How to Install and Uninstall r-cran-bdgraph Package on Ubuntu 22.10 (Kinetic Kudu)

Last updated: May 13,2024

1. Install "r-cran-bdgraph" package

This tutorial shows how to install r-cran-bdgraph on Ubuntu 22.10 (Kinetic Kudu)


    
        
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                sudo apt update
            
                    
    
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            $
        

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

Please follow the step by step instructions below to uninstall r-cran-bdgraph on Ubuntu 22.10 (Kinetic Kudu):


    
        
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                sudo apt remove
            
                        
                r-cran-bdgraph
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the r-cran-bdgraph package on Ubuntu 22.10 (Kinetic Kudu)

Package: r-cran-bdgraph
Architecture: amd64
Version: 2.68+dfsg-1
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: 1085
Depends: r-base-core (>= 4.2.1-1ubuntu1), r-api-4.0, r-cran-igraph, libblas3 | libblas.so.3, libc6 (>= 2.29), libgcc-s1 (>= 3.0), libgomp1 (>= 4.9), liblapack3 | liblapack.so.3, libstdc++6 (>= 11)
Suggests: r-cran-huge, r-cran-proc, r-cran-ggplot2, r-cran-tmvtnorm, r-cran-skimr, r-cran-knitr, r-cran-rmarkdown
Filename: pool/universe/r/r-cran-bdgraph/r-cran-bdgraph_2.68+dfsg-1_amd64.deb
Size: 699454
MD5sum: 1e95912ea349bce4dd4f8c8e4969d8bf
SHA1: 879c41c7012babc8027ea6f3bb683ffc383823f1
SHA256: e0ddae0fd13920110edb2420ab891da0de95a5de48d14399b42392080b70481d
SHA512: e496f460b205dc613566c390ff944b23f0ac5c35ebdcdd3fe588ddbc3d68b70e781120e16fc77cab89e84e68cf06c995f4ba38148f21f84e435d6a29a4b75a7f
Homepage: https://cran.r-project.org/package=BDgraph
Description: GNU R bayesian structure learning in graphical models
Description-md5: e1b471b28a428f7222b8d3a86d9ed7c7