as
a reverse linear regression: instead of computing correlation (univariate
regression coefficients are simply scaled correlation) between a dependent
variable Y and independent variables X, it uses known correlation between X and
Y to predict Y.")
    (license license:gpl3+)))

(define-public r-omegag
  (package
    (name "r-omegag")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OmegaG" version))
       (sha256
        (base32 "1aihcrgml67rvnx9vpnq2nnbc79kicw4ks1fradsa36ykkdz6b1g"))))
    (properties `((upstream-name . "OmegaG")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=OmegaG")
    (synopsis
     "Omega-Generic: Composite Reliability of Multidimensional Measures")
    (description
     "It is a computer tool to estimate the item-sum score's reliability (composite
reliability, CR) in multidimensional scales with overlapping items.  An item
that measures more than one domain construct is called an overlapping item.  The
estimation is based on factor models allowing unlimited cross-factor loadings
such as exploratory structural equation modeling (ESEM) and Bayesian structural
equation modeling (BSEM).  The factor models include correlated-factor models
and bi-factor models.  Specifically for bi-factor models, a type of hierarchical
factor model, the package estimates the CR hierarchical subscale/hierarchy and
CR subscale/scale total.  The CR estimator Omega-generic was proposed by Mai,
Srivastava, and Krull (2021)
<https://whova.com/embedded/subsession/enars_202103/1450751/1452993/>.  The
current version can only handle continuous data.  Yujiao Mai contributes to the
algorithms, R programming, and application example.  Deo Kumar Srivastava
contributes to the algorithms and the application example.  Kevin R. Krull
contributes to the application example.  The package @code{OmegaG} was sponsored
by American Lebanese Syrian Associated Charities (ALSAC).  However, the contents
of @code{OmegaG} do not necessarily represent the policy of the ALSAC.")
    (license license:gpl2)))

(define-public r-olympicrshiny
  (package
    (name "r-olympicrshiny")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OlympicRshiny" version))
       (sha256
        (base32 "1pal80qcj8jb0a0yd95qb56mkm99m9kyfcn44d63k769hkfx43fi"))))
    (properties `((upstream-name . "OlympicRshiny")))
    (build-system r-build-system)
    (propagated-inputs (list r-summarytools
                             r-shinythemes
                             r-shinybusy
                             r-shiny
                             r-golem
                             r-ggplot2
                             r-forcats
                             r-dplyr
                             r-config))
    (home-page "https://github.com/Amalan-ConStat/OlympicRshiny")
    (synopsis "'Shiny' Application for Olympic Data")
    (description
     "Shiny Application to visualize Olympic Data.  From 1896 to 2016.  Even Winter
Olympics events are included.  Data is from Kaggle at
<https://www.kaggle.com/heesoo37/120-years-of-olympic-history-athletes-and-results>.")
    (license license:expat)))

(define-public r-olstrajr
  (package
    (name "r-olstrajr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OLStrajr" version))
       (sha256
        (base32 "1ln2as15aay4hzdm82yc024dlv7wdip9l5dryrdhkmmhjy026gia"))))
    (properties `((upstream-name . "OLStrajr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-purrr
                             r-ggplot2
                             r-broom
                             r-boot))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mightymetrika/OLStrajr")
    (synopsis "Ordinary Least Squares Trajectory Analysis")
    (description
     "The OLStrajr package provides comprehensive functions for ordinary least squares
(OLS) trajectory analysis and case-by-case OLS regression as outlined in Carrig,
Wirth, and Curran (2004) <doi:10.1207/S15328007SEM1101_9> and Rogosa and Saner
(1995) <doi:10.3102/10769986020002149>.  It encompasses two primary functions,
OLStraj() and cbc_lm().  The OLStraj() function simplifies the estimation of
individual growth curves over time via OLS regression, with options for
visualizing both group-level and individual-level growth trajectories and
support for linear and quadratic models.  The cbc_lm() function facilitates
case-by-case OLS estimates and provides unbiased mean population intercept and
slope estimators by averaging OLS intercepts and slopes across cases.  It
further offers standard error calculations across bootstrap replicates and
computation of 95% confidence intervals based on empirical distributions from
the resampling processes.")
    (license license:expat)))

(define-public r-olsrr
  (package
    (name "r-olsrr")
    (version "0.6.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "olsrr" version))
       (sha256
        (base32 "1jnp7dirjgg49v958fwcmcz1nalkgmr15kr4pqbxylmi45bqkqr6"))))
    (properties `((upstream-name . "olsrr")))
    (build-system r-build-system)
    (propagated-inputs (list r-xplorerr
                             r-nortest
                             r-gridextra
                             r-goftest
                             r-ggplot2
                             r-car))
    (native-inputs (list r-knitr))
    (home-page "https://olsrr.rsquaredacademy.com/")
    (synopsis "Tools for Building OLS Regression Models")
    (description
     "This package provides tools designed to make it easier for users, particularly
beginner/intermediate R users to build ordinary least squares regression models.
 Includes comprehensive regression output, heteroskedasticity tests,
collinearity diagnostics, residual diagnostics, measures of influence, model fit
assessment and variable selection procedures.")
    (license license:expat)))

(define-public r-olr
  (package
    (name "r-olr")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "olr" version))
       (sha256
        (base32 "1l6m2gbglh8idy4k2q23qgfb7in1a6pnwiji1gbygfan6paw4xza"))))
    (properties `((upstream-name . "olr")))
    (build-system r-build-system)
    (propagated-inputs (list r-plyr))
    (home-page "https://github.com/MatHatter")
    (synopsis "Optimal Linear Regression")
    (description
     "The optimal linear regression olr(), runs all the possible combinations of
linear regression equations.  The olr() returns the equation which has the
greatest adjusted R-squared term or the greatest R-squared term based on the
user's discretion.  Essentially, the olr() returns the best fit equation out of
all the possible equations.  R-squared increases with the addition of an
explanatory variable whether it is significant or not, thus this was developed
to eliminate that conundrum.  Adjusted R-squared is preferred to overcome this
phenomenon, but each combination will still produce different results and this
will return the best one.  Complimentary functions are included which list all
of the equations, all of the equations in ascending order, a function to give
the user a specific model's summary, and the list of adjusted R-squared terms &
R-squared terms.  A Python version is available at:
<https://pypi.org/project/olr/>.")
    (license license:gpl3)))

(define-public r-ollggamma
  (package
    (name "r-ollggamma")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ollggamma" version))
       (sha256
        (base32 "1990hr9gww636xr4gkvc816hd0pc78nw3ypbzflkh5g3pmsn7bc2"))))
    (properties `((upstream-name . "ollggamma")))
    (build-system r-build-system)
    (home-page "https://mjsaldanha.com/posts/ollggamma")
    (synopsis "Odd Log-Logistic Generalized Gamma Probability Distribution")
    (description
     "Density, distribution function, quantile function and random generation for the
Odd Log-Logistic Generalized Gamma proposed in Prataviera, F. et al (2017)
<doi:10.1080/00949655.2016.1238088>.")
    (license license:expat)))

(define-public r-ollg
  (package
    (name "r-ollg")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ollg" version))
       (sha256
        (base32 "1xjfn3hlmmx65kphchhxqa9fx6qmkiyx24lp19si1y3v92wdv2i9"))))
    (properties `((upstream-name . "ollg")))
    (build-system r-build-system)
    (home-page "https://github.com/dmazarei/ollg")
    (synopsis "Computes some Measures of OLL-G Family of Distributions")
    (description
     "Computes the pdf, cdf, quantile function, hazard function and generating random
numbers for Odd log-logistic family (OLL-G).  This family have been developed by
different authors in the recent years.  See Alizadeh (2019)
<doi:10.31801/cfsuasmas.542988> for example.")
    (license license:gpl2+)))

(define-public r-ollamar
  (package
    (name "r-ollamar")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ollamar" version))
       (sha256
        (base32 "0l9k84hf5y46ci6l2sy1zi3423akip2jr0zi8cnjh337dfww9sis"))))
    (properties `((upstream-name . "ollamar")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-jsonlite
                             r-httr2
                             r-glue
                             r-crayon
                             r-base64enc))
    (home-page "https://hauselin.github.io/ollama-r/")
    (synopsis "'Ollama' Language Models")
    (description
     "An interface to easily run local language models with Ollama
<https://ollama.com> server and API endpoints (see
<https://github.com/ollama/ollama/blob/main/docs/api.md> for details).  It lets
you run open-source large language models locally on your machine.")
    (license license:expat)))

(define-public r-olinkanalyze
  (package
    (name "r-olinkanalyze")
    (version "4.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OlinkAnalyze" version))
       (sha256
        (base32 "0xb7dg4ncqvypl27rb8s05ck1zjxs2j49f4lnpl3hqjvh0da6p3x"))))
    (properties `((upstream-name . "OlinkAnalyze")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyselect
                             r-tidyr
                             r-tibble
                             r-stringr
                             r-rstatix
                             r-rlang
                             r-readxl
                             r-magrittr
                             r-ggrepel
                             r-ggpubr
                             r-ggplot2
                             r-generics
                             r-forcats
                             r-emmeans
                             r-dplyr
                             r-data-table
                             r-cli
                             r-car
                             r-broom))
    (native-inputs (list r-knitr r-kableextra))
    (home-page "https://cran.r-project.org/package=OlinkAnalyze")
    (synopsis "Facilitate Analysis of Proteomic Data from Olink")
    (description
     "This package provides a collection of functions to facilitate analysis of
proteomic data from Olink, primarily NPX data that has been exported from Olink
Software.  The functions also work on QUANT data from Olink by log- transforming
the QUANT data.  The functions are focused on reading data, facilitating data
wrangling and quality control analysis, performing statistical analysis and
generating figures to visualize the results of the statistical analysis.  The
goal of this package is to help users extract biological insights from proteomic
data run on the Olink platform.")
    (license license:agpl3+)))

(define-public r-olctools
  (package
    (name "r-olctools")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "olctools" version))
       (sha256
        (base32 "1gbchwynvmryarz32f24v56kj57h7x6nrrm878fkjkpq140cqwzz"))))
    (properties `((upstream-name . "olctools")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/Ironholds/olctools")
    (synopsis "Open Location Code Handling in R")
    (description
     "Open Location Codes <http://openlocationcode.com/> are a Google-created standard
for identifying geographic locations.  olctools provides utilities for
validating, encoding and decoding entries that follow this standard.")
    (license license:expat)))

(define-public r-olcpm
  (package
    (name "r-olcpm")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OLCPM" version))
       (sha256
        (base32 "0w60w1qhq8sbcaqk56kf4cgn51fm8zjmxdm42imn5c05m06pc8k0"))))
    (properties `((upstream-name . "OLCPM")))
    (build-system r-build-system)
    (propagated-inputs (list r-rspectra r-laplacesdemon))
    (home-page "https://cran.r-project.org/package=OLCPM")
    (synopsis "Online Change Point Detection for Matrix-Valued Time Series")
    (description
     "We provide two algorithms for monitoring change points with online matrix-valued
time series, under the assumption of a two-way factor structure.  The algorithms
are based on different calculations of the second moment matrices.  One is based
on stacking the columns of matrix observations, while another is by a more
delicate projected approach.  A well-known fact is that, in the presence of a
change point, a factor model can be rewritten as a model with a larger number of
common factors.  In turn, this entails that, in the presence of a change point,
the number of spiked eigenvalues in the second moment matrix of the data
increases.  Based on this, we propose two families of procedures - one based on
the fluctuations of partial sums, and one based on extreme value theory - to
monitor whether the first non-spiked eigenvalue diverges after a point in time
in the monitoring horizon, thereby indicating the presence of a change point.
This package also provides some simple functions for detecting and removing
outliers, imputing missing entries and testing moments.  See more details in He
et al. (2021)<doi:10.48550/@code{arXiv.2112.13479>}.")
    (license (list license:gpl2 license:gpl3))))

(define-public r-okxapi
  (package
    (name "r-okxapi")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "okxAPI" version))
       (sha256
        (base32 "0wysfpkij9l265clw6qi4zpr1c860idxfp82xz2nmy1l5b2n8ri0"))))
    (properties `((upstream-name . "okxAPI")))
    (build-system r-build-system)
    (propagated-inputs (list r-websocket
                             r-r6
                             r-jsonlite
                             r-httr
                             r-digest
                             r-data-table
                             r-base64enc))
    (home-page "https://cran.r-project.org/package=okxAPI")
    (synopsis "An Unofficial Wrapper for 'okx exchange v5' API")
    (description
     "An unofficial wrapper for okx exchange v5 API <https://www.okx.com/docs-v5/en/>,
including REST API and @code{WebSocket} API.")
    (license license:expat)))

(define-public r-oknne
  (package
    (name "r-oknne")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OkNNE" version))
       (sha256
        (base32 "10kkg6n6fsqm1kir1ay96br1m8adykarmp57bnw900fiblqqa2i0"))))
    (properties `((upstream-name . "OkNNE")))
    (build-system r-build-system)
    (propagated-inputs (list r-fnn))
    (home-page "https://cran.r-project.org/package=OkNNE")
    (synopsis
     "k-Nearest Neighbours Ensemble via Optimal Model Selection for Regression")
    (description
     "Optimal k Nearest Neighbours Ensemble is an ensemble of base k nearest neighbour
models each constructed on a bootstrap sample with a random subset of features.
k closest observations are identified for a test point \"x\" (say), in each base k
nearest neighbour model to fit a stepwise regression to predict the output value
of \"x\".  The final predicted value of \"x\" is the mean of estimates given by all
the models.  The implemented model takes training and test datasets and trains
the model on training data to predict the test data.  Ali, A., Hamraz, M.,
Kumam, P., Khan, D.M., Khalil, U., Sulaiman, M. and Khan, Z. (2020)
<DOI:10.1109/ACCESS.2020.3010099>.")
    (license license:gpl3+)))

