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

Last updated: January 23,2025

1. Install "r-cran-profilemodel" package

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


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                r-cran-profilemodel
            
                    
    
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2. Uninstall "r-cran-profilemodel" package

In this section, we are going to explain the necessary steps to uninstall r-cran-profilemodel on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                r-cran-profilemodel
            
                    
    
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                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the r-cran-profilemodel package on Ubuntu 20.10 (Groovy Gorilla)

Package: r-cran-profilemodel
Architecture: all
Version: 0.6.0-2build1
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: 137
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0
Suggests: r-cran-mass, r-cran-gnm
Filename: pool/universe/r/r-cran-profilemodel/r-cran-profilemodel_0.6.0-2build1_all.deb
Size: 105776
MD5sum: e3d6d060526b77e45f495d855b8aa535
SHA1: 6df4e413e6de3bf37e5e4ab04158de4631e0acd1
SHA256: dc095ab2cf839208635048c3654d0b102ce95e7ce12f1247b4dfbf3227225032
SHA512: 5b7103332fc4de2e4f52f2baddab0e8a605f65e55c5eab24ce4ed580822eaa44cf1a423e546fea82a466336ce8b04eed7a6b0cc12628aa219d73769e3a93ed74
Homepage: https://cran.r-project.org/package=profileModel
Description-en: GNU R tools for profiling inference functions
profileModel provides tools that can be used to calculate, evaluate,
plot and use for inference the profiles of *arbitrary* inference
functions for *arbitrary* 'glm'-like fitted models with linear
predictors.
Description-md5: 55031ce393bdba36514676ea2cab54fa