k3ylabs/cosoco-image-dataset huggingface dataset:
Package: r-cran-bdgraph (2.64-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=BDgraph
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-igraph, libblas3 | libblas.so.3, libc6 (>= 2.29), libgcc-s1 (>= 3.3.1), libgomp1 (>= 4.9), liblapack3 | liblapack.so.3, libstdc++6 (>= 11)
Description:  GNU R bayesian structure learning in graphical models Statistical tools for Bayesian structure learning in undirected graphical models for continuous, discrete, and mixed data. The package is implemented the recent improvements in the Bayesian graphical models literature, including Mohammadi and Wit (2015) <doi:10.1214/14-BA889>, Mohammadi and Wit (2019) <doi:10.18637/jss.v089.i03>.
Package: r-cran-bdsmatrix (1.3-4-1build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=bdsmatrix
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0
Description:  GNU R routines for block diagonal symmetric matrices Provides an R class for block diagonal symmetric matrices, allowing them to be manipulated much like an ordinary matrix, but the total memory use can be much smaller. . Also provides a solver for such matrices, and generalized Cholesky decomposition routines for both symmetric and block diagonal symmetric matrices.
Package: r-cran-beeswarm (0.4.0-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=beeswarm
Depends: r-base-core (>= 4.1.1-2), r-api-4.0
Description:  bee swarm plot, an alternative to stripchart Beeswarm is an add-on package for the R statistical environment. The bee swarm plot is a one-dimensional scatter plot like "stripchart", but with closely-packed, non-overlapping points.
Package: r-cran-bench (1.1.2-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=bench
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-cran-glue, r-cran-pillar, r-cran-profmem, r-cran-rlang (>= 0.2.0), r-cran-tibble (>= 3.0.1), libc6 (>= 2.17)
Description:  High Precision Timing of R Expressions Tools to accurately benchmark and analyze execution times for R expressions.
Package: r-cran-benchmarkme (1.0.7-2)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=benchmarkme
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-benchmarkmedata (>= 1.0.4), r-cran-doparallel, r-cran-dplyr, r-cran-foreach, r-cran-httr, r-cran-matrix, r-cran-tibble
Description:  GNU R crowd sourced system benchmarks Benchmark your CPU and compare against other CPUs. Also provides functions for obtaining system specifications, such as RAM, CPU type, and R version.
Package: r-cran-benchmarkmedata (1.0.4-2)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=benchmarkmeData
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-dplyr, r-cran-tibble
Description:  GNU R data set for the 'benchmarkme' package This GNU R package crowd sourced benchmarks from running the 'benchmarkme' package.
Package: r-cran-bh (1.74.0-2)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=BH
Depends: libboost-dev (>= 1.74.0)
Description:  (Virtual) GNU R package to provide BH The CRAN package BH provides a (large) subset of Boost.  This package tricks R into believing BH is installed when we just depend on the distribution's Boost packages.  The actual set of Boost libraries could get fine-tuned. In short, we avoid doubling up the 140+ mb of the 'BH' package which are alredy in libboost-dev.
Package: r-cran-biasedurn (1.07-4)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=BiasedUrn
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, libc6 (>= 2.29), libstdc++6 (>= 4.1.1)
Description:  GNU R Biased Urn model distributions Statistical models of biased sampling in the form of univariate and multivariate noncentral hypergeometric distributions, including Wallenius' noncentral hypergeometric distribution and Fisher's noncentral hypergeometric distribution (also called extended hypergeometric distribution). See vignette("UrnTheory") for explanation of these distributions.
Package: r-cran-bibtex (0.4.2.3-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=bibtex
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, r-cran-stringr, libc6 (>= 2.14)
Description:  GNU R Bibtex Parser This package provides a utility to parse a bibtex file with GNU R.
Package: r-cran-bigmemory.sri (0.1.3-3build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=bigmemory.sri
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0
Description:  Shared resource interface for Bigmemory Project packages This package provides a shared resource interface for the bigmemory and synchronicity packages.
