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

Last updated: May 20,2024

1. Install "r-cran-rms" package

Please follow the steps below to install r-cran-rms on Ubuntu 21.10 (Impish Indri)

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

2. Uninstall "r-cran-rms" package

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

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

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

Package: r-cran-rms
Architecture: amd64
Version: 6.2-0-1
Priority: optional
Section: universe/gnu-r
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Dirk Eddelbuettel
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 2418
Depends: libc6 (>= 2.29), r-base-core (>= 4.0.4-1build1), r-api-4.0, r-cran-hmisc (>= 4.3-0), r-cran-survival (>= 3.1-12), r-cran-lattice, r-cran-ggplot2 (>= 2.2), r-cran-sparsem, r-cran-quantreg, r-cran-rpart, r-cran-nlme (>= 3.1-123), r-cran-polspline, r-cran-multcomp, r-cran-htmltable (>= 1.11.0), r-cran-htmltools, r-cran-mass, r-cran-cluster, r-cran-digest, r-cran-foreign, r-cran-nnet
Conflicts: r-noncran-design
Replaces: r-noncran-design
Filename: pool/universe/r/r-cran-rms/r-cran-rms_6.2-0-1_amd64.deb
Size: 2106124
MD5sum: 6feeae4a0a164668193ab6ed012b0c66
SHA1: 1f9151b69d7c334e87fe0ec291a201c5dd969f8e
SHA256: bbea33679fd1ae9aeedb6e2db3eafb030c5f14fc6ef746eec92ef136b9554d59
SHA512: 9bbb9bf3e166875067127adb7ddcc5a849412ffecf08481e74890b0c7325c807dc551ea7731dcbceb6ae2676cfdceb7e00bae585a2140531c062578db753c73b
Homepage: https://cran.r-project.org/package=rms
Description-en: GNU R regression modeling strategies by Frank Harrell
Regression modeling, testing, estimation, validation, graphics,
prediction, and typesetting by storing enhanced model design
attributes in the fit. rms is a collection of 229 functions that
assist with and streamline modeling. It also contains functions for
binary and ordinal logistic regression models and the Buckley-James
multiple regression model for right-censored responses, and implements
penalized maximum likelihood estimation for logistic and ordinary
linear models. rms works with almost any regression model, but it
was especially written to work with binary or ordinal logistic
regression, Cox regression, accelerated failure time models,
ordinary linear models, the Buckley-James model, generalized least
squares for serially or spatially correlated observations, generalized
linear models, and quantile regression.
.
See Frank Harrell (2001), Regression Modeling Strategies, Springer
Series in Statistics, as well as http://biostat.mc.vanderbilt.edu/Rrms.
Description-md5: 9fe79ccc22f1a3025abc6da6b5e51bde