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

Last updated: July 05,2024

1. Install "r-cran-mcmcpack" package

This guide covers the steps necessary to install r-cran-mcmcpack on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                r-cran-mcmcpack
            
                    
    
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2. Uninstall "r-cran-mcmcpack" package

This is a short guide on how to uninstall r-cran-mcmcpack on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                r-cran-mcmcpack
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the r-cran-mcmcpack package on Ubuntu 20.10 (Groovy Gorilla)

Package: r-cran-mcmcpack
Architecture: amd64
Version: 1.4-7-1build1
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: 3907
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-coda (>= 0.11-3), r-cran-mass, r-cran-lattice, r-cran-mcmc, r-cran-quantreg, libc6 (>= 2.29), libgcc-s1 (>= 3.0), libstdc++6 (>= 9)
Filename: pool/universe/r/r-cran-mcmcpack/r-cran-mcmcpack_1.4-7-1build1_amd64.deb
Size: 1736004
MD5sum: 757c9314ae2174dc8785036efbcededd
SHA1: 25f0769023b17d3b73c00f9ddc1abeaad1f5fe43
SHA256: 49d98bcf78c180229d30bbafda67284b0d8b6f533d705ffea86c11e9e16ae02d
SHA512: fa0f1532a285d08813b09c4f7380700aad507ad939344bd5bfee16627610b68ee7a9693cf9128b19c5cfb6aef7388706c440c990c0d77b12d6c82a949db22fdd
Homepage: https://cran.r-project.org/package=MCMCpack
Description-en: R routines for Markov chain Monte Carlo model estimation
This is a set of routines for GNU R that implement various
statistical and econometric models using Markov chain Monte Carlo
(MCMC) estimation, which allows "solving" models that would otherwise
be intractable with traditional techniques, particularly problems in
Bayesian statistics (where one or more "priors" are used as part of
the estimation procedure, instead of an assumption of ignorance about
the "true" point estimates), although MCMC can also be used to solve
frequentist statistical problems with uninformative priors. MCMC
techniques are also preferable over direct estimation in the presence
of missing data.
.
Currently implemented are a number of ecological inference (EI)
routines (for estimating individual-level attributes or behavior from
aggregate data, such as electoral returns or census results), as well
as models for traditional linear panel and cross-sectional data, some
visualization routines for EI diagnostics, two item-response theory
(or ideal-point estimation) models, metric, ordinal, and
mixed-response factor analysis, and models for Gaussian (linear) and
Poisson regression, logistic regression (or logit), and binary and
ordinal-response probit models.
.
The suggested packages (r-cran-bayesm, -eco, and -mnp) contain
additional models that may also be useful for those interested in
this package.
Description-md5: e61e7c97144ccf110c561d9a0afdc130