(define-public r-ojsr
  (package
    (name "r-ojsr")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ojsr" version))
       (sha256
        (base32 "0nwdws9kqnya9qjc939b7ksrf7ri6d25zzcdxhyhabirhnrqdg7m"))))
    (properties `((upstream-name . "ojsr")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2
                             r-urltools
                             r-tidyr
                             r-rvest
                             r-rlang
                             r-purrr
                             r-magrittr
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ojsr")
    (synopsis "Crawler and Data Scraper for Open Journal System ('OJS')")
    (description
     "Crawler for OJS pages and scraper for meta-data from articles.  You can crawl
OJS archives, issues, articles, galleys, and search results.  You can scrape
articles metadata from their head tag in html, or from Open Archives Initiative
('OAI') records.  Most of these functions rely on OJS routing conventions
(<https://docs.pkp.sfu.ca/dev/documentation/en/architecture-routes>).")
    (license license:gpl3)))

(define-public r-oii
  (package
    (name "r-oii")
    (version "1.0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oii" version))
       (sha256
        (base32 "1n41hikn53ikyynsravg127cw5csa8s0s1l63w5hym7c6j625ya5"))))
    (properties `((upstream-name . "oii")))
    (build-system r-build-system)
    (propagated-inputs (list r-rapportools r-gmodels r-deducer))
    (home-page "https://cran.r-project.org/package=oii")
    (synopsis "Crosstab and Statistical Tests for OII MSc Stats Course")
    (description
     "This package provides simple crosstab output with optional statistics (e.g.,
Goodman-Kruskal Gamma, Somers d, and Kendall's tau-b) as well as two-way and
one-way tables.  The package is used within the statistics component of the
Masters of Science (MSc) in Social Science of the Internet at the Oxford
Internet Institute (OII), University of Oxford, but the functions should be
useful for general data analysis and especially for analysis of categorical and
ordinal data.")
    (license license:expat)))

(define-public r-ohun
  (package
    (name "r-ohun")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ohun" version))
       (sha256
        (base32 "0l3c6p1q2mjvr03q905ygmaax94bn3a0fkfn8kfjr6d5bs60283s"))))
    (properties `((upstream-name . "ohun")))
    (build-system r-build-system)
    (propagated-inputs (list r-warbler
                             r-tuner
                             r-sf
                             r-seewave
                             r-rlang
                             r-igraph
                             r-ggplot2
                             r-fftw
                             r-cli
                             r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://docs.ropensci.org/ohun/")
    (synopsis "Optimizing Acoustic Signal Detection")
    (description
     "Facilitates the automatic detection of acoustic signals, providing functions to
diagnose and optimize the performance of detection routines.  Detections from
other software can also be explored and optimized.  This package has been
peer-reviewed by @code{rOpenSci}.  Araya-Salas et al. (2022)
<doi:10.1101/2022.12.13.520253>.")
    (license license:gpl2+)))

(define-public r-ohtadstats
  (package
    (name "r-ohtadstats")
    (version "2.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ohtadstats" version))
       (sha256
        (base32 "0hkjs322vii1dsminlkwpwi12sc9pd88jag7p4dmy6nfw2hh2d69"))))
    (properties `((upstream-name . "ohtadstats")))
    (build-system r-build-system)
    (propagated-inputs (list r-lattice))
    (home-page "https://github.com/pfpetrowski/OhtaDStats")
    (synopsis "Tomoka Ohta D Statistics")
    (description
     "Calculate's Tomoka Ohta's partitioning of linkage disequilibrium, deemed
D-statistics, for pairs of loci.  Petrowski et al. (2019)
<doi:10.5334/jors.250>.")
    (license license:expat)))

(define-public r-ohsome
  (package
    (name "r-ohsome")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ohsome" version))
       (sha256
        (base32 "0zw4r1sv46mfxzbp620a00wsh9i1dc21lmf1iadsdm4iss8pjk44"))))
    (properties `((upstream-name . "ohsome")))
    (build-system r-build-system)
    (propagated-inputs (list r-sf r-readr r-jsonlite r-httr r-geojsonsf))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/GIScience/ohsome-r")
    (synopsis "An 'ohsome API' Client")
    (description
     "This package provides a client that grants access to the power of the ohsome API
from R. It lets you analyze the rich data source of the @code{OpenStreetMap}
(OSM) history.  You can retrieve the geometry of OSM data at specific points in
time, and you can get aggregated statistics on the evolution of OSM elements and
specify your own temporal, spatial and/or thematic filters.")
    (license license:lgpl3+)))

(define-public r-ohpl
  (package
    (name "r-ohpl")
    (version "1.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OHPL" version))
       (sha256
        (base32 "1bcg97lgjs00xka2k5k8kdnc42vz10g78cb9mh5jz2g58iamjzbk"))))
    (properties `((upstream-name . "OHPL")))
    (build-system r-build-system)
    (propagated-inputs (list r-pls r-mvtnorm r-glmnet))
    (home-page "https://ohpl.io")
    (synopsis "Ordered Homogeneity Pursuit Lasso for Group Variable Selection")
    (description
     "Ordered homogeneity pursuit lasso (OHPL) algorithm for group variable selection
proposed in Lin et al. (2017) <DOI:10.1016/j.chemolab.2017.07.004>.  The OHPL
method exploits the homogeneity structure in high-dimensional data and enjoys
the grouping effect to select groups of important variables automatically.  This
feature makes it particularly useful for high-dimensional datasets with strongly
correlated variables, such as spectroscopic data.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-ohoegdm
  (package
    (name "r-ohoegdm")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ohoegdm" version))
       (sha256
        (base32 "1p1jica3fr4a5ilz1m2gxyzbapxjvgiw4v5rn90d5qgsmbp1hj42"))))
    (properties `((upstream-name . "ohoegdm")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo r-rcpp))
    (home-page "https://github.com/tmsalab/ohoegdm")
    (synopsis
     "Ordinal Higher-Order Exploratory General Diagnostic Model for Polytomous Data")
    (description
     "Perform a Bayesian estimation of the ordinal exploratory Higher-order General
Diagnostic Model (OHOEGDM) for Polytomous Data described by Culpepper, S. A. and
Balamuta, J. J. (In Press) <doi:10.1080/00273171.2021.1985949>.")
    (license license:gpl2+)))

(define-public r-ohmmed
  (package
    (name "r-ohmmed")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oHMMed" version))
       (sha256
        (base32 "09ii42791qyfzc641906k92p5nd8r162jji3fxjdidw2ncwnnn8b"))))
    (properties `((upstream-name . "oHMMed")))
    (build-system r-build-system)
    (propagated-inputs (list r-vcd
                             r-scales
                             r-mistr
                             r-gridextra
                             r-ggplot2
                             r-ggmcmc
                             r-cvms))
    (home-page "https://github.com/LynetteCaitlin/oHMMed")
    (synopsis "HMMs with Ordered Hidden States and Emission Densities")
    (description
     "Inference using a class of Hidden Markov models (HMMs) called
@code{oHMMed'(ordered} HMM with emission densities
<doi:10.1186/s12859-024-05751-4>): The @code{oHMMed} algorithms identify the
number of comparably homogeneous regions within observed sequences with
autocorrelation patterns.  These are modelled as discrete hidden states; the
observed data points are then realisations of continuous probability
distributions with state-specific means that enable ordering of these
distributions.  The observed sequence is labelled according to the hidden
states, permitting only neighbouring states that are also neighbours within the
ordering of their associated distributions.  The parameters that characterise
these state-specific distributions are then inferred.  Relevant for application
to genomic sequences, time series, or any other sequence data with serial
autocorrelation.")
    (license license:gpl3)))

(define-public r-ohit
  (package
    (name "r-ohit")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Ohit" version))
       (sha256
        (base32 "132d4drc2phw9ppxnczb1ycdg3dv085k8p6bcaj3v866j0hfxjgb"))))
    (properties `((upstream-name . "Ohit")))
    (build-system r-build-system)
    (home-page "http://mx.nthu.edu.tw/~cking/pdf/IngLai2011.pdf")
    (synopsis "OGA+HDIC+Trim and High-Dimensional Linear Regression Models")
    (description
     "Ing and Lai (2011) <doi:10.5705/ss.2010.081> proposed a high-dimensional model
selection procedure that comprises three steps: orthogonal greedy algorithm
(OGA), high-dimensional information criterion (HDIC), and Trim.  The first two
steps, OGA and HDIC, are used to sequentially select input variables and
determine stopping rules, respectively.  The third step, Trim, is used to delete
irrelevant variables remaining in the second step.  This package aims at fitting
a high-dimensional linear regression model via OGA+HDIC+Trim.")
    (license license:gpl2)))

(define-public r-ohenery
  (package
    (name "r-ohenery")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ohenery" version))
       (sha256
        (base32 "0i7cc110c30y7dm86srh2xkikkmlr28mvy0kkjxywxmiwnrsmzjq"))))
    (properties `((upstream-name . "ohenery")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-maxlik r-magrittr r-dplyr))
    (home-page "https://github.com/shabbychef/ohenery")
    (synopsis "Modeling of Ordinal Random Variables via Softmax Regression")
    (description
     "Supports the modeling of ordinal random variables, like the outcomes of races,
via Softmax regression, under the Harville <doi:10.1080/01621459.1973.10482425>
and Henery <doi:10.1111/j.2517-6161.1981.tb01153.x> models.")
    (license license:lgpl3)))

(define-public r-ohcspackage
  (package
    (name "r-ohcspackage")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OHCSpackage" version))
       (sha256
        (base32 "0dr2yxz9amqq9mpl8skhdvs7w01zc4y3sw4wqs0iwj1pj9jb96fz"))))
    (properties `((upstream-name . "OHCSpackage")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble r-readr r-openxlsx r-dplyr))
    (home-page "https://cran.r-project.org/package=OHCSpackage")
    (synopsis "Prepare Housing Data for Analysis")
    (description
     "Prepares census and core housing needs data, specifically designed for use with
Statistics Canada data and standardized input data.  The package offers
functions for tidying, organizing, and splitting complex data tables, making it
easier for users to perform analyses on the data.  OHCSpackage is particularly
useful for those working with census data that has a consistent format, number
of rows, and number of columns.  With this package, users can save time and
streamline their data preparation processes.")
    (license license:gpl3)))

(define-public r-ogrdbstats
  (package
    (name "r-ogrdbstats")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ogrdbstats" version))
       (sha256
        (base32 "140i4wippqr1260a1c4syg6lfspkf9q8rifnalf6iaaqx2bz4yfq"))))
    (properties `((upstream-name . "ogrdbstats")))
    (build-system r-build-system)
    (propagated-inputs (list r-tigger
                             r-tidyr
                             r-stringr
                             r-stringdist
                             r-scales
                             r-rcolorbrewer
                             r-magrittr
                             r-gridextra
                             r-ggplot2
                             r-dplyr
                             r-data-table
                             r-complexheatmap
                             r-bookdown
                             r-biostrings
                             r-argparser
                             r-alakazam))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/airr-community/ogrdbstats")
    (synopsis
     "Analysis of Adaptive Immune Receptor Repertoire Germ Line Statistics")
    (description
     "Multiple tools are now available for inferring the personalised germ line set
from an adaptive immune receptor repertoire.  Output from these tools is
converted to a single format and supplemented with rich data such as usage and
characterisation of novel germ line alleles.  This data can be particularly
useful when considering the validity of novel inferences.  Use of the analysis
provided is described in <doi:10.3389/fimmu.2019.00435>.")
    (license license:cc-by-sa4.0)))

(define-public r-oglmx
  (package
    (name "r-oglmx")
    (version "3.0.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oglmx" version))
       (sha256
        (base32 "13axmhbqhv4kkcdsdmp9r7p0d0kyqlsaqgyyllbkxlxb4hfz79b6"))))
    (properties `((upstream-name . "oglmx")))
    (build-system r-build-system)
    (propagated-inputs (list r-maxlik))
    (home-page "https://cran.r-project.org/package=oglmx")
    (synopsis "Estimation of Ordered Generalized Linear Models")
    (description
     "Ordered models such as ordered probit and ordered logit presume that the error
variance is constant across observations.  In the case that this assumption does
not hold estimates of marginal effects are typically biased (Weiss (1997)).
This package allows for generalization of ordered probit and ordered logit
models by allowing the user to specify a model for the variance.  Furthermore,
the package includes functions to calculate the marginal effects.  Wrapper
functions to estimate the standard limited dependent variable models are also
included.")
    (license license:gpl2)))

(define-public r-oglcnac
  (package
    (name "r-oglcnac")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oglcnac" version))
       (sha256
        (base32 "1r8agkpfkvr6ix6286dap4489pq3ym8maqigkhwby83l2p3s30c1"))))
    (properties `((upstream-name . "oglcnac")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny
                             r-readxl
                             r-jsonlite
                             r-httr
                             r-glue
                             r-dt
                             r-cli
                             r-bslib))
    (home-page "https://cran.r-project.org/package=oglcnac")
    (synopsis "Processing and Analysis of O-GlcNAcAtlas Data")
    (description
     "This package provides tools for processing and analyzing data from the
O-@code{GlcNAcAtlas} database <https://oglcnac.org/>, as described in Ma (2021)
<doi:10.1093/glycob/cwab003>.  It integrates @code{UniProt}
<https://www.uniprot.org/> API calls to retrieve additional information.  It is
specifically designed for research workflows involving O-@code{GlcNAcAtlas}
data, providing a flexible and user-friendly interface for customizing and
downloading processed results.  Interactive elements allow users to easily
adjust parameters and handle various biological datasets.")
    (license license:gpl2)))

(define-public r-ogi
  (package
    (name "r-ogi")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OGI" version))
       (sha256
        (base32 "0qw55jamkvdf3vfa5c0ygbymbs4d9q15dihiqz691hdfnyjvc2mk"))))
    (properties `((upstream-name . "OGI")))
    (build-system r-build-system)
    (propagated-inputs (list r-lpsolve))
    (home-page "https://cran.r-project.org/package=OGI")
    (synopsis "Objective General Index")
    (description
     "Consider a data matrix of n individuals with p variates.  The objective general
index (OGI) is a general index that combines the p variates into a univariate
index in order to rank the n individuals.  The OGI is always positively
correlated with each of the variates.  More details can be found in Sei (2016)
<doi:10.1016/j.jmva.2016.02.005>.")
    (license license:gpl3)))