Package: r-cran-bigmemory (4.5.36-1build2)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=bigmemory
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-rcpp, r-cran-bigmemory.sri, r-cran-bh, libc6 (>= 2.14), libgcc-s1 (>= 3.0), libstdc++6 (>= 5.2)
Description:  Manage Massive Matrices with Shared Memory and Memory-Mapped Files Create, store, access, and manipulate massive matrices. Matrices are allocated to shared memory and may use memory-mapped files.  Packages 'biganalytics', 'bigtabulate', 'synchronicity', and 'bigalgebra' provide advanced functionality.
Package: r-cran-bindr (0.1.1-3build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=bindr
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0
Description:  Parametrized Active Bindings for GNU R This package provides a simple interface for creating active bindings where the bound function accepts additional arguments for GNU R.
Package: r-cran-bindrcpp (0.2.2-3)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=bindrcpp
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, r-cran-bindr (>= 0.1.1), r-cran-rcpp (>= 0.12.16), r-cran-plogr, libc6 (>= 2.14), libgcc-s1 (>= 3.0), libstdc++6 (>= 5.2)
Description:  GNU R 'Rcpp' Interface to Active Bindings This GNU R package provides an easy way to fill an environment with active bindings that call a C++ function.
Package: r-cran-bio3d (2.4-2-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=bio3d
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-rcpp, libc6 (>= 2.14), libgcc-s1 (>= 3.3.1), libstdc++6 (>= 9), zlib1g (>= 1:1.1.4)
Description:  GNU R package for biological structure analysis The bio3d package contains utilities to process, organize and explore protein structure, sequence and dynamics data.  Features include the ability to read and write structure, sequence and dynamic trajectory data, perform atom summaries, atom selection, re-orientation, superposition, rigid core identification, clustering, torsion analysis, distance matrix analysis, structure and sequence conservation analysis, and principal component analysis (PCA).  In addition, various utility functions are provided to enable the statistical and graphical power of the R environment to work with biological sequence and structural data.
Package: r-cran-biocmanager (1.30.16+dfsg-3)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=BiocManager
Depends: r-base-core (>= 4.1.1-2), r-api-4.0
Description:  access the Bioconductor project package repository A convenient tool to install and update Bioconductor packages.
Package: r-cran-bios2cor (2.2-2)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=Bios2cor
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, r-cran-bio3d, r-cran-circular, r-cran-bigmemory, r-cran-igraph
Description:  GNU R from Biological Sequences and Simulations to Correlation Analysis Utilities for computation and analysis of correlation/covariation in multiple sequence alignments and in side chain motions during molecular dynamics simulations. Features include the computation of correlation/covariation scores using a variety of scoring functions between either sequence positions in alignments or side chain dihedral angles in molecular dynamics simulations and utilities to analyze the correlation/covariation matrix through a variety of tools including network representation and principal components analysis. In addition, several utility functions are based on the R graphical environment to provide friendly tools for help in data interpretation. Examples of sequence covariation analysis are provided in: (1) Pele J, Moreau M, Abdi H, Rodien P, Castel H, Chabbert M (2014) <doi:10.1002/prot.24570> and (2) Taddese B, Deniaud M, Garnier A, Tiss A, Guissouma H, Abdi H, Henrion D, Chabbert M (2018) <doi: 10.1371/journal.pcbi.1006209>. An example of side chain correlated motion analysis is provided in: Taddese B, Garnier A, Abdi H, Henrion D, Chabbert M (2020) <doi: 10.1038/s41598-020-72766- 1>. This work was supported by the French National Research Agency (Grant number: ANR-11-BSV2-026) and by GENCI (Grant number: 100567).
Package: r-cran-bit64 (4.0.5-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=bit64
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, r-cran-bit (>= 4.0.0), libc6 (>= 2.29)
Description:  GNU R S3 Class for Vectors of 64bit Integers Package 'bit64' provides serializable S3 atomic 64bit (signed) integers. These are useful for handling database keys and exact counting in +-2^63. WARNING: do not use them as replacement for 32bit integers, integer64 are not supported for subscripting by R-core and they have different semantics when combined with double, e.g. integer64 + double => integer64. Class integer64 can be used in vectors, matrices, arrays and data.frames. Methods are available for coercion from and to logicals, integers, doubles, characters and factors as well as many elementwise and summary functions. Many fast algorithmic operations such as 'match' and 'order' support interactive data exploration and manipulation and optionally leverage caching.
