How to Install and Uninstall r-cran-mcmc Package on Kali Linux
Last updated: November 26,2024
1. Install "r-cran-mcmc" package
This tutorial shows how to install r-cran-mcmc on Kali Linux
$
sudo apt update
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$
sudo apt install
r-cran-mcmc
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2. Uninstall "r-cran-mcmc" package
This guide covers the steps necessary to uninstall r-cran-mcmc on Kali Linux:
$
sudo apt remove
r-cran-mcmc
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$
sudo apt autoclean && sudo apt autoremove
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3. Information about the r-cran-mcmc package on Kali Linux
Package: r-cran-mcmc
Version: 0.9-8-1
Installed-Size: 1703
Maintainer: Debian R Packages Maintainers
Architecture: amd64
Depends: r-api-4.0, libc6 (>= 2.4)
Recommends: r-cran-xtable, r-cran-iso
Enhances: r-cran-mcmcpack
Size: 1230672
SHA256: f0a0068651e8c4a29119ee5440a4a0e5f0ab3fcddb4d7f75b915828a20fa7983
SHA1: fe37d4350b5b7a09d8d07a866a0a1929ffc6a1f8
MD5sum: 673899c9ba9b82a6dfe3a2d729dc1f3e
Description: GNU R package for Markov Chain Monte Carlo simulations
Simulates continuous distributions of random vectors using Markov
chain Monte Carlo (MCMC). Users specify the distribution by an R
function that evaluates the log unnormalized density. Algorithms are
random walk Metropolis algorithm (function metrop), simulated
tempering (function temper), and morphometric random walk Metropolis
(Johnson and Geyer, Annals of Statistics, 2012, function
morph.metrop), which achieves geometric ergodicity by change of
variable.
Description-md5:
Homepage: https://cran.r-project.org/package=mcmc
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-cran-mcmc/r-cran-mcmc_0.9-8-1_amd64.deb
Version: 0.9-8-1
Installed-Size: 1703
Maintainer: Debian R Packages Maintainers
Architecture: amd64
Depends: r-api-4.0, libc6 (>= 2.4)
Recommends: r-cran-xtable, r-cran-iso
Enhances: r-cran-mcmcpack
Size: 1230672
SHA256: f0a0068651e8c4a29119ee5440a4a0e5f0ab3fcddb4d7f75b915828a20fa7983
SHA1: fe37d4350b5b7a09d8d07a866a0a1929ffc6a1f8
MD5sum: 673899c9ba9b82a6dfe3a2d729dc1f3e
Description: GNU R package for Markov Chain Monte Carlo simulations
Simulates continuous distributions of random vectors using Markov
chain Monte Carlo (MCMC). Users specify the distribution by an R
function that evaluates the log unnormalized density. Algorithms are
random walk Metropolis algorithm (function metrop), simulated
tempering (function temper), and morphometric random walk Metropolis
(Johnson and Geyer, Annals of Statistics, 2012, function
morph.metrop), which achieves geometric ergodicity by change of
variable.
Description-md5:
Homepage: https://cran.r-project.org/package=mcmc
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-cran-mcmc/r-cran-mcmc_0.9-8-1_amd64.deb