(define-public r-ofpetrial
  (package
    (name "r-ofpetrial")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ofpetrial" version))
       (sha256
        (base32 "1wid8d4m8bk087z8fi4ls493p1g30cymyl5xcbzcv0an2rkd739j"))))
    (properties `((upstream-name . "ofpetrial")))
    (build-system r-build-system)
    (propagated-inputs (list r-zip
                             r-tmap
                             r-tidyr
                             r-tibble
                             r-terra
                             r-sf
                             r-rmarkdown
                             r-purrr
                             r-magrittr
                             r-lwgeom
                             r-leaflet
                             r-ggpubr
                             r-ggplot2
                             r-ggextra
                             r-dplyr
                             r-data-table
                             r-bookdown))
    (native-inputs (list r-knitr))
    (home-page "https://difm-brain.github.io/ofpetrial/")
    (synopsis "Design on-Farm Precision Field Agronomic Trials")
    (description
     "This package provides a comprehensive system for designing and implementing
on-farm precision field agronomic trials.  You provide field data, tell
ofpetrial how to design a trial, and get readily-usable trial design files and a
report checks the validity and reliability of the trial design.")
    (license license:gpl3+)))

(define-public r-ofgem
  (package
    (name "r-ofgem")
    (version "1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ofGEM" version))
       (sha256
        (base32 "0xdkl8k12an9pdy6i5nay4m2iakrwsp0lr3zl8gphii75j0ywz7k"))))
    (properties `((upstream-name . "ofGEM")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass r-forestplot r-compquadform))
    (home-page "https://github.com/randel/ofGEM")
    (synopsis
     "Meta-Analysis Approach with Filtering for Identifying Gene-Level Gene-Environment Interactions with Genetic Association Data")
    (description
     "Offers a gene-based meta-analysis test with filtering to detect gene-environment
interactions (@code{GxE}) with association data, proposed by Wang et al. (2018)
<doi:10.1002/gepi.22115>.  It first conducts a meta-filtering test to filter out
unpromising SNPs by combining all samples in the consortia data.  It then runs a
test of omnibus-filtering-based @code{GxE} meta-analysis (@code{ofGEM}) that
combines the strengths of the fixed- and random-effects meta-analysis with
meta-filtering.  It can also analyze data from multiple ethnic groups.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-offsetreg
  (package
    (name "r-offsetreg")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "offsetreg" version))
       (sha256
        (base32 "1nxiaz5p3s4i3dxl3cph5c8aily3d6g212086wrxy38jyqk55xkm"))))
    (properties `((upstream-name . "offsetreg")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-poissonreg r-parsnip r-glue r-generics))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mattheaphy/offsetreg/")
    (synopsis "An Extension of 'Tidymodels' Supporting Offset Terms")
    (description
     "Extend the tidymodels ecosystem <https://www.tidymodels.org/> to enable the
creation of predictive models with offset terms.  Models with offsets are most
useful when working with count data or when fitting an adjustment model on top
of an existing model with a prior expectation.  The former situation is common
in insurance where data is often weighted by exposures.  The latter is common in
life insurance where industry mortality tables are often used as a starting
point for setting assumptions.")
    (license license:expat)))

(define-public r-offlinechange
  (package
    (name "r-offlinechange")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "offlineChange" version))
       (sha256
        (base32 "005afrm4ki4zz3zkgrf8c1v9gf5cjhc5g50mjkqya3r8npaccwq2"))))
    (properties `((upstream-name . "offlineChange")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=offlineChange")
    (synopsis "Detect Multiple Change Points from Time Series")
    (description
     "Detect the number and locations of change points.  The locations can be either
exact or in terms of ranges, depending on the available computational resource.
The method is based on Jie Ding, Yu Xiang, Lu Shen, Vahid Tarokh (2017)
<doi:10.1109/TSP.2017.2711558>.")
    (license license:gpl3)))

(define-public r-officedown
  (package
    (name "r-officedown")
    (version "0.3.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "officedown" version))
       (sha256
        (base32 "0mxg46jg4vb6bxxqayvf84g8bllwsf11ybkfinrsdzdlkw89s3vk"))))
    (properties `((upstream-name . "officedown")))
    (build-system r-build-system)
    (propagated-inputs (list r-yaml
                             r-xml2
                             r-uuid
                             r-rvg
                             r-rmarkdown
                             r-rlang
                             r-officer
                             r-memoise
                             r-knitr))
    (native-inputs (list r-knitr))
    (home-page "https://ardata-fr.github.io/officeverse/")
    (synopsis "Enhanced 'R Markdown' Format for 'Word' and 'PowerPoint'")
    (description
     "Allows production of Microsoft corporate documents from R Markdown by reusing
formatting defined in Microsoft Word documents.  You can reuse table styles,
list styles but also add column sections, landscape oriented pages.  Table and
image captions as well as cross-references are transformed into Microsoft Word
fields, allowing documents edition and merging without issue with references;
the syntax conforms to the bookdown cross-reference definition.  Objects
generated by the officer package are also supported in the knitr chunks.
Microsoft @code{PowerPoint} presentations also benefit from this as well as the
ability to produce editable vector graphics in @code{PowerPoint} and also to
define placeholder where content is to be added.")
    (license license:expat)))

(define-public r-oews2021
  (package
    (name "r-oews2021")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oews2021" version))
       (sha256
        (base32 "0b03jqn7bz528qky6h35h3kxr6pnfqpllc4h2lgpf790slsfc054"))))
    (properties `((upstream-name . "oews2021")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=oews2021")
    (synopsis "May 2021 Occupational Employment and Wage Statistics")
    (description
     "This package contains data from the May 2021 Occupational Employment and Wage
Statistics data release from the U.S. Bureau of Labor Statistics.  The dataset
covers employment and wages across occupations, industries, states, and at the
national level.  Metropolitan data is not included.")
    (license license:expat)))

(define-public r-oews2020
  (package
    (name "r-oews2020")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oews2020" version))
       (sha256
        (base32 "0qan0dw6v25219xxij8ra36ccdvz21n4c1025dnb36rgb63wa3kg"))))
    (properties `((upstream-name . "oews2020")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=oews2020")
    (synopsis "May 2020 Occupational Employment and Wage Statistics")
    (description
     "This package contains data from the May 2020 Occupational Employment and Wage
Statistics data release from the U.S. Bureau of Labor Statistics.  The dataset
covers employment and wages across occupations, industries, states, and at the
national level.  Metropolitan data is not included.")
    (license license:expat)))

(define-public r-oesr
  (package
    (name "r-oesr")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oesr" version))
       (sha256
        (base32 "078jjvm9d0g8jaab0x2z4h7h8m2pznamiglhkwv07xc65cskjmpb"))))
    (properties `((upstream-name . "oesr")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-sandwich
                             r-rlang
                             r-ggplot2
                             r-extrafont
                             r-estimatr
                             r-dplyr
                             r-broom))
    (home-page "https://cran.r-project.org/package=oesr")
    (synopsis "Methods for the Office of Evaluation Sciences")
    (description
     "This package provides methods for statistical analysis and reporting preferred
by the US Office of Evaluation Sciences (OES).  This package prepares data from
standard model output objects (such as from \\code{lm()} and
\\code{estimatr::lm_robust()}) and creates visualizations of treatment effects
from the prepared quantities, according to the standards of the US Office of
Evaluation Sciences.")
    (license license:gpl3)))

(define-public r-oenokpm
  (package
    (name "r-oenokpm")
    (version "2.4.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OenoKPM" version))
       (sha256
        (base32 "1qqfnq0zzmnjjb9rr6qd2l08rn5plkg4xsbrdk7jv1alfnq1b938"))))
    (properties `((upstream-name . "OenoKPM")))
    (build-system r-build-system)
    (propagated-inputs (list r-openxlsx r-minpack-lm r-gridextra r-ggpubr
                             r-ggplot2))
    (home-page "https://cran.r-project.org/package=OenoKPM")
    (synopsis
     "Modeling the Kinetics of Carbon Dioxide Production in Alcoholic Fermentation")
    (description
     "Developed to help researchers who need to model the kinetics of carbon dioxide
(CO2) production in alcoholic fermentation of wines, beers and other fermented
products.  The following models are available for modeling the carbon dioxide
production curve as a function of time: 5PL, Gompertz and 4PL. This package has
different functions, which applied can: perform the modeling of the data
obtained in the fermentation and return the coefficients, analyze the model fit
and return different statistical metrics, and calculate the kinetic parameters:
Maximum production of carbon dioxide; Maximum rate of production of carbon
dioxide; Moment in which maximum fermentation rate occurs; Duration of the
latency phase for carbon dioxide production; Carbon dioxide produced until
maximum fermentation rate occurs.  In addition, a function that generates graphs
with the observed and predicted data from the models, isolated and combined, is
available.  Gava, A., Borsato, D., & Ficagna, E. (2020).\"Effect of mixture of
fining agents on the fermentation kinetics of base wine for sparkling wine
production: Use of methodology for modeling\". <doi:10.1016/j.lwt.2020.109660>.")
    (license license:gpl3)))

(define-public r-oem
  (package
    (name "r-oem")
    (version "2.0.12")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oem" version))
       (sha256
        (base32 "1a12d4fnrkrawb5f7rfidjixjl1v5qznqdyv8a5s1bp37pf1gh89"))))
    (properties `((upstream-name . "oem")))
    (build-system r-build-system)
    (propagated-inputs (list r-rspectra
                             r-rcppeigen
                             r-rcpparmadillo
                             r-rcpp
                             r-matrix
                             r-foreach
                             r-bigmemory
                             r-bh))
    (native-inputs (list r-knitr))
    (home-page "https://arxiv.org/abs/1801.09661")
    (synopsis "Orthogonalizing EM: Penalized Regression for Big Tall Data")
    (description
     "Solves penalized least squares problems for big tall data using the
orthogonalizing EM algorithm of Xiong et al. (2016)
<doi:10.1080/00401706.2015.1054436>.  The main fitting function is oem() and the
functions cv.oem() and xval.oem() are for cross validation, the latter being an
accelerated cross validation function for linear models.  The big.oem() function
allows for out of memory fitting.  A description of the underlying methods and
code interface is described in Huling and Chien (2022)
<doi:10.18637/jss.v104.i06>.")
    (license license:gpl2+)))

(define-public r-oeli
  (package
    (name "r-oeli")
    (version "0.7.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oeli" version))
       (sha256
        (base32 "0pnf7xb803xm2b2hzvgzrvmdcz09mkdrzzqc3xdz6j7kwdy5jwsc"))))
    (properties `((upstream-name . "oeli")))
    (build-system r-build-system)
    (propagated-inputs (list r-usethis
                             r-testthat
                             r-sysfonts
                             r-simmulticorrdata
                             r-showtext
                             r-rprojroot
                             r-rcpparmadillo
                             r-rcpp
                             r-latex2exp
                             r-hexsticker
                             r-ggplot2
                             r-cli
                             r-checkmate
                             r-benchmarkme))
    (home-page "https://github.com/loelschlaeger/oeli")
    (synopsis "Utilities for Developing Data Science Software")
    (description
     "Some general helper functions that I (and maybe others) find useful when
developing data science software.")
    (license license:gpl3+)))

(define-public r-oefpil
  (package
    (name "r-oefpil")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OEFPIL" version))
       (sha256
        (base32 "0gnbbz2spaqlqqn7978l15jv7xiqpfrh8k9girrpdqih02x95rfw"))))
    (properties `((upstream-name . "OEFPIL")))
    (build-system r-build-system)
    (propagated-inputs (list r-plyr
                             r-minpack-lm
                             r-matrixcalc
                             r-mass
                             r-ggplot2
                             r-deriv))
    (home-page "https://cran.r-project.org/package=OEFPIL")
    (synopsis
     "Optimal Estimation of Function Parameters by Iterated Linearization")
    (description
     "Package for estimating the parameters of a nonlinear function using iterated
linearization via Taylor series.  Method is based on KubÃ¡Äek (2000) ISBN:
80-244-0093-6.  The algorithm is a generalization of the procedure given in
KÃ¶ning, R., Wimmer, G. and WitkovskÃ½, V. (2014)
<doi:10.1088/0957-0233/25/11/115001>.")
    (license license:gpl2+)))

(define-public r-oecd
  (package
    (name "r-oecd")
    (version "0.2.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OECD" version))
       (sha256
        (base32 "13f185xvjlhxbg94vmnzvyddidxsbkvffjabp7jkg1zjl4x680s1"))))
    (properties `((upstream-name . "OECD")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2 r-readsdmx r-httr))
    (home-page "https://github.com/expersso/OECD")
    (synopsis "Search and Extract Data from the OECD")
    (description
     "Search and extract data from the Organization for Economic Cooperation and
Development (OECD).")
    (license license:cc0)))

(define-public r-odt
  (package
    (name "r-odt")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ODT" version))
       (sha256
        (base32 "0gwjnx99g2r3fhysp0in8dby5syvnpzs3lysgagsdd38pfhizq9h"))))
    (properties `((upstream-name . "ODT")))
    (build-system r-build-system)
    (propagated-inputs (list r-rsvg
                             r-partykit
                             r-matrixstats
                             r-magick
                             r-diagrammersvg
                             r-diagrammer
                             r-data-tree))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ODT")
    (synopsis "Optimal Decision Trees Algorithm")
    (description
     "This package implements a tree-based method specifically designed for
personalized medicine applications.  By using genomic and mutational data, ODT
efficiently identifies optimal drug recommendations tailored to individual
patient profiles.  The ODT algorithm constructs decision trees that bifurcate at
each node, selecting the most relevant markers (discrete or continuous) and
corresponding treatments, thus ensuring that recommendations are both
personalized and statistically robust.  This iterative approach enhances
therapeutic decision-making by refining treatment suggestions until a predefined
group size is achieved.  Moreover, the simplicity and interpretability of the
resulting trees make the method accessible to healthcare professionals.
Includes functions for training the decision tree, making predictions on new
samples or patients, and visualizing the resulting tree.  For detailed insights
into the methodology, please refer to Gimeno et al. (2023)
<doi:10.1093/bib/bbad200>.")
    (license license:artistic2.0)))