Package: r-cran-bit (4.0.4+dfsg-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=bit
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, libc6 (>= 2.4)
Description:  GNU R class for vectors of 1-bit booleans This GNU R package provides bitmapped vectors of booleans (no NAs), coercion from and to logicals, integers and integer subscripts; fast boolean operators and fast summary statistics. With 'bit' vectors you can store true binary booleans {FALSE,TRUE} at the expense of 1 bit only, on a 32 bit architecture this means factor 32 less RAM and ~ factor 32 more speed on boolean operations. Due to overhead of R calls, actual speed gain depends on the size of the vector: expect gains for vectors of size > 10000 elements. Even for one-time boolean operations it can pay-off to convert to bit, the pay-off is obvious, when such components are used more than once. . Reading from and writing to bit is approximately as fast as accessing standard logicals - mostly due to R's time for memory allocation. The package allows one to work with pre-allocated memory for return values by calling .Call() directly: when evaluating the speed of C-access with pre-allocated vector memory, coping from bit to logical requires only 70% of the time for copying from logical to logical; and copying from logical to bit comes at a performance penalty of 150%. the package now contains further classes for representing logical selections: 'bitwhich' for very skewed selections and 'ri' for selecting ranges of values for chunked processing. All three index classes can be used for subsetting 'ff' objects (ff-2.1-0 and higher).
Package: r-cran-bitops (1.0-7-1)
Section: universe/math
Homepage: https://cran.r-project.org/package=bitops
Depends: r-base-core (>= 4.1.1-2), r-api-4.0
Description:  GNU R package implementing bitwise operations Functions for bitwise operations on integer vectors. . This package of R programming tools for plotting data was written by Steve Dutky <sdutky@terpalum.umd.edu> with parts by Martin Maechler.
Package: r-cran-biwt (1.0-2build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=biwt
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-rrcov, r-cran-mass
Description:  biweight mean vector and covariance and correlation Compute multivariate location, scale, and correlation estimates based on Tukey's biweight M-estimator.
Package: r-cran-blme (1.0-5-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=blme
Depends: r-base-core (>= 4.0.3-1), r-api-4.0, r-cran-lme4 (>= 1.0-6)
Description:  GNU R Bayesian linear mixed-effects models Maximum a posteriori estimation for linear and generalized linear mixed-effects models in a Bayesian setting. Extends 'lme4' by Douglas Bates, Martin Maechler, Ben Bolker, and Steve Walker.
Package: r-cran-blob (1.2.2-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=blob
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-rlang, r-cran-vctrs (>= 0.2.1)
Description:  GNU R S3 Class for Representing Vectors of Binary Data ('BLOBS') R's raw vector is useful for storing a single binary object. What if you want to put a vector of them in a data frame? The blob package provides the blob object, a list of raw vectors, suitable for use as a column in data frame.
Package: r-cran-blockmodeling (1.0.5-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=blockmodeling
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-matrix, libc6 (>= 2.29)
Description:  Generalized and classical blockmodeling of valued networks This R package is primarly meant as an implementation of Generalized blockmodeling for valued networks. In addition, measurese of similarity or dissimilarity based on structural equivalence and regular equivalence (REGE algorithm) can be computed and partitioned matrices can be ploted.
Package: r-cran-bms (0.3.4-6build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=BMS
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0
Description:  GNU R package for Bayesian model averaging for linear models r-cran-bms is a GNU Package for Bayesian model averaging for linear models with a wide choice of (customizable) priors. Built-in priors include coefficient priors (fixed, flexible and hyper-g priors), 5 kinds of model priors, moreover model sampling by enumeration or various MCMC approaches.
Package: r-cran-bold (1.2.0-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=bold
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-xml2, r-cran-crul (>= 0.3.8), r-cran-stringr, r-cran-jsonlite, r-cran-reshape, r-cran-plyr, r-cran-data.table, r-cran-tibble
Description:  GNU R interface to Bold Systems for genetic barcode data A programmatic interface to the Web Service methods provided by Bold Systems for genetic barcode data. Functions include methods for searching by sequences by taxonomic names, ids, collectors, and institutions; as well as a function for searching for specimens, and downloading trace files.
