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

Last updated: September 20,2024

1. Install "r-cran-glmnet" package

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


    
        
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                sudo apt update
            
                    
    
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            $
        

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

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


    
        
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                sudo apt remove
            
                        
                r-cran-glmnet
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

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

Package: r-cran-glmnet
Architecture: amd64
Version: 4.0-2-1
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: 2130
Depends: r-base-core (>= 4.0.2-1), r-api-4.0, r-cran-matrix (>= 1.0-6), r-cran-foreach, r-cran-shape, r-cran-survival, libc6 (>= 2.29), libgfortran5 (>= 8)
Suggests: r-cran-knitr, r-cran-testthat
Filename: pool/universe/r/r-cran-glmnet/r-cran-glmnet_4.0-2-1_amd64.deb
Size: 1683136
MD5sum: 1a2bc2cab71baf9e56c9e4a1db6fa4d3
SHA1: fe6fc967714c288699a078bfa4602a5ebd213fd5
SHA256: 7a499233b4bf3737408293d507bda3574ddcacb95647a2881d26c5c2902e5eb1
SHA512: 9b1385e33cd08717e0d1da2289586a52e28ff6fc1b83bf5acc6e930f7226f48606682a082ee10e1cd74f60cb79b57330836eae8108da46f96dc641d75c9386e4
Homepage: https://cran.r-project.org/package=glmnet
Description-en: Lasso and Elastic-Net Regularized Generalized Linear Models
Extremely efficient procedures for fitting the entire lasso or elastic-net
regularization path for linear regression, logistic and multinomial
regression models, Poisson regression and the Cox model. Two recent
additions are the multiple-response Gaussian, and the grouped multinomial.
The algorithm uses cyclical coordinate descent in a path-wise fashion, as
described in the paper Introduction to Glmnet.
Description-md5: 3540cbed28fd611fe9733912b4c8302a