(define-public r-ods
  (package
    (name "r-ods")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ODS" version))
       (sha256
        (base32 "0i7giibass7hadvv6mb7k9xrykgfss57jmm6gpbym8qcywhzq4ny"))))
    (properties `((upstream-name . "ODS")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival r-cubature))
    (home-page "https://github.com/Yinghao-Pan/ODS")
    (synopsis "Statistical Methods for Outcome-Dependent Sampling Designs")
    (description
     "Outcome-dependent sampling (ODS) schemes are cost-effective ways to enhance
study efficiency.  In ODS designs, one observes the exposure/covariates with a
probability that depends on the outcome variable.  Popular ODS designs include
case-control for binary outcome, case-cohort for time-to-event outcome, and
continuous outcome ODS design (Zhou et al.  2002) <doi:
10.1111/j.0006-341X.2002.00413.x>.  Because ODS data has biased sampling nature,
standard statistical analysis such as linear regression will lead to biases
estimates of the population parameters.  This package implements four
statistical methods related to ODS designs: (1) An empirical likelihood method
analyzing the primary continuous outcome with respect to exposure variables in
continuous ODS design (Zhou et al., 2002). (2) A partial linear model analyzing
the primary outcome in continuous ODS design (Zhou, Qin and Longnecker, 2011)
<doi: 10.1111/j.1541-0420.2010.01500.x>. (3) Analyze a secondary outcome in
continuous ODS design (Pan et al.  2018) <doi: 10.1002/sim.7672>. (4) An
estimated likelihood method analyzing a secondary outcome in case-cohort data
(Pan et al.  2017) <doi: 10.1111/biom.12838>.")
    (license license:gpl2+)))

(define-public r-odrf
  (package
    (name "r-odrf")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ODRF" version))
       (sha256
        (base32 "017z7yr4r864cxvqyn14fxgmc2rgq01c95sbcmp6qg8dj03bcz53"))))
    (properties `((upstream-name . "ODRF")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-rcpparmadillo
                             r-rcpp
                             r-pursuit
                             r-partykit
                             r-nnet
                             r-magrittr
                             r-lifecycle
                             r-glue
                             r-foreach
                             r-doparallel))
    (native-inputs (list r-knitr))
    (home-page "https://liuyu-star.github.io/ODRF/")
    (synopsis
     "Oblique Decision Random Forest for Classification and Regression")
    (description
     "The oblique decision tree (ODT) uses linear combinations of predictors as
partitioning variables in a decision tree.  Oblique Decision Random Forest
(ODRF) is an ensemble of multiple ODTs generated by feature bagging.  Both can
be used for classification and regression as supplements to the classical CART
of Breiman (1984) <DOI:10.1201/9781315139470> and Random Forest of Breiman
(2001) <DOI:10.1023/A:1010933404324> respectively.")
    (license license:gpl3+)))

(define-public r-odr
  (package
    (name "r-odr")
    (version "1.4.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "odr" version))
       (sha256
        (base32 "037v6523kbl0izfzyg6lp6h4r5p8w23dp8r1fpx07wyr34q2w8vn"))))
    (properties `((upstream-name . "odr")))
    (build-system r-build-system)
    (native-inputs (list r-rmarkdown r-markdown r-knitr))
    (home-page "https://cran.r-project.org/package=odr")
    (synopsis
     "Optimal Design and Statistical Power for Experimental Studies Investigating Main, Mediation, and Moderation Effects")
    (description
     "Calculate the optimal sample size allocation that produces the highest
statistical power for experimental studies under a budget constraint, and
perform power analyses with and without accommodating cost structures of
sampling.  The designs cover single-level and multilevel experiments detecting
main, mediation, and moderation effects (and some combinations).  The references
for the proposed methods include: (1) Shen, Z., & Kelcey, B. (2020).  Optimal
sample allocation under unequal costs in cluster-randomized trials.  Journal of
Educational and Behavioral Statistics, 45(4): 446-474.
<doi:10.3102/1076998620912418>. (2) Shen, Z., & Kelcey, B. (2022b).  Optimal
sample allocation for three-level multisite cluster-randomized trials.  Journal
of Research on Educational Effectiveness, 15 (1), 130-150.
<doi:10.1080/19345747.2021.1953200>. (3) Shen, Z., & Kelcey, B. (2022a).
Optimal sample allocation in multisite randomized trials.  The Journal of
Experimental Education. <doi:10.1080/00220973.2020.1830361>. (4) Champely, S.
(2020).  pwr: Basic functions for power analysis (Version 1.3-0) [Software].
Available from <https://CRAN.R-project.org/package=pwr>.")
    (license license:gpl3)))

(define-public r-odmeans
  (package
    (name "r-odmeans")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ODMeans" version))
       (sha256
        (base32 "0fxy792h439kjbs7hq3cchnz00va5vbi1s6fq3ppjnp0qxf7h7zq"))))
    (properties `((upstream-name . "ODMeans")))
    (build-system r-build-system)
    (propagated-inputs (list r-ggrepel r-ggplot2 r-ggmap r-geosphere))
    (home-page "https://cran.r-project.org/package=ODMeans")
    (synopsis "OD-Means: k-Means for Origin-Destination")
    (description
     "OD-means is a hierarchical adaptive k-means algorithm based on
origin-destination pairs.  In the first layer of the hierarchy, the clusters are
separated automatically based on the variation of the within-cluster distance of
each cluster until convergence.  The second layer of the hierarchy corresponds
to the sub clustering process of small clusters based on the distance between
the origin and destination of each cluster.")
    (license license:gpl3+)))

(define-public r-odk
  (package
    (name "r-odk")
    (version "1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "odk" version))
       (sha256
        (base32 "0fcnr4c1clwx1sk6fgg4cx506gdi90n2h05g0i47p4s5bra0qwwl"))))
    (properties `((upstream-name . "odk")))
    (build-system r-build-system)
    (propagated-inputs (list r-openxlsx r-gsheet))
    (home-page "https://cran.r-project.org/package=odk")
    (synopsis "Convert 'ODK' or 'XLSForm' to 'SPSS' Data Frame")
    (description
     "After develop a ODK <https://opendatakit.org/> frame, we can link the frame to
Google Sheets <https://www.google.com/sheets/about/> and collect data through
Android <https://www.android.com/>.  This data uploaded to a Google sheets'.
odk2spss() function help to convert the odk frame into SPSS
<https://www.ibm.com/analytics/us/en/technology/spss/> frame.  Also able to add
downloaded Google sheets data or read data from Google sheets by using ODK frame
submission_url'.")
    (license license:gpl3)))

(define-public r-odin
  (package
    (name "r-odin")
    (version "1.2.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "odin" version))
       (sha256
        (base32 "0rr3sg96z7f64pz84pfrcaaz8sqa6lgp4z7dj2pyrvzgjxjr3fjm"))))
    (properties `((upstream-name . "odin")))
    (build-system r-build-system)
    (propagated-inputs (list r-withr
                             r-ring
                             r-r6
                             r-jsonlite
                             r-glue
                             r-digest
                             r-desolve
                             r-cinterpolate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/mrc-ide/odin")
    (synopsis "ODE Generation and Integration")
    (description
     "Generate systems of ordinary differential equations (ODE) and integrate them,
using a domain specific language (DSL).  The DSL uses R's syntax, but compiles
to C in order to efficiently solve the system.  A solver is not provided, but
instead interfaces to the packages @code{deSolve} and dde are generated.  With
these, while solving the differential equations, no allocations are done and the
calculations remain entirely in compiled code.  Alternatively, a model can be
transpiled to R for use in contexts where a C compiler is not present.  After
compilation, models can be inspected to return information about parameters and
outputs, or intermediate values after calculations.  odin is not targeted at any
particular domain and is suitable for any system that can be expressed primarily
as mathematical expressions.  Additional support is provided for working with
delays (delay differential equations, DDE), using interpolated functions during
interpolation, and for integrating quantities that represent arrays.")
    (license license:expat)))

(define-public r-odetector
  (package
    (name "r-odetector")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "odetector" version))
       (sha256
        (base32 "094i6ykv3s0c5yhdnlgpkz1wb6pr9k6r3vsh7zgkxyy5iayi6dlv"))))
    (properties `((upstream-name . "odetector")))
    (build-system r-build-system)
    (propagated-inputs (list r-ppclust))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/zcebeci/odetector")
    (synopsis "Outlier Detection Using Partitioning Clustering Algorithms")
    (description
     "An object is called \"outlier\" if it remarkably deviates from the other objects
in a data set.  Outlier detection is the process to find outliers by using the
methods that are based on distance measures, clustering and spatial methods
(Ben-Gal, 2005 <ISBN 0-387-24435-2>).  It is one of the intensively studied
research topics for identification of novelties, frauds, anomalies, deviations
or exceptions in addition to its use for outlier removing in data processing.
This package provides the implementations of some novel approaches to detect the
outliers based on typicality degrees that are obtained with the soft
partitioning clustering algorithms such as Fuzzy C-means and its variants.")
    (license license:gpl2+)))

(define-public r-odesensitivity
  (package
    (name "r-odesensitivity")
    (version "1.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ODEsensitivity" version))
       (sha256
        (base32 "0yddv5h3y0xfviqjgrbixawd00jc1rh9ngckfqka5j855vhchh66"))))
    (properties `((upstream-name . "ODEsensitivity")))
    (build-system r-build-system)
    (propagated-inputs (list r-sensitivity r-odenetwork r-desolve r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/surmann/ODEsensitivity")
    (synopsis "Sensitivity Analysis of Ordinary Differential Equations")
    (description
     "This package performs sensitivity analysis in ordinary differential equation
(ode) models.  The package utilize the ode interface from @code{deSolve} and
connects it with the sensitivity analysis from sensitivity'.  Additionally we
add a method to run the sensitivity analysis on variables with class
ODEnetwork'.  A detailed plotting function provides outputs on the calculations.
 The method is described by Weber, Theers, Surmann, Ligges, and Weihs (2018)
<doi:10.17877/DE290R-18874>.")
    (license license:lgpl3)))

(define-public r-odenetwork
  (package
    (name "r-odenetwork")
    (version "1.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ODEnetwork" version))
       (sha256
        (base32 "0wicp0xxqq3jl0kjhc26iqpk8rwa9nv2aiwf18pkgnqxbyw6lgnp"))))
    (properties `((upstream-name . "ODEnetwork")))
    (build-system r-build-system)
    (propagated-inputs (list r-desolve r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/surmann/ODEnetwork")
    (synopsis "Network of Differential Equations")
    (description
     "Simulates a network of ordinary differential equations of order two.  The
package provides an easy interface to construct networks.  In addition you are
able to define different external triggers to manipulate the trajectory.  The
method is described by Surmann, Ligges, and Weihs (2014)
<doi:10.1109/ENERGYCON.2014.6850482>.")
    (license license:lgpl3)))

(define-public r-odeguts
  (package
    (name "r-odeguts")
    (version "1.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "odeGUTS" version))
       (sha256
        (base32 "0bk2ahk9qigqx00rdppgml4fb1czibhqal8wymqgs1bifixxb5wy"))))
    (properties `((upstream-name . "odeGUTS")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-tidyr r-magrittr r-dplyr r-desolve))
    (home-page "https://github.com/bgoussen/odeGUTS")
    (synopsis "Solve ODE for GUTS-RED-SD and GUTS-RED-IT Using Compiled Code")
    (description
     "Allows performing forwards prediction for the General Unified Threshold model of
Survival using compiled ode code.  This package was created to avoid dependency
with the morse package that requires the installation of JAGS'.  This package is
based on functions from the morse package v3.3.1: Virgile Baudrot, Sandrine
Charles, Marie Laure Delignette-Muller, Wandrille Duchemin, Benoit Goussen, Nils
Kehrein, Guillaume Kon-Kam-King, Christelle Lopes, Philippe Ruiz, Alexander
Singer and Philippe Veber (2021) <https://CRAN.R-project.org/package=morse>.")
    (license license:gpl3+)))

(define-public r-oddstream
  (package
    (name "r-oddstream")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oddstream" version))
       (sha256
        (base32 "1nwjw7fq6b4jdq4m2w0a7xgmzjg5a6pbma1d3r9msiz8rnhb0c54"))))
    (properties `((upstream-name . "oddstream")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-tibble
                             r-reshape
                             r-rcpproll
                             r-rcolorbrewer
                             r-pcapp
                             r-mvtsplot
                             r-moments
                             r-mgcv
                             r-mass
                             r-magrittr
                             r-ks
                             r-kernlab
                             r-ggplot2
                             r-dplyr))
    (home-page "https://cran.r-project.org/package=oddstream")
    (synopsis "Outlier Detection in Data Streams")
    (description
     "We proposes a framework that provides real time support for early detection of
anomalous series within a large collection of streaming time series data.  By
definition, anomalies are rare in comparison to a system's typical behaviour.
We define an anomaly as an observation that is very unlikely given the forecast
distribution.  The algorithm first forecasts a boundary for the system's typical
behaviour using a representative sample of the typical behaviour of the system.
An approach based on extreme value theory is used for this boundary prediction
process.  Then a sliding window is used to test for anomalous series within the
newly arrived collection of series.  Feature based representation of time series
is used as the input to the model.  To cope with concept drift, the forecast
boundary for the system's typical behaviour is updated periodically.  More
details regarding the algorithm can be found in Talagala, P. D., Hyndman, R. J.,
Smith-Miles, K., et al. (2019) <doi:10.1080/10618600.2019.1617160>.")
    (license license:gpl3)))