Package: r-cran-bookdown (0.21+dfsg-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=bookdown
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, r-cran-htmltools (>= 0.3.6), r-cran-knitr (>= 1.22), r-cran-rmarkdown (>= 2.4), r-cran-xfun (>= 0.13), r-cran-tinytex (>= 0.12), r-cran-yaml (>= 2.1.19), libjs-jquery, libjs-lunr, fonts-font-awesome
Description:  authoring books and technical documents with GNU R markdown The bookdown package is a GNU R package that facilitates writing books and long-form articles/reports with R Markdown. Features include: .  * Generate printer-ready books and ebooks from R Markdown documents.  * A markup language easier to learn than LaTeX, and to write elements    such as section headers, lists, quotes, figures, tables, and    citations.  * Multiple choices of output formats: PDF, LaTeX, HTML, EPUB, and Word.  * Possibility of including dynamic graphics and interactive    applications (HTML widgets and Shiny apps).  * Support a wide range of languages: R, C/C++, Python, Fortran, Julia,    Shell scripts, and SQL, etc.  * LaTeX equations, theorems, and proofs work for all output formats.  * Can be published to GitHub, bookdown.org, and any web servers.  * Integrated with the RStudio IDE.  * One-click publishing to https://bookdown.org.
Package: r-cran-boolnet (2.1.5-3)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=BoolNet
Depends: r-base-core (>= 4.0.2-1build1), r-api-4.0, r-cran-igraph (>= 0.6), r-cran-xml, libc6 (>= 2.14)
Description:  assembling, analyzing and visualizing Boolean networks BoolNet is an R package that provides tools for assembling, analyzing and visualizing synchronous and asynchronous Boolean networks as well as probabilistic Boolean networks.
Package: r-cran-boot (1.3-28-2)
Section: universe/math
Homepage: https://cran.r-project.org/package=boot
Depends: r-base-core (>= 4.1.1-2), r-api-4.0
Description:  GNU R package for bootstrapping functions from Davison and Hinkley This package provides functions and datasets from the book "Bootstrap Methods and Their Applications" by A. C. Davison and D. V. Hinkley (1997, CUP). It was witten by Angelo Canty, and ported to R by Brian Ripley. . This package is part of the set of packages that are 'recommended' by R Core and shipped with upstream source releases of R itself.
Package: r-cran-bradleyterry2 (1.1-2-2build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=BradleyTerry2
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-brglm, r-cran-gtools, r-cran-lme4 (>= 1.0), r-cran-qvcalc
Description:  GNU R package for using Bradley-Terry models Specify and fit the Bradley-Terry model, including structured versions in which the parameters are related to explanatory variables through a linear predictor and versions with contest-specific effects, such as a home advantage.
Package: r-cran-brew (1.0-7-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=brew
Depends: r-base-core (>= 4.1.2-1ubuntu2), r-api-4.0
Description:  GNU R templating framework for report generation The GNU R package brew implements a templating framework for mixing text and R code for report generation. brew template syntax is similar to PHP, Ruby's erb module, Java Server Pages, and Python's psp module.
Package: r-cran-brglm (0.7.2-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=brglm
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-profilemodel
Description:  GNU R package for bias reduction in binomial-response GLMs Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'.  More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
Package: r-cran-bridgesampling (1.1-2-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=bridgesampling
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-mvtnorm, r-cran-matrix, r-cran-brobdingnag, r-cran-stringr, r-cran-coda, r-cran-scales
Description:  GNU R bridge sampling for marginal likelihoods and Bayes factors Provides functions for estimating marginal likelihoods, Bayes factors, posterior model probabilities, and normalizing constants in general, via different versions of bridge sampling (Meng & Wong, 1996, <http://www3.stat.sinica.edu.tw/statistica/j6n4/j6n43/j6n43.htm>).
