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

Last updated: November 25,2024

1. Install "r-cran-ordinal" package

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


    
        
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                sudo apt update
            
                    
    
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            $
        

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

Here is a brief guide to show you how to uninstall r-cran-ordinal on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                r-cran-ordinal
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

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

Package: r-cran-ordinal
Architecture: amd64
Version: 2019.12-10-1build1
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: 1452
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-ucminf, r-cran-mass, r-cran-matrix, r-cran-numderiv, libc6 (>= 2.4)
Recommends: r-cran-testthat (>= 0.8)
Suggests: r-cran-lme4, r-cran-nnet, r-cran-xtable
Filename: pool/universe/r/r-cran-ordinal/r-cran-ordinal_2019.12-10-1build1_amd64.deb
Size: 1228400
MD5sum: c3ddd7c40f1fa5f61bcb171e04168886
SHA1: 531a947dd5a18e22bab3ba6db3b839cff31ae484
SHA256: aeb68d4fcf000f832517bbdc7dc20d2c5d468d6f4648e32d0daa2b8a48c9dd1b
SHA512: 963df078c25ebe1c195a44572144c87ddd9be2d8aee6517a4a7e4849dea976249b3713bee226f8be34dfabcc9bd8074190a82755552c703999ead3b8460e6f16
Homepage: https://cran.r-project.org/package=ordinal
Description-en: GNU R regression models for ordinal data
Implementation of cumulative link (mixed) models also known
as ordered regression models, proportional odds models, proportional
hazards models for grouped survival times and ordered logit/probit/...
models. Estimation is via maximum likelihood and mixed models are fitted
with the Laplace approximation and adaptive Gauss-Hermite quadrature.
Multiple random effect terms are allowed and they may be nested, crossed or
partially nested/crossed. Restrictions of symmetry and equidistance can be
imposed on the thresholds (cut-points/intercepts). Standard model
methods are available (summary, anova, drop-methods, step,
confint, predict etc.) in addition to profile methods and slice
methods for visualizing the likelihood function and checking
convergence.
Description-md5: 0bf2fc8be0c888e4b10f61d8ac7fb929