(define-public r-oddsratio
  (package
    (name "r-oddsratio")
    (version "2.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oddsratio" version))
       (sha256
        (base32 "1db0pxi5j18rvi8dyc2xx1im3l269775vpjjavapjcv2pylfg5r0"))))
    (properties `((upstream-name . "oddsratio")))
    (build-system r-build-system)
    (propagated-inputs (list r-mgcv r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/pat-s/oddsratio")
    (synopsis "Odds Ratio Calculation for GAM(M)s & GLM(M)s")
    (description
     "Simplified odds ratio calculation of GAM(M)s & GLM(M)s.  Provides structured
output (data frame) of all predictors and their corresponding odds ratios and
confident intervals for further analyses.  It helps to avoid false references of
predictors and increments by specifying these parameters in a list instead of
using exp(coef(model)) (standard approach of odds ratio calculation for GLMs)
which just returns a plain numeric output.  For GAM(M)s, odds ratio calculation
is highly simplified with this package since it takes care of the multiple
predict() calls of the chosen predictor while holding other predictors constant.
 Also, this package allows odds ratio calculation of percentage steps across the
whole predictor distribution range for GAM(M)s.  In both cases, confident
intervals are returned additionally.  Calculated odds ratio of GAM(M)s can be
inserted into the smooth function plot.")
    (license license:expat)))

(define-public r-oddsplotty
  (package
    (name "r-oddsplotty")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OddsPlotty" version))
       (sha256
        (base32 "0adgbrni7yrarybh0djmq68hifwqzn2rn9mfqgwqma1d7mg3ai93"))))
    (properties `((upstream-name . "OddsPlotty")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidymodels
                             r-tibble
                             r-rmarkdown
                             r-mlbench
                             r-magrittr
                             r-ggthemes
                             r-ggplot2
                             r-e1071
                             r-caret))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/StatsGary/OddsPlotty")
    (synopsis "Odds Plot to Visualise a Logistic Regression Model")
    (description
     "Uses the outputs of a logistic regression model, from caret
<https://CRAN.R-project.org/package=caret>, to build an odds plot.  This allows
for the rapid visualisation of odds plot ratios and works best with the outputs
of CARET's GLM model class, by returning the final trained model.")
    (license license:gpl3+)))

(define-public r-oddsapir
  (package
    (name "r-oddsapir")
    (version "0.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oddsapiR" version))
       (sha256
        (base32 "0vjmmbyxsnc40sv053s3jgwssxnn897kf5hkx1vbxrym7zx775k9"))))
    (properties `((upstream-name . "oddsapiR")))
    (build-system r-build-system)
    (inputs (list pandoc pandoc))
    (propagated-inputs (list r-tidyr
                             r-rvest
                             r-rlang
                             r-magrittr
                             r-jsonlite
                             r-janitor
                             r-httr
                             r-glue
                             r-dplyr
                             r-data-table
                             r-cli))
    (home-page "https://oddsapiR.sportsdataverse.org/")
    (synopsis "Access Live Sports Odds from the Odds API")
    (description
     "This package provides a utility to quickly obtain clean and tidy sports odds
from The Odds API <https://the-odds-api.com>.")
    (license license:expat)))

(define-public r-odds-n-ends
  (package
    (name "r-odds-n-ends")
    (version "0.1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "odds.n.ends" version))
       (sha256
        (base32 "1md0m1z8a6jnmkjj2njngpqpasnvgngdxj57r3jc7jq356qzg707"))))
    (properties `((upstream-name . "odds.n.ends")))
    (build-system r-build-system)
    (propagated-inputs (list r-mass))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=odds.n.ends")
    (synopsis
     "Odds Ratios, Contingency Table, and Model Significance from a Generalized Linear Model Object")
    (description
     "Computes odds ratios and 95% confidence intervals from a generalized linear
model object.  It also computes model significance with the chi-squared
statistic and p-value and it computes model fit using a contingency table to
determine the percent of observations for which the model correctly predicts the
value of the outcome.  Calculates model sensitivity and specificity.")
    (license license:cc0)))

(define-public r-odds-converter
  (package
    (name "r-odds-converter")
    (version "1.4.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "odds.converter" version))
       (sha256
        (base32 "09s8pg55gpsxmrbimzg5rsr1n07la93781sar6vab5p9zn9zxgx4"))))
    (properties `((upstream-name . "odds.converter")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=odds.converter")
    (synopsis "Betting Odds Conversion")
    (description
     "Conversion between the most common odds types for sports betting.  Hong Kong
odds, US odds, Decimal odds, Indonesian odds, Malaysian odds, and raw
Probability are covered in this package.")
    (license license:gpl3)))

(define-public r-oddnet
  (package
    (name "r-oddnet")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oddnet" version))
       (sha256
        (base32 "0wa3vjjsn9f60b4c2l43sy41x0qhkbsg0yjy1ki6pgflgavr9ldg"))))
    (properties `((upstream-name . "oddnet")))
    (build-system r-build-system)
    (propagated-inputs (list r-tsibble
                             r-tidyr
                             r-tibble
                             r-rlang
                             r-pcapp
                             r-lookout
                             r-igraph
                             r-fabletools
                             r-fable
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://sevvandi.github.io/oddnet/")
    (synopsis "Anomaly Detection in Temporal Networks")
    (description
     "Anomaly detection in dynamic, temporal networks.  The package oddnet uses a
feature-based method to identify anomalies.  First, it computes many features
for each network.  Then it models the features using time series methods.  Using
time series residuals it detects anomalies.  This way, the temporal dependencies
are accounted for when identifying anomalies (Kandanaarachchi, Hyndman 2022)
<@code{arXiv:2210.07407>}.")
    (license license:gpl3+)))

(define-public r-odbc
  (package
    (name "r-odbc")
    (version "1.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "odbc" version))
       (sha256
        (base32 "1c49209bf1swsk5mhwb4zxymlg5dha9rg500nq83kbgib6ikkk9f"))))
    (properties `((upstream-name . "odbc")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang
                             r-rcpp
                             r-lifecycle
                             r-hms
                             r-dbi
                             r-cli
                             r-blob
                             r-bit64))
    (native-inputs (list pkg-config r-knitr))
    (home-page "https://odbc.r-dbi.org")
    (synopsis "Connect to ODBC Compatible Databases (using the DBI Interface)")
    (description
     "This package provides a DBI-compatible interface to ODBC databases.")
    (license license:expat)))

(define-public r-odb
  (package
    (name "r-odb")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ODB" version))
       (sha256
        (base32 "0frkbl99ilpmppm4fm97lbkqhmjgcwlz9j5vh5nzzcsxrh8qwicn"))))
    (properties `((upstream-name . "ODB")))
    (build-system r-build-system)
    (inputs (list zip))
    (propagated-inputs (list r-rjdbc r-dbi))
    (home-page "http://bioinformatics.ovsa.fr/ODB")
    (synopsis "Open Document Databases (.odb) Management")
    (description
     "This package provides functions to create, connect, update and query HSQL
databases embedded in Open Document Databases files, as @code{OpenOffice} and
@code{LibreOffice} do.")
    (license license:gpl3+)))

(define-public r-odataquery
  (package
    (name "r-odataquery")
    (version "0.5.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ODataQuery" version))
       (sha256
        (base32 "058j3rc5kh134ndsxn5gck2xh6llrs73cyxpa5z8zkmsw9am22qj"))))
    (properties `((upstream-name . "ODataQuery")))
    (build-system r-build-system)
    (propagated-inputs (list r-rlang r-r6 r-jsonlite r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ODataQuery")
    (synopsis "Querying on 'OData'")
    (description
     "Make querying on OData easier.  It exposes an O@code{DataQuery} object that can
be manipulated and provides features such as selection, filtering and ordering.")
    (license license:gpl3)))

(define-public r-od
  (package
    (name "r-od")
    (version "0.5.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "od" version))
       (sha256
        (base32 "16lal5asj6h9i5zwafpgzplcbl5pmwfn9gs2azi5swq5v6n0i748"))))
    (properties `((upstream-name . "od")))
    (build-system r-build-system)
    (propagated-inputs (list r-vctrs r-sfheaders))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/itsleeds/od")
    (synopsis "Manipulate and Map Origin-Destination Data")
    (description
     "The aim of od is to provide tools and example datasets for working with
origin-destination ('OD') datasets of the type used to describe aggregate urban
mobility patterns (Carey et al.  1981) <doi:10.1287/trsc.15.1.32>.  The package
builds on functions for working with OD data in the package stplanr', (Lovelace
and Ellison 2018) <doi:10.32614/RJ-2018-053> with a focus on computational
efficiency and support for the sf class system (Pebesma 2018)
<doi:10.32614/RJ-2018-009>.  With few dependencies and a simple class system
based on data frames, the package is intended to facilitate efficient analysis
of OD datasets and to provide a place for developing new functions.  The package
enables the creation and analysis of geographic entities representing large
scale mobility patterns, from daily travel between zones in cities to migration
between countries.")
    (license license:gpl3)))

(define-public r-octopusr
  (package
    (name "r-octopusr")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "octopusR" version))
       (sha256
        (base32 "1hah1zphwrvj1kx344s9nxq8bw4q358fz9j487hi6dkfhjvg7j21"))))
    (properties `((upstream-name . "octopusR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-rlang
                             r-httr2
                             r-glue
                             r-cli
                             r-askpass))
    (home-page "https://github.com/Moohan/octopusR")
    (synopsis "Interact with the 'Octopus Energy' API")
    (description
     "This package provides a simple wrapper for the Octopus Energy API
<https://developer.octopus.energy/docs/api/>.  It handles authentication, by
storing a provided API key and meter details.  Implemented endpoints include
products for viewing tariff details and consumption for viewing meter
consumption data.")
    (license license:expat)))

(define-public r-octopus
  (package
    (name "r-octopus")
    (version "0.4.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "octopus" version))
       (sha256
        (base32 "0a24czpsvq5xpr3g9m6d2bsd3dv5jcr2m724gz4z3c56f4xbxd8b"))))
    (properties `((upstream-name . "octopus")))
    (build-system r-build-system)
    (propagated-inputs (list r-shinyjs
                             r-shinyace
                             r-shiny
                             r-rio
                             r-janitor
                             r-httr
                             r-glue
                             r-dt
                             r-dplyr
                             r-dbi
                             r-data-table
                             r-bslib))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/MCodrescu/octopus")
    (synopsis "Database Management Tool")
    (description
     "This package provides a database management tool built as a shiny application.
Connect to various databases to send queries, upload files, preview tables, and
more.")
    (license license:expat)))

(define-public r-octopucs
  (package
    (name "r-octopucs")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "octopucs" version))
       (sha256
        (base32 "0l9km2q9yjv43bis32gmw6sc7y5c425plgs0vi9sjx17pgsyvqdw"))))
    (properties `((upstream-name . "octopucs")))
    (build-system r-build-system)
    (propagated-inputs (list r-vegan r-stringr r-progress))
    (home-page "https://cran.r-project.org/package=octopucs")
    (synopsis "Statistical Support for Hierarchical Clusters")
    (description
     "Generates n hierarchical clustering hypotheses on subsets of classifiers
(usually species in community ecology studies).  The n clustering hypotheses are
combined to generate a generalized cluster, and computes three metrics of
support.  1) The average proportion of elements conforming the group in each of
the n clusters (integrity).  And 2) the contamination, i.e., the average
proportion of elements from other groups that enter a focal group.  3) The
probability of existence of the group gives the integrity and contamination in a
Bayesian approach.")
    (license license:gpl3)))

(define-public r-ocsdata
  (package
    (name "r-ocsdata")
    (version "1.0.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OCSdata" version))
       (sha256
        (base32 "0119c2i9k63mbz40lbbf7x59nf4yyhrmaynn0m0sh1h3jjbsiazc"))))
    (properties `((upstream-name . "OCSdata")))
    (build-system r-build-system)
    (propagated-inputs (list r-usethis r-purrr r-httr))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/opencasestudies/OCSdata")
    (synopsis "Download Data from the 'Open Case Studies' Repository")
    (description
     "This package provides functions to access and download data from the Open Case
Studies <https://www.opencasestudies.org/> repositories on @code{GitHub}
<https://github.com/opencasestudies>.  Different functions enable users to grab
the data they need at different sections in the case study, as well as download
the whole case study repository.  All the user needs to do is input the name of
the case study being worked on.  The package relies on the httr::GET() function
to access files through the @code{GitHub} API. The functions usethis::use_zip()
and usethis::create_from_github() are used to clone and/or download the case
study repositories.  To cite an individual case study, please see the respective
README file at <https://github.com/opencasestudies/>.
<https://github.com/opencasestudies/ocs-bp-rural-and-urban-obesity>
<https://github.com/opencasestudies/ocs-bp-air-pollution>
<https://github.com/opencasestudies/ocs-bp-vaping-case-study>
<https://github.com/opencasestudies/ocs-bp-opioid-rural-urban>
<https://github.com/opencasestudies/ocs-bp-RTC-wrangling>
<https://github.com/opencasestudies/ocs-bp-RTC-analysis>
<https://github.com/opencasestudies/ocs-bp-youth-disconnection>
<https://github.com/opencasestudies/ocs-bp-youth-mental-health>
<https://github.com/opencasestudies/ocs-bp-school-shootings-dashboard>
<https://github.com/opencasestudies/ocs-bp-co2-emissions>
<https://github.com/opencasestudies/ocs-bp-diet>.")
    (license license:expat)))

(define-public r-ocs4r
  (package
    (name "r-ocs4r")
    (version "0.2-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ocs4R" version))
       (sha256
        (base32 "09zl9jl1kzvyq0wccp41j32pr3as93qh250iaawhwkpcswjpyl89"))))
    (properties `((upstream-name . "ocs4R")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml
                             r-r6
                             r-openssl
                             r-keyring
                             r-jsonlite
                             r-httr
                             r-curl))
    (home-page "https://github.com/eblondel/ocs4R")
    (synopsis "Interface to Open Collaboration Services (OCS) REST API")
    (description
     "This package provides an Interface to Open Collaboration Services OCS
(<https://www.open-collaboration-services.org/>) REST API.")
    (license license:expat)))

