How to Install and Uninstall r-cran-bayesfactor Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: April 28,2024

1. Install "r-cran-bayesfactor" package

This is a short guide on how to install r-cran-bayesfactor on Ubuntu 20.10 (Groovy Gorilla)

$ sudo apt update $ sudo apt install r-cran-bayesfactor

2. Uninstall "r-cran-bayesfactor" package

Please follow the guidelines below to uninstall r-cran-bayesfactor on Ubuntu 20.10 (Groovy Gorilla):

$ sudo apt remove r-cran-bayesfactor $ sudo apt autoclean && sudo apt autoremove

3. Information about the r-cran-bayesfactor package on Ubuntu 20.10 (Groovy Gorilla)

Package: r-cran-bayesfactor
Architecture: amd64
Version: 0.9.12-4.2-1build3
Priority: optional
Section: universe/gnu-r
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian R Packages Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 7023
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-coda, r-cran-matrix (>= 1.1-1), r-cran-pbapply, r-cran-mvtnorm, r-cran-stringr, r-cran-gtools, r-cran-matrixmodels, r-cran-rcpp (>= 0.11.2), r-cran-hypergeo, r-cran-rcppeigen (>= 0.3.2.2.0), libc6 (>= 2.29), libgcc-s1 (>= 3.0), libstdc++6 (>= 5.2)
Recommends: r-cran-testthat
Suggests: r-cran-domc, r-cran-foreach, r-cran-knitr, r-cran-markdown, r-cran-arm, r-cran-lme4, r-cran-xtable
Filename: pool/universe/r/r-cran-bayesfactor/r-cran-bayesfactor_0.9.12-4.2-1build3_amd64.deb
Size: 4121712
MD5sum: 0d03c4d13b3d7620a12b8c7bfe1ccd45
SHA1: 5240515ff1bac7198784554a1007fc5f02951c99
SHA256: 509a739fc19e81f2319c7f9aaa2f2e5209ba6fbe5bdea2455ed14ae7331acf79
SHA512: b527327a7090df9d6e78ec4ec17cb97deab0c106b8d801d22a52f3263f950bd8d5146d878102c59e19d4b669451c177cc27574936a44d05f3f400ab08a2332a3
Homepage: https://cran.r-project.org/package=BayesFactor
Description-en: GNU R Bayes factors for t-tests, ANOVAs and contingency tables
r-cran-bayesfactor is a GNU R package providing a suite of functions for
computing various Bayes factors for simple designs, including
contingency tables, one- and two-sample designs, one- way designs,
general ANOVA designs, and linear regression.
Description-md5: 06d60c3d3dde73181a4abfe2f8692d24