Package: r-cran-brio (1.1.3-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=brio
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, libc6 (>= 2.14)
Description:  basic R input output Functions to handle basic input output, these functions always read and write UTF-8 (8-bit Unicode Transformation Format) files and provide more explicit control over line endings.
Package: r-cran-brms (2.16.3-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=brms
Depends: r-base-core (>= 4.1.2-1ubuntu1), r-api-4.0, r-cran-rcpp (>= 0.12.0), r-cran-rstan (>= 2.19.2), r-cran-ggplot2 (>= 2.0.0), r-cran-loo (>= 2.3.1), r-cran-posterior (>= 1.0.0), r-cran-matrix (>= 1.1.1), r-cran-mgcv (>= 1.8-13), r-cran-rstantools (>= 2.1.1), r-cran-bayesplot (>= 1.5.0), r-cran-shinystan (>= 2.4.0), r-cran-bridgesampling (>= 0.3-0), r-cran-glue (>= 1.3.0), r-cran-future (>= 1.19.0), r-cran-matrixstats, r-cran-nleqslv, r-cran-nlme, r-cran-coda, r-cran-abind, r-cran-backports
Description:  GNU R Bayesian regression models using 'Stan' Fit Bayesian generalized (non-)linear multivariate multilevel models using 'Stan' for full Bayesian inference. A wide range of distributions and link functions are supported, allowing users to fit -- among others  -- linear, robust linear, count data, survival, response times, ordinal, zero-inflated, hurdle, and even self-defined mixture models all in a multilevel context. Further modeling options include non-linear and smooth terms, auto-correlation structures, censored data, meta-analytic standard errors, and quite a few more. In addition, all parameters of the response distribution can be predicted in order to perform distributional regression. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their beliefs. Model fit can easily be assessed and compared with posterior predictive checks and leave-one-out cross-validation.
Package: r-cran-brobdingnag (1.2-7-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=Brobdingnag
Depends: r-base-core (>= 4.1.2-1ubuntu2), r-api-4.0
Description:  Very Large Numbers in R Handles very large numbers in R.  Real numbers are held using their natural logarithms, plus a logical flag indicating sign.  The package includes a vignette that gives a step-by-step introduction to using S4 methods.
Package: r-cran-broom.mixed (0.2.7-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=broom.mixed
Depends: r-base-core (>= 4.1.1-2), r-api-4.0, r-cran-broom, r-cran-coda, r-cran-dplyr, r-cran-nlme, r-cran-purrr, r-cran-stringr, r-cran-tibble, r-cran-tidyr
Description:  GNU R tidying methods for mixed models Convert fitted objects from various R mixed-model packages into tidy data frames along the lines of the 'broom' package. The package provides three S3 generics for each model: tidy(), which summarizes a model's statistical findings such as coefficients of a regression; augment(), which adds columns to the original data such as predictions, residuals and cluster assignments; and glance(), which provides a one-row summary of model-level statistics.
Package: r-cran-broom (0.7.12+dfsg-1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=broom
Depends: r-base-core (>= 4.1.2-1ubuntu2), r-api-4.0, r-cran-backports, r-cran-dplyr (>= 1.0.0), r-cran-ellipsis, r-cran-generics (>= 0.0.2), r-cran-glue, r-cran-purrr, r-cran-rlang, r-cran-stringr, r-cran-tibble (>= 3.0.0), r-cran-tidyr (>= 1.0.0), r-cran-ggplot2
Description:  convert statistical analysis objects into tidy data frames with GNU R Convert statistical analysis objects from R into tidy data frames, so that they can more easily be combined, reshaped and otherwise processed with tools like 'dplyr', 'tidyr' and 'ggplot2'. The package provides three S3 generics: tidy, which summarizes a model's statistical findings such as coefficients of a regression; augment, which adds columns to the original data such as predictions, residuals and cluster assignments; and glance, which provides a one-row summary of model-level statistics.
Package: r-cran-ca (0.71.1-2build1)
Section: universe/gnu-r
Homepage: https://cran.r-project.org/package=ca
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0
Description:  GNU R package for simple, multiple and joint correspondence analysis r-cran-ca is a GNU R package for computation and visualization of simple, multiple and joint correspondence analysis