(define-public r-ocp
  (package
    (name "r-ocp")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ocp" version))
       (sha256
        (base32 "0q52s8j3z3xwnma3sxx6019qxid66bf0a43w4g8xjagplwps57dx"))))
    (properties `((upstream-name . "ocp")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=ocp")
    (synopsis "Bayesian Online Changepoint Detection")
    (description
     "This package implements the Bayesian online changepoint detection method by
Adams and @code{MacKay} (2007) <@code{arXiv:0710.3742>} for univariate or
multivariate data.  Gaussian and Poisson probability models are implemented.
Provides post-processing functions with alternative ways to extract
changepoints.")
    (license license:gpl3)))

(define-public r-ocnet
  (package
    (name "r-ocnet")
    (version "1.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OCNet" version))
       (sha256
        (base32 "1ryb5jbz1dd4b9v45za6li1szdz8n9mmf3n3wx4ivqmcrnp2zqdh"))))
    (properties `((upstream-name . "OCNet")))
    (build-system r-build-system)
    (propagated-inputs (list r-terra
                             r-spdep
                             r-spam
                             r-rgl
                             r-rcpp
                             r-igraph
                             r-fields
                             r-adespatial))
    (native-inputs (list r-knitr gfortran))
    (home-page "https://lucarraro.github.io/OCNet/")
    (synopsis "Optimal Channel Networks")
    (description
     "Generate and analyze Optimal Channel Networks (OCNs): oriented spanning trees
reproducing all scaling features characteristic of real, natural river networks.
 As such, they can be used in a variety of numerical experiments in the fields
of hydrology, ecology and epidemiology.  See Carraro et al. (2020)
<doi:10.1002/ece3.6479> for a presentation of the package; Rinaldo et al. (2014)
<doi:10.1073/pnas.1322700111> for a theoretical overview on the OCN concept;
Furrer and Sain (2010) <doi:10.18637/jss.v036.i10> for the construct used.")
    (license license:gpl3)))

(define-public r-oclust
  (package
    (name "r-oclust")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oclust" version))
       (sha256
        (base32 "08247vcjs7hhzbj69f2x39n5y5ycns0qd7pdlvpwyn4j7yd1ji31"))))
    (properties `((upstream-name . "oclust")))
    (build-system r-build-system)
    (propagated-inputs (list r-mvtnorm
                             r-mixture
                             r-mclust
                             r-mass
                             r-entropy
                             r-dbscan))
    (home-page "https://cran.r-project.org/package=oclust")
    (synopsis "Gaussian Model-Based Clustering with Outliers")
    (description
     "This package provides a function to detect and trim outliers in Gaussian mixture
model-based clustering using methods described in Clark and @code{McNicholas}
(2022) <@code{arXiv:1907.01136>}.")
    (license license:gpl2+)))

(define-public r-ockc
  (package
    (name "r-ockc")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ockc" version))
       (sha256
        (base32 "1iqv9vjdcv96a8k5ccrh6r3jpjq39g4g0qjhb4hzvfv17p28rpcb"))))
    (properties `((upstream-name . "ockc")))
    (build-system r-build-system)
    (propagated-inputs (list r-modeltools r-flexclust))
    (home-page "https://cran.r-project.org/package=ockc")
    (synopsis "Order Constrained Solutions in k-Means Clustering")
    (description
     "Extends flexclust with an R implementation of order constrained solutions in
k-means clustering (Steinley and Hubert, 2008, <doi:10.1007/s11336-008-9058-z>).")
    (license (list license:gpl2 license:gpl3))))

(define-public r-ocf
  (package
    (name "r-ocf")
    (version "1.0.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ocf" version))
       (sha256
        (base32 "1vzpiy7dby61yydszgm2magdq9dah7c0pw9zl7bsrycrzs5qfxgs"))))
    (properties `((upstream-name . "ocf")))
    (build-system r-build-system)
    (propagated-inputs (list r-stringr
                             r-rcppeigen
                             r-rcpp
                             r-ranger
                             r-orf
                             r-matrix
                             r-glmnet))
    (native-inputs (list r-knitr))
    (home-page "https://riccardo-df.github.io/ocf/")
    (synopsis "Ordered Correlation Forest")
    (description
     "Machine learning estimator specifically optimized for predictive modeling of
ordered non-numeric outcomes.  ocf provides forest-based estimation of the
conditional choice probabilities and the covariatesâ marginal effects.  Under
an \"honesty\" condition, the estimates are consistent and asymptotically normal
and standard errors can be obtained by leveraging the weight-based
representation of the random forest predictions.  Please reference the use as Di
Francesco (2023) <doi:10.48550/@code{arXiv.2309.08755>}.")
    (license license:gpl3)))

(define-public r-ocedata
  (package
    (name "r-ocedata")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ocedata" version))
       (sha256
        (base32 "0yj90gaaacq6d53di2vz23za5sz9wy2j626ib3cbdhvxg731pizk"))))
    (properties `((upstream-name . "ocedata")))
    (build-system r-build-system)
    (home-page "https://dankelley.github.io/ocedata/")
    (synopsis "Oceanographic Data Sets for 'oce' Package")
    (description
     "Several Oceanographic data sets are provided for use by the oce package and for
other purposes.")
    (license license:gpl2+)))

(define-public r-ocecens
  (package
    (name "r-ocecens")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oceCens" version))
       (sha256
        (base32 "1ckp89n22scmjli30x99iaxgyk41a27v1n9gxjp9n29y66lw71nb"))))
    (properties `((upstream-name . "oceCens")))
    (build-system r-build-system)
    (propagated-inputs (list r-survival))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=oceCens")
    (synopsis "Ordered Composite Endpoints with Censoring")
    (description
     "Estimates win ratio or Mann-Whitney parameter for two group comparisons using
ordered composite endpoints with right censoring as described in Follmann, Fay,
Hamasaki, and Evans (2020)<doi:10.1002/sim.7890>.")
    (license license:gpl3)))

(define-public r-oceanwaves
  (package
    (name "r-oceanwaves")
    (version "0.2.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oceanwaves" version))
       (sha256
        (base32 "1v4gj4ippv1l3r77z2ic19x5zi5lpsh5wihaqay3264zhpb3kv9a"))))
    (properties `((upstream-name . "oceanwaves")))
    (build-system r-build-system)
    (propagated-inputs (list r-signal r-ggplot2 r-bspec))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/millerlp/oceanwaves")
    (synopsis "Ocean Wave Statistics")
    (description
     "Calculate ocean wave height summary statistics and process data from
bottom-mounted pressure sensor data loggers.  Derived primarily from MATLAB
functions provided by U. Neumeier at
<http://neumeier.perso.ch/matlab/waves.html>.  Wave number calculation based on
the algorithm in Hunt, J. N. (1979, ISSN:0148-9895) \"Direct Solution of Wave
Dispersion Equation\", American Society of Civil Engineers Journal of the
Waterway, Port, Coastal, and Ocean Division, Vol 105, pp 457-459.")
    (license license:gpl3)))

(define-public r-oceanview
  (package
    (name "r-oceanview")
    (version "1.0.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OceanView" version))
       (sha256
        (base32 "0s615mrbwamd85h1q8rg5mciwq0hcjzl5rqjaq578nz5ikr3px9a"))))
    (properties `((upstream-name . "OceanView")))
    (build-system r-build-system)
    (propagated-inputs (list r-shape r-rgl r-plot3drgl r-plot3d))
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=OceanView")
    (synopsis "Visualisation of Oceanographic Data and Model Output")
    (description
     "This package provides functions for transforming and viewing 2-D and 3-D
(oceanographic) data and model output.")
    (license license:gpl3+)))

(define-public r-oceanmap
  (package
    (name "r-oceanmap")
    (version "0.1.6")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oceanmap" version))
       (sha256
        (base32 "12ppcqk2s14p7hg0a6b3hgnz90dxn3kagfgkpykz6ks93vjy8pd7"))))
    (properties `((upstream-name . "oceanmap")))
    (build-system r-build-system)
    (inputs (list imagemagick))
    (propagated-inputs (list r-sp
                             r-sf
                             r-reshape2
                             r-raster
                             r-plotrix
                             r-plotly
                             r-ncdf4
                             r-maps
                             r-mapdata
                             r-lubridate
                             r-ggplot2
                             r-ggedit
                             r-fields
                             r-extrafont
                             r-abind))
    (home-page "https://cran.r-project.org/package=oceanmap")
    (synopsis "Plotting Toolbox for 2D Oceanographic Data")
    (description
     "Plotting toolbox for 2D oceanographic data (satellite data, sea surface
temperature, chlorophyll, ocean fronts & bathymetry).  Recognized classes and
formats include netcdf, Raster, .nc and .gz files.")
    (license license:gpl3+)))

(define-public r-oceanis
  (package
    (name "r-oceanis")
    (version "1.8.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oceanis" version))
       (sha256
        (base32 "13zdzqjlf5pihji6np9a3m2j5ycy4jvfl75knzry2ir78zr9ngj7"))))
    (properties `((upstream-name . "oceanis")))
    (build-system r-build-system)
    (propagated-inputs (list r-zip
                             r-webshot
                             r-stringr
                             r-shinythemes
                             r-shinyjs
                             r-shinybs
                             r-shiny
                             r-sf
                             r-lwgeom
                             r-leaflet-extras
                             r-leaflet
                             r-htmlwidgets
                             r-ggplot2
                             r-dt
                             r-dplyr
                             r-classint))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/insee-psar-at/oceanis-package/")
    (synopsis "Cartography for Statistical Analysis")
    (description
     "Creating maps for statistical analysis such as proportional circles, choropleth,
typology and flows.  Some functions use shiny or leaflet technologies for
dynamism and interactivity.  The great features are : - Create maps in a web
environment where the parameters are modifiable on the fly ('shiny and leaflet
technologies). - Create interactive maps through zoom and pop-up ('leaflet
technology). - Create frozen maps with the possibility to add labels.")
    (license (list license:gpl2+
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-oceanic
  (package
    (name "r-oceanic")
    (version "0.1.7")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oceanic" version))
       (sha256
        (base32 "0nfz257i0gfkqvnpi4gaki79mgh1ff6h075dyylk0fs0gw01dddm"))))
    (properties `((upstream-name . "oceanic")))
    (build-system r-build-system)
    (propagated-inputs (list r-spdata
                             r-sp
                             r-sf
                             r-maps
                             r-ggplot2
                             r-broom))
    (home-page "https://cran.r-project.org/package=oceanic")
    (synopsis "Location Identify Tool")
    (description
     "Determine the sea area where the fishing boat operates.  The latitude and
longitude of geographic coordinates are used to match oceanic areas and economic
sea areas.  You can plot the distribution map with dotplot() function.  Please
refer to Flanders Marine Institute (2020) <doi:10.14284/403>.")
    (license license:gpl2+)))

(define-public r-oceanexplorer
  (package
    (name "r-oceanexplorer")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oceanexplorer" version))
       (sha256
        (base32 "07l2la7nrqj8bsyv0flyjs08wishlvq6v2hx5n1g9kag4bcfl6vz"))))
    (properties `((upstream-name . "oceanexplorer")))
    (build-system r-build-system)
    (propagated-inputs (list r-waiter
                             r-thematic
                             r-stars
                             r-shinyjs
                             r-shinyfeedback
                             r-shiny
                             r-sf
                             r-rstudioapi
                             r-rnetcdf
                             r-rlang
                             r-purrr
                             r-ncmeta
                             r-miniui
                             r-maps
                             r-glue
                             r-ggplot2
                             r-fs
                             r-dt
                             r-dplyr
                             r-bslib))
    (native-inputs (list r-knitr))
    (home-page "https://martinschobben.github.io/oceanexplorer/")
    (synopsis "Explore Our Planet's Oceans with NOAA")
    (description
     "This package provides tools for easy exploration of the world ocean atlas of the
US agency National Oceanic and Atmospheric Administration (NOAA).  It includes
functions to extract @code{NetCDF} data from the repository and code to
visualize several physical and chemical parameters of the ocean.  A Shiny app
further allows interactive exploration of the data.  The methods for data
collecting and quality checks are described in several papers, which can be
found here: <https://www.ncei.noaa.gov/products/world-ocean-atlas>.")
    (license license:expat)))

(define-public r-oce
  (package
    (name "r-oce")
    (version "1.8-3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oce" version))
       (sha256
        (base32 "13vg1g3pn1bmmjb5sb34qmwy2czxigin02nz4vkwlw9z4vpjkwgi"))))
    (properties `((upstream-name . "oce")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpp r-gsw))
    (native-inputs (list r-knitr gfortran))
    (home-page "https://dankelley.github.io/oce/")
    (synopsis "Analysis of Oceanographic Data")
    (description
     "Supports the analysis of Oceanographic data, including ADCP measurements,
measurements made with argo floats, CTD measurements, sectional data, sea-level
time series, coastline and topographic data, etc.  Provides specialized
functions for calculating seawater properties such as potential temperature in
either the UNESCO or TEOS-10 equation of state.  Produces graphical displays
that conform to the conventions of the Oceanographic literature.  This package
is discussed extensively by Kelley (2018) \"Oceanographic Analysis with R\"
<doi:10.1007/978-1-4939-8844-0>.")
    (license license:gpl2+)))

(define-public r-ocd
  (package
    (name "r-ocd")
    (version "1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "ocd" version))
       (sha256
        (base32 "06pyc352pvn85k76z9797gwk0ksbb3snvh6krysp68k3lcygq872"))))
    (properties `((upstream-name . "ocd")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=ocd")
    (synopsis "High-Dimensional Multiscale Online Changepoint Detection")
    (description
     "This package implements the algorithm in Chen, Wang and Samworth (2020)
<arxiv:2003.03668> for online detection of sudden mean changes in a sequence of
high-dimensional observations.  It also implements methods by Mei (2010)
<doi:10.1093/biomet/asq010>, Xie and Siegmund (2013) <doi:10.1214/13-AOS1094>
and Chan (2017) <doi:10.1214/17-AOS1546>.")
    (license license:gpl3)))

