How to Install and Uninstall r-cran-bayesfactor Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 12,2024

1. Install "r-cran-bayesfactor" package

Here is a brief guide to show you how to install r-cran-bayesfactor on Ubuntu 21.10 (Impish Indri)

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

2. Uninstall "r-cran-bayesfactor" package

Please follow the steps below to uninstall r-cran-bayesfactor on Ubuntu 21.10 (Impish Indri):

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

3. Information about the r-cran-bayesfactor package on Ubuntu 21.10 (Impish Indri)

Package: r-cran-bayesfactor
Architecture: amd64
Version: 0.9.12-4.2+dfsg-1
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: 1667
Depends: r-base-core (>= 4.0.2-1build1), 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+dfsg-1_amd64.deb
Size: 959380
MD5sum: eca94788a85e2112b21bcafd3573d3f7
SHA1: 009568b0a99a7cbc34abb26814852ea39f2bdc1b
SHA256: c85578539b5e3d9dd3a6a51608f53539c6e43ebe074edb2cfdee503514f47d5e
SHA512: 47c88fa820c95500ec1bd5d1493b0c3c7a76c9ce92666714f49816e43b133266efca0576bef04d83a09ca8ffb9a33586c59c08166fbf6b469b7eaa77f9183549
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