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

Last updated: April 28,2024

1. Install "r-cran-bdgraph" package

Learn how to install r-cran-bdgraph on Ubuntu 20.10 (Groovy Gorilla)


    
        
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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

This guide covers the steps necessary to uninstall r-cran-bdgraph on Ubuntu 20.10 (Groovy Gorilla):


    
        
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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 20.10 (Groovy Gorilla)

Package: r-cran-bdgraph
Architecture: amd64
Version: 2.62-1build2
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: 1537
Depends: r-base-core (>= 4.0.0.20200528-1), 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 (>= 5.2)
Filename: pool/universe/r/r-cran-bdgraph/r-cran-bdgraph_2.62-1build2_amd64.deb
Size: 1236676
MD5sum: 928ba8ba3722fd453bdb953c8e417203
SHA1: 3859355616149149d8ff66549496e5571e10ee13
SHA256: 9ea1e57e0b376bfd729697bdda5334597d7877ed388c669b8ea3c1dbd3dd6a78
SHA512: 708f9dc1de3f3ce9da1bae4dc5b5046326b8109bbafc5d0be276c9d0c8170ed0079a3536224a47be87fb4237d734872c43f5b27b3260460c1b03ca9f8ef6ca7d
Homepage: https://cran.r-project.org/package=BDgraph
Description-en: GNU R bayesian structure learning in graphical models
Statistical tools for Bayesian structure learning in undirected
graphical models for continuous, discrete, and mixed data. The package
is implemented the recent improvements in the Bayesian graphical models
literature, including Mohammadi and Wit (2015) ,
Mohammadi and Wit (2019) .
Description-md5: e1b471b28a428f7222b8d3a86d9ed7c7