(define-public r-occupationmeasurement
  (package
    (name "r-occupationmeasurement")
    (version "0.3.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "occupationMeasurement" version))
       (sha256
        (base32 "03kq8sbcbb1swnc7rl2qqzmvlhfb7n5ba8q546v657cm35h15rr9"))))
    (properties `((upstream-name . "occupationMeasurement")))
    (build-system r-build-system)
    (propagated-inputs (list r-tm
                             r-text2vec
                             r-stringr
                             r-stringdist
                             r-shiny
                             r-digest
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page
     "https://occupationMeasurement.github.io/occupationMeasurement/")
    (synopsis "Interactively Measure Occupations in Interviews and Beyond")
    (description
     "Perform interactive occupation coding during interviews as described in
Peycheva, D., Sakshaug, J., Calderwood, L. (2021) <doi:10.2478/jos-2021-0042>
and Schierholz, M., Gensicke, M., Tschersich, N., Kreuter, F. (2018)
<doi:10.1111/rssa.12297>.  Generate suggestions for occupational categories
based on free text input, with pre-trained machine learning models in German and
a ready-to-use shiny application provided for quick and easy data collection.")
    (license license:expat)))

(define-public r-occupancy
  (package
    (name "r-occupancy")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "occupancy" version))
       (sha256
        (base32 "0j50vg1405n1hp72xqsq1hp3gdbfx5yq9w1zdv6dzjc6vjhbx00d"))))
    (properties `((upstream-name . "occupancy")))
    (build-system r-build-system)
    (propagated-inputs (list r-matrixstats))
    (home-page "https://cran.r-project.org/package=occupancy")
    (synopsis "Probability Functions for Occupancy Distributions")
    (description
     "The classical and extended occupancy distributions occur in cases where balls
are randomly allocated to bins.  The PDF, CDF, quantile functions, generation of
random variates, and calculating the first four central moments of the
distributions are implemented as described in OâNeill (2019)
<doi:10.1080/00031305.2019.1699445>.")
    (license license:expat)))

(define-public r-occumb
  (package
    (name "r-occumb")
    (version "1.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "occumb" version))
       (sha256
        (base32 "1rfaswipykflwkdiacq66ibbvf2hzzal2ffibsgrl8q1m6frj5k3"))))
    (properties `((upstream-name . "occumb")))
    (build-system r-build-system)
    (inputs (list jags))
    (propagated-inputs (list r-knitr r-jagsui r-crayon r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://fukayak.github.io/occumb/")
    (synopsis "Site Occupancy Modeling for Environmental DNA Metabarcoding")
    (description
     "Fits multispecies site occupancy models to environmental DNA metabarcoding data
collected using spatially-replicated survey design.  Model fitting results can
be used to evaluate and compare the effectiveness of species detection to find
an efficient survey design.  Reference: Fukaya et al. (2022)
<doi:10.1111/2041-210X.13732>.")
    (license license:gpl3+)))

(define-public r-occcite
  (package
    (name "r-occcite")
    (version "0.5.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "occCite" version))
       (sha256
        (base32 "0147c89yppj4mq3s2r49bwl64kw7nlsa81p7ljhiqzh80scq8fg3"))))
    (properties `((upstream-name . "occCite")))
    (build-system r-build-system)
    (propagated-inputs (list r-waffle
                             r-viridis
                             r-tidyr
                             r-stringr
                             r-rpostgresql
                             r-rlang
                             r-rgbif
                             r-rcolorbrewer
                             r-lubridate
                             r-leaflet
                             r-htmltools
                             r-ggplot2
                             r-dplyr
                             r-dbi
                             r-curl
                             r-bien
                             r-bib2df))
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://docs.ropensci.org/occCite/")
    (synopsis "Querying and Managing Large Biodiversity Occurrence Datasets")
    (description
     "Facilitates the gathering of biodiversity occurrence data from disparate
sources.  Metadata is managed throughout the process to facilitate reporting and
enhanced ability to repeat analyses.")
    (license license:gpl3)))

(define-public r-occ
  (package
    (name "r-occ")
    (version "1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "occ" version))
       (sha256
        (base32 "043n429q4md3x7bzgr22gh5mmbdx27b0vi161sw31vkmmzk1mblw"))))
    (properties `((upstream-name . "occ")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=occ")
    (synopsis "Estimation of PET Neuroreceptor Occupancies")
    (description
     "Estimate the positron emission tomography (PET) neuroreceptor occupancies from
the total volumes of distribution of a set of regions of interest.  Fitting
methods include the simple reference region', ordinary least squares (sometimes
known as occupancy plot), and restricted maximum likelihood estimation'.")
    (license license:gpl3)))

(define-public r-oca
  (package
    (name "r-oca")
    (version "0.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OCA" version))
       (sha256
        (base32 "19bayggqkzzpvn7ax8m8xgvz27a03iyybsxjz2vphf03dwsr8c5h"))))
    (properties `((upstream-name . "OCA")))
    (build-system r-build-system)
    (propagated-inputs (list r-mathjaxr))
    (home-page "https://cran.r-project.org/package=OCA")
    (synopsis "Optimal Capital Allocations")
    (description
     "Computes optimal capital allocations based on some standard principles such as
Haircut, Overbeck type II and the Covariance Allocation Principle.  It also
provides some shortcuts for obtaining the Value at Risk and the Expectation
Shortfall, using both the normal and the t-student distribution, see Urbina and
GuillÃ©n (2014)<doi:10.1016/j.eswa.2014.05.017> and Urbina
(2013)<http://hdl.handle.net/2099.1/19443>.")
    (license license:gpl2)))

(define-public r-oc
  (package
    (name "r-oc")
    (version "1.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oc" version))
       (sha256
        (base32 "0g4ij5g2xkkd73srm21b2xc170rgwbdsdx2qjkp3pr30axb0bf91"))))
    (properties `((upstream-name . "oc")))
    (build-system r-build-system)
    (propagated-inputs (list r-pscl))
    (native-inputs (list gfortran))
    (home-page "https://legacy.voteview.com/oc_in_R.htm")
    (synopsis "Optimal Classification Roll Call Analysis Software")
    (description
     "Estimates optimal classification (Poole 2000)
<doi:10.1093/oxfordjournals.pan.a029814> scores from roll call votes supplied
though a rollcall object from package pscl'.")
    (license license:gpl2)))

(define-public r-obssens
  (package
    (name "r-obssens")
    (version "1.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "obsSens" version))
       (sha256
        (base32 "07dvz3v580yliwqvfisgvzvg8ly9nw3r4y5bmwkmgphbfmh88635"))))
    (properties `((upstream-name . "obsSens")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=obsSens")
    (synopsis "Sensitivity Analysis for Observational Studies")
    (description
     "Observational studies are limited in that there could be an unmeasured variable
related to both the response variable and the primary predictor.  If this
unmeasured variable were included in the analysis it would change the
relationship (possibly changing the conclusions).  Sensitivity analysis is a way
to see how much of a relationship needs to exist with the unmeasured variable
before the conclusions change.  This package provides tools for doing a
sensitivity analysis for regression (linear, logistic, and cox) style models.")
    (license license:gpl2)))

(define-public r-obsmd
  (package
    (name "r-obsmd")
    (version "12.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OBsMD" version))
       (sha256
        (base32 "02ik14vpj8diwc0ylp37bk6s96mp9b79myzy8y9mmp7krj5p473q"))))
    (properties `((upstream-name . "OBsMD")))
    (build-system r-build-system)
    (native-inputs (list gfortran))
    (home-page "https://cran.r-project.org/package=OBsMD")
    (synopsis "Objective Bayesian Model Discrimination in Follow-Up Designs")
    (description
     "This package implements the objective Bayesian methodology proposed in Consonni
and Deldossi in order to choose the optimal experiment that better discriminate
between competing models, see Deldossi and Nai Ruscone (2020)
<doi:10.18637/jss.v094.i02>.")
    (license license:gpl2+)))

(define-public r-observation
  (package
    (name "r-observation")
    (version "0.3.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Observation" version))
       (sha256
        (base32 "1z9ldp050f7jy76s8yk509nwjx1ymvk5k9d19i67brd7xcawxnr3"))))
    (properties `((upstream-name . "Observation")))
    (build-system r-build-system)
    (propagated-inputs (list r-svdialogs))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/paulhibbing/Observation")
    (synopsis "Collect and Process Physical Activity Direct Observation Data")
    (description
     "Two-part system for first collecting then managing direct observation data, as
described by Hibbing PR, Ellingson LD, Dixon PM, & Welk GJ (2018)
<doi:10.1249/MSS.0000000000001486>.")
    (license (list license:gpl3
                   (license:fsdg-compatible "file://LICENSE")))))

(define-public r-obre
  (package
    (name "r-obre")
    (version "0.2-0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OBRE" version))
       (sha256
        (base32 "1x1s46yffjr140mwx8amnh02k6g8x2gz5hz7lypiwxh0v7a8bm8w"))))
    (properties `((upstream-name . "OBRE")))
    (build-system r-build-system)
    (propagated-inputs (list r-pracma))
    (home-page "https://cran.r-project.org/package=OBRE")
    (synopsis "Optimal B-Robust Estimator Tools")
    (description
     "An implementation for computing Optimal B-Robust Estimators of two-parameter
distribution.  The procedure is composed of some equations that are evaluated
alternatively until the solution is reached.  Some tools for analyzing the
estimates are included.  The most relevant is covariance matrix computation
using a closed formula.")
    (license license:gpl3+)))

(define-public r-obmbpkg
  (package
    (name "r-obmbpkg")
    (version "1.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OBMbpkg" version))
       (sha256
        (base32 "01wch8wwij3fd0jambk0hpkhlnp4ryrq8qnnr2w1iad9zssjyii5"))))
    (properties `((upstream-name . "OBMbpkg")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=OBMbpkg")
    (synopsis
     "Estimate the Population Size for the Mb Capture-Recapture Model")
    (description
     "Applies an objective Bayesian method to the Mb capture-recapture model to
estimate the population size N. The Mb model is a class of capture-recapture
methods used to account for variations in capture probability due to animal
behavior.  Under the Mb formulation, the initial capture of an animal may effect
the probability of subsequent captures due to their becoming \"trap happy\" or
\"trap shy.\".")
    (license license:gpl3)))

(define-public r-obliquersf
  (package
    (name "r-obliquersf")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "obliqueRSF" version))
       (sha256
        (base32 "1y9bkhwlb9aabfvnz62cg128c242hd1qdrwmmf6i76yfg0b0w10k"))))
    (properties `((upstream-name . "obliqueRSF")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr
                             r-survival
                             r-scales
                             r-rlang
                             r-rcpparmadillo
                             r-rcpp
                             r-purrr
                             r-prodlim
                             r-pec
                             r-missforest
                             r-glmnet
                             r-ggthemes
                             r-ggplot2
                             r-dplyr
                             r-data-table))
    (home-page "https://cran.r-project.org/package=obliqueRSF")
    (synopsis "Oblique Random Forests for Right-Censored Time-to-Event Data")
    (description
     "Oblique random survival forests incorporate linear combinations of input
variables into random survival forests (Ishwaran, 2008
<DOI:10.1214/08-AOAS169>).  Regularized Cox proportional hazard models (Simon,
2016 <DOI:10.18637/jss.v039.i05>) are used to identify optimal linear
combinations of input variables.")
    (license license:gpl3)))

(define-public r-oblicubes
  (package
    (name "r-oblicubes")
    (version "0.1.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oblicubes" version))
       (sha256
        (base32 "0656dfaz19bmcaiqh988lryj5gql39q8pwnl6c9fab07wwd85w3k"))))
    (properties `((upstream-name . "oblicubes")))
    (build-system r-build-system)
    (native-inputs (list r-rmarkdown r-knitr))
    (home-page "https://trevorldavis.com/R/oblicubes/")
    (synopsis "3D Rendering Using Obliquely Projected Cubes and Cuboids")
    (description
     "Three-dimensional rendering for grid and ggplot2 graphics using cubes and
cuboids drawn with an oblique projection.  As a special case also supports
primary view orthographic projections.  Can be viewed as an extension to the
isocubes package <https://github.com/coolbutuseless/isocubes>.")
    (license license:expat)))

(define-public r-obl
  (package
    (name "r-obl")
    (version "0.2.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OBL" version))
       (sha256
        (base32 "06icw1dnmavgaf51fs2nfi6582cpjrnlii1j9s62nwnwfnqw00v3"))))
    (properties `((upstream-name . "OBL")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-ggplot2
                             r-forecast
                             r-foreach
                             r-forcats
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=OBL")
    (synopsis "Optimum Block Length")
    (description
     "Obtain optimum block from Non-overlapping Block Bootstrap method.")
    (license license:gpl2+)))

(define-public r-objectsignals
  (package
    (name "r-objectsignals")
    (version "0.10.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "objectSignals" version))
       (sha256
        (base32 "087hknxhw3zqxrzdazbqw9zxi01dvrzcgm6k1i7r231vvvm6nxid"))))
    (properties `((upstream-name . "objectSignals")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=objectSignals")
    (synopsis "Observer Pattern for S4")
    (description
     "This package provides a mutable Signal object can report changes to its state,
clients could register functions so that they are called whenever the signal is
emitted.  The signal could be emitted, disconnected, blocked, unblocked, and
buffered.")
    (license license:gpl2+)))

(define-public r-objectremover
  (package
    (name "r-objectremover")
    (version "0.8.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "objectremover" version))
       (sha256
        (base32 "0qywigwb6r5lzvw8ylgriwignk4ayfkvfnmc6cb1yxsg0hrc4hiv"))))
    (properties `((upstream-name . "objectremover")))
    (build-system r-build-system)
    (propagated-inputs (list r-shiny r-miniui))
    (home-page "https://github.com/alan-y/objectremover")
    (synopsis
     "'RStudio' Addin for Removing Objects from the Global Environment Based on Patterns and Object Type")
    (description
     "An RStudio addin to assist with removing objects from the global environment.
Features include removing objects according to name patterns and object type.
During the course of an analysis, temporary objects are often created and this
tool assists with removing them quickly.  This can be useful when memory
management within R is important.")
    (license license:expat)))

