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

Last updated: April 27,2024

1. Install "r-cran-bayesm" package

In this section, we are going to explain the necessary steps to install r-cran-bayesm on Ubuntu 20.10 (Groovy Gorilla)

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

2. Uninstall "r-cran-bayesm" package

In this section, we are going to explain the necessary steps to uninstall r-cran-bayesm on Ubuntu 20.10 (Groovy Gorilla):

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

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

Package: r-cran-bayesm
Architecture: amd64
Version: 3.1-4+dfsg-1build2
Priority: optional
Section: universe/math
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian R Packages Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 3017
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-rcpp (>= 0.12.0), r-cran-rcpparmadillo, libblas3 | libblas.so.3, libc6 (>= 2.29), libgcc-s1 (>= 3.0), liblapack3 | liblapack.so.3, libstdc++6 (>= 9)
Recommends: r-cran-knitr, r-cran-rmarkdown
Filename: pool/universe/r/r-cran-bayesm/r-cran-bayesm_3.1-4+dfsg-1build2_amd64.deb
Size: 1954380
MD5sum: 3d11d8145a88f7c37ea31310a0063eac
SHA1: fd4d79c7e4e9aafa6c33b61816bbb8e6d8ec5369
SHA256: 7f9d79da6b6d105ade37379abf390caca86d607d733c38e248613a0fd6ecd1f8
SHA512: c52ac1f5d8ee76daeca7b40698b00cbf3ce8b6179bd9e3950f02b8ee62b5e35a444706d462d2550f80903498b2a21da9591242772fe79bf012c60216f5e0b154
Homepage: https://cran.r-project.org/package=bayesm
Description-en: GNU R package for Bayesian inference
The bayesm package covers many important models used in marketing and
micro-econometrics applications. The package includes:
.
* Bayes Regression (univariate or multivariate dep var)
* Multinomial Logit (MNL) and Multinomial Probit (MNP)
* Multivariate Probit,
* Multivariate Mixtures of Normals
* Hierarchical Linear Models with normal prior and covariates
* Hierarchical Multinomial Logits with mixture of normals prior and
covariates
* Bayesian analysis of choice-based conjoint data
* Bayesian treatment of linear instrumental variables models
* Analyis of Multivariate Ordinal survey data with scale usage heterogeneity
(as in Rossi et al, JASA (01)).
.
For further reference, consult the authors' book, _Bayesian Statistics and
Marketing_ by Allenby, McCulloch and Rossi.
Description-md5: 6f649751db2fffd16683aa065ef0eeca