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

Last updated: November 07,2024

1. Install "r-cran-bayesfm" package

Please follow the steps below to install r-cran-bayesfm on Ubuntu 20.10 (Groovy Gorilla)


    
        
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                sudo apt update
            
                    
    
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            $
        

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

Learn how to uninstall r-cran-bayesfm on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                r-cran-bayesfm
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

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

Package: r-cran-bayesfm
Architecture: amd64
Version: 0.1.3-1build1
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: 338
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-checkmate (>= 1.8.0), r-cran-coda, r-cran-ggplot2 (>= 2.1.0), r-cran-gridextra, r-cran-plyr (>= 1.8.0), libc6 (>= 2.29), libgfortran5 (>= 8), liblapack3 | liblapack.so.3
Filename: pool/universe/r/r-cran-bayesfm/r-cran-bayesfm_0.1.3-1build1_amd64.deb
Size: 201188
MD5sum: b706ef85065e711e880b9f631426e86d
SHA1: 06674a26a15be9e421ea9cdd8a5fef5b7201ad5d
SHA256: 8ac25807d6faa2b2633cb73fd12fcfba7fd69aa73fed5ff98f0a48e6757a55fa
SHA512: 730f10b490e4f1e7ceaa3d047207475b431ca39c76e577d118714021f6c20a7d5a6bf6ac8fe093be4d3a021abaf5ce0901cad2e0f097cb2dc244896df471de20
Homepage: https://cran.r-project.org/package=BayesFM
Description-en: GNU R Bayesian inference for factor modeling
Collection of procedures to perform Bayesian analysis on a variety
of factor models. Currently, it includes: Bayesian Exploratory Factor
Analysis (befa), an approach to dedicated factor analysis with stochastic
search on the structure of the factor loading matrix. The number of latent
factors, as well as the allocation of the manifest variables to the factors,
are not fixed a priori but determined during MCMC sampling.
More approaches will be included in future releases of this package.
Description-md5: 46d1c4a09a99a7f20a1099229096521d