(define-public r-objectproperties
  (package
    (name "r-objectproperties")
    (version "0.6.8")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "objectProperties" version))
       (sha256
        (base32 "02rbxp2w0q6sr3zvgj99a4hi8dldn57isvimfhqjm1j8yc8p3afz"))))
    (properties `((upstream-name . "objectProperties")))
    (build-system r-build-system)
    (propagated-inputs (list r-objectsignals))
    (home-page "https://cran.r-project.org/package=objectProperties")
    (synopsis "Factory of Self-Describing Properties")
    (description
     "Supports the definition of sets of properties on objects.  Observers can listen
to changes on individual properties or the set as a whole.  The properties are
meant to be fully self-describing.  In support of this, there is a framework for
defining enumerated types, as well as other bounded types, as S4 classes.")
    (license license:gpl2+)))

(define-public r-obic
  (package
    (name "r-obic")
    (version "3.0.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OBIC" version))
       (sha256
        (base32 "0bhmry7214i018r5cjxlrf07x5wbbg0aysish053wdcgrkzjplrs"))))
    (properties `((upstream-name . "OBIC")))
    (build-system r-build-system)
    (propagated-inputs (list r-data-table r-checkmate))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/AgroCares/Open-Bodem-Index-Calculator")
    (synopsis "Calculate the Open Bodem Index (OBI) Score")
    (description
     "The Open Bodem Index (OBI) is a method to evaluate the quality of soils of
agricultural fields in The Netherlands and the sustainability of the current
agricultural practices.  The OBI score is based on four main criteria: chemical,
physical, biological and management, which consist of more than 21 indicators.
By providing results of a soil analysis and management info the OBIC package can
be use to calculate he scores, indicators and derivatives that are used by the
OBI. More information about the Open Bodem Index can be found at
<https://openbodemindex.nl/>.")
    (license license:gpl3)))

(define-public r-obfuscator
  (package
    (name "r-obfuscator")
    (version "0.2.2")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "obfuscatoR" version))
       (sha256
        (base32 "1scd63giywfbvpynbxbk0kq01rwhx62416dibs5gky15dxfcsvmk"))))
    (properties `((upstream-name . "obfuscatoR")))
    (build-system r-build-system)
    (propagated-inputs (list r-tibble
                             r-stringr
                             r-rfast
                             r-readr
                             r-matrixstats
                             r-crayon))
    (native-inputs (list r-knitr))
    (home-page "https://obfuscator.edsandorf.me")
    (synopsis "Obfuscation Game Designs")
    (description
     "When people make decisions, they may do so using a wide variety of decision
rules.  The package allows users to easily create obfuscation games to test the
obfuscation hypothesis.  It provides an easy to use interface and multiple
options designed to vary the difficulty of the game and tailor it to the user's
needs.  For more detail: Chorus et al., 2021, Obfuscation maximization-based
decision-making: Theory, methodology and first empirical evidence, Mathematical
Social Sciences, 109, 28-44, <doi:10.1016/j.mathsocsci.2020.10.002>.")
    (license license:gpl3)))

(define-public r-obcost
  (package
    (name "r-obcost")
    (version "0.1.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "obcost" version))
       (sha256
        (base32 "1i2a4xzgagx9f8fs1jh9pgmvsd7hkyhhr3dj349fijbis6fvq6v5"))))
    (properties `((upstream-name . "obcost")))
    (build-system r-build-system)
    (propagated-inputs (list r-tidyr r-dplyr))
    (home-page "https://cran.r-project.org/package=obcost")
    (synopsis "Obesity Cost Database")
    (description
     "This database contains necessary data relevant to medical costs on obesity
throughout the United States.  This database, in form of an R package, could
output necessary data frames relevant to obesity costs, where the clients could
easily manipulate the output using difference parameters, e.g. relative risks
for each illnesses.  This package contributes to parts of our published journal
named \"Modeling the Economic Cost of Obesity Risk and Its Relation to the Health
Insurance Premium in the United States: A State Level Analysis\".  Please use the
following citation for the journal: Woods Thomas, Tatjana Miljkovic (2022)
\"Modeling the Economic Cost of Obesity Risk and Its Relation to the Health
Insurance Premium in the United States: A State Level Analysis\"
<doi:10.3390/risks10100197>.  The database is composed of the following main
tables: 1.  Relative_Risks: (constant) Relative risks for a given disease group
with a risk factor of obesity; 2.  Disease_Cost: (obesity_cost_disease)
Supplementary output with all variables related to individual disease groups in
a given state and year; 3.  Full_Cost: (obesity_cost_full) Complete output with
all variables used to make cost calculations, as well as cost calculations in a
given state and year; 4.  National_Summary: (obesity_cost_national_summary)
National summary cost calculations in a given year.  Three functions are
included to assist users in calling and adjusting the mentioned tables and they
are data_load(), data_produce(), and rel_risk_fun().")
    (license license:lgpl2.0+)))

(define-public r-obaspatial
  (package
    (name "r-obaspatial")
    (version "1.9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OBASpatial" version))
       (sha256
        (base32 "13jx5f5piii9cys7xyhfwilyg87zsi632fscy8902mlhbgg7abkp"))))
    (properties `((upstream-name . "OBASpatial")))
    (build-system r-build-system)
    (propagated-inputs (list r-truncdist
                             r-mvtnorm
                             r-modeest
                             r-laplacesdemon
                             r-invgamma
                             r-hdinterval
                             r-cubature))
    (home-page "https://cran.r-project.org/package=OBASpatial")
    (synopsis "Objective Bayesian Analysis for Spatial Regression Models")
    (description
     "It makes an objective Bayesian analysis of the spatial regression model using
both the normal (NSR) and student-T (TSR) distributions.  The functions provided
give prior and posterior objective densities and allow default Bayesian
estimation of the model regression parameters.  Details can be found in Ordonez
et al. (2020) <@code{arXiv:2004.04341>}.")
    (license license:gpl2+)))

(define-public r-obanalytics
  (package
    (name "r-obanalytics")
    (version "0.1.1")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "obAnalytics" version))
       (sha256
        (base32 "1l4ld120qk0adycmvqrkzada10kb7z03lj2njzqagmacl1z8598f"))))
    (properties `((upstream-name . "obAnalytics")))
    (build-system r-build-system)
    (propagated-inputs (list r-zoo r-reshape2 r-ggplot2))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/phil8192/ob-analytics")
    (synopsis "Limit Order Book Analytics")
    (description
     "Data processing, visualisation and analysis of Limit Order Book event data.")
    (license license:gpl2+)))

(define-public r-oaxaca
  (package
    (name "r-oaxaca")
    (version "0.1.5")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oaxaca" version))
       (sha256
        (base32 "1z3sbkgzaqq6n1bz0f17gqrbfjbm8bp20384ryx3jq2v50b6gbry"))))
    (properties `((upstream-name . "oaxaca")))
    (build-system r-build-system)
    (propagated-inputs (list r-reshape2 r-ggplot2 r-formula))
    (home-page "https://cran.r-project.org/package=oaxaca")
    (synopsis "Blinder-Oaxaca Decomposition")
    (description
     "An implementation of the Blinder-Oaxaca decomposition for linear regression
models.")
    (license license:gpl2+)))

(define-public r-oarray
  (package
    (name "r-oarray")
    (version "1.4-9")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "Oarray" version))
       (sha256
        (base32 "04jng89s19rd8lbjm76wm4p4ggkffwnsa5qa60c4lwn2rj89a8a1"))))
    (properties `((upstream-name . "Oarray")))
    (build-system r-build-system)
    (home-page "https://cran.r-project.org/package=Oarray")
    (synopsis "Arrays with Arbitrary Offsets")
    (description "Generalise the starting point of the array index.")
    (license (list license:gpl2+ license:gpl3+))))

(define-public r-oaqc
  (package
    (name "r-oaqc")
    (version "2.0.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oaqc" version))
       (sha256
        (base32 "0f777a8i03mb4f4q2zdacglyn0lbmf5b7c6682ssw2dlnm14jhz9"))))
    (properties `((upstream-name . "oaqc")))
    (build-system r-build-system)
    (native-inputs (list r-knitr))
    (home-page "https://github.com/schochastics/oaqc")
    (synopsis "Computation of the Orbit-Aware Quad Census")
    (description
     "This package implements the efficient algorithm by Ortmann and Brandes (2017)
<doi:10.1007/s41109-017-0027-2> to compute the orbit-aware frequency
distribution of induced and non-induced quads, i.e.  subgraphs of size four.
Given an edge matrix, data frame, or a graph object (e.g., igraph'), the
orbit-aware counts are computed respective each of the edges and nodes.")
    (license license:gpl3+)))

(define-public r-oaplots
  (package
    (name "r-oaplots")
    (version "0.0.25")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oaPlots" version))
       (sha256
        (base32 "0c5ig1ar02vg38pjjmp3gd53ij1j7pzajs0zrlfajz141qkv2ysr"))))
    (properties `((upstream-name . "oaPlots")))
    (build-system r-build-system)
    (propagated-inputs (list r-oacolors r-ggplot2))
    (home-page "http://www.openanalytics.eu")
    (synopsis "OpenAnalytics Plots Package")
    (description "Offers a suite of functions for enhancing R plots.")
    (license (license:fsdg-compatible "GPL-3 + file LICENSE"))))

(define-public r-oaii
  (package
    (name "r-oaii")
    (version "0.5.0")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oaii" version))
       (sha256
        (base32 "1kj86c3mydc8zylxx1s088iz6d1b02gixvy40d4qwxs55k07g9m0"))))
    (properties `((upstream-name . "oaii")))
    (build-system r-build-system)
    (propagated-inputs (list r-magrittr r-httr r-checkmate r-base64enc))
    (home-page "https://github.com/cezarykuran/oaii")
    (synopsis "'OpenAI' API R Interface")
    (description
     "This package provides a comprehensive set of helpers that streamline data
transmission and processing, making it effortless to interact with the
@code{OpenAI} API.")
    (license license:expat)))

(define-public r-oaiharvester
  (package
    (name "r-oaiharvester")
    (version "0.3-4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "OAIHarvester" version))
       (sha256
        (base32 "0b5v275w0c7y073fgwiy966djrw6p1zggzqlywa2fsdn2p0aq56w"))))
    (properties `((upstream-name . "OAIHarvester")))
    (build-system r-build-system)
    (propagated-inputs (list r-xml2 r-curl))
    (home-page "https://cran.r-project.org/package=OAIHarvester")
    (synopsis "Harvest Metadata Using OAI-PMH Version 2.0")
    (description
     "Harvest metadata using the Open Archives Initiative Protocol for Metadata
Harvesting (OAI-PMH) version 2.0 (for more information, see
<https://www.openarchives.org/OAI/openarchivesprotocol.html>).")
    (license license:gpl2)))

(define-public r-oacolors
  (package
    (name "r-oacolors")
    (version "0.0.4")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "oaColors" version))
       (sha256
        (base32 "040sdqrk9dciylnnrrshlj06s9qhvngii9shx1p8412ip7mk8r1m"))))
    (properties `((upstream-name . "oaColors")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcolorbrewer r-mass))
    (home-page "http://www.openanalytics.eu")
    (synopsis "OpenAnalytics Colors Package")
    (description
     "This package provides carefully chosen color palettes as used a.o.  at
@code{OpenAnalytics} <http://www.openanalytics.eu>.")
    (license (license:fsdg-compatible "GPL-3 + file LICENSE"))))

(define-public r-o2plsda
  (package
    (name "r-o2plsda")
    (version "0.0.25")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "o2plsda" version))
       (sha256
        (base32 "1lsww2g9inpaw7mhg49ia517am14sjvy9i92h2xsfv4qygqkl1wq"))))
    (properties `((upstream-name . "o2plsda")))
    (build-system r-build-system)
    (propagated-inputs (list r-rcpparmadillo
                             r-rcpp
                             r-magrittr
                             r-ggrepel
                             r-ggplot2
                             r-dplyr))
    (native-inputs (list r-knitr))
    (home-page "https://cran.r-project.org/package=o2plsda")
    (synopsis "Multiomics Data Integration")
    (description
     "This package provides functions to do O2PLS-DA analysis for multiple omics data
integration.  The algorithm came from \"O2-PLS, a two-block (XÂ±Y) latent
variable regression (LVR) method with an integral OSC filter\" which published by
Johan Trygg and Svante Wold at 2003 <doi:10.1002/cem.775>.  O2PLS is a
bidirectional multivariate regression method that aims to separate the
covariance between two data sets (it was recently extended to multiple data
sets) (LÃ¶fstedt and Trygg, 2011 <doi:10.1002/cem.1388>; LÃ¶fstedt et al., 2012
<doi:10.1016/j.aca.2013.06.026>) from the systematic sources of variance being
specific for each data set separately.")
    (license license:gpl3)))

(define-public r-o2geosocial
  (package
    (name "r-o2geosocial")
    (version "1.1.3")
    (source
     (origin
       (method url-fetch)
       (uri (cran-uri "o2geosocial" version))
       (sha256
        (base32 "044m21116zwbkh55z84pns5l3agvdw50pcza669blmf3za7m2bby"))))
    (properties `((upstream-name . "o2geosocial")))
    (build-system r-build-system)
    (propagated-inputs (list r-visnetwork
                             r-rcpp
                             r-outbreaker2
                             r-ggplot2
                             r-geosphere
                             r-data-table))
    (native-inputs (list r-knitr))
    (home-page "https://github.com/alxsrobert/o2geosocial")
    (synopsis "Reconstruction of Transmission Chains from Surveillance Data")
    (description
     "Bayesian reconstruction of who infected whom during past outbreaks using
routinely-collected surveillance data.  Inference of transmission trees using
genotype, age specific social contacts, distance between cases and onset dates
of the reported cases. (Robert A, Kucharski AJ, Gastanaduy PA, Paul P, Funk S.
(2020) <doi:10.1098/rsif.2020.0084>).")
    (license license:expat)))

