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

Last updated: May 16,2024

1. Install "r-cran-corpcor" package

In this section, we are going to explain the necessary steps to install r-cran-corpcor on Ubuntu 21.10 (Impish Indri)


    
        
            $
        

        
            
                sudo apt update
            
                    
    
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            $
        

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

Please follow the guidelines below to uninstall r-cran-corpcor on Ubuntu 21.10 (Impish Indri):


    
        
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                sudo apt remove
            
                        
                r-cran-corpcor
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the r-cran-corpcor package on Ubuntu 21.10 (Impish Indri)

Package: r-cran-corpcor
Architecture: all
Version: 1.6.9-4build1
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: 150
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0
Filename: pool/universe/r/r-cran-corpcor/r-cran-corpcor_1.6.9-4build1_all.deb
Size: 114844
MD5sum: 66bb3e08a0f6fc77bb0f381eb7a87ea2
SHA1: 2beb615a9573817086a5c32496e052b369bfb6f8
SHA256: 4bccb3b680bed567739ee34fe80d2b373032b4fd25cdf5eee8da9d54c80cfd9b
SHA512: 3268638effe8d1aa711097870e298500788c0a260517ef6d3188d8b880e1cbba684bd85b363ef8682e9a0423cb05afde2f772a9dc53bf99455cedb4b513d8332
Homepage: https://cran.r-project.org/package=corpcor
Description-en: GNU R for Estimation of Covariance and Correlation -- corpcor
GNU R package which implements a James-Stein-type shrinkage estimator for the
covