How to Install and Uninstall r-cran-glmnet Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 14,2024

1. Install "r-cran-glmnet" package

Please follow the steps below to install r-cran-glmnet on Ubuntu 21.10 (Impish Indri)


    
        
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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 21.10 (Impish Indri):


    
        
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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 21.10 (Impish Indri)

Package: r-cran-glmnet
Architecture: amd64
Version: 4.1-2
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: 2244
Depends: r-base-core (>= 4.0.4-1build1), r-api-4.0, r-cran-matrix (>= 1.0-6), r-cran-foreach, r-cran-shape, r-cran-survival, libc6 (>= 2.29), libgfortran5 (>= 8), libjs-mathjax
Suggests: r-cran-knitr, r-cran-testthat, r-cran-xfun, r-cran-rmarkdown
Filename: pool/universe/r/r-cran-glmnet/r-cran-glmnet_4.1-2_amd64.deb
Size: 1777680
MD5sum: d2d31253673425ef5760936999e9622e
SHA1: 6e6d70092464b3d26a65561e29824ecebf79ddf4
SHA256: 93204997ec5cca41b1ca2485df218f0961d61b561315b634965ee551edb32f1c
SHA512: 9940d5b54fa2305b84c7a0b0c28e91e615e30f605ea3a18d22d731d8aa153c0b3ab90cfbd3cf4061cac164e690bdeac53916338363ba4348e516e5a42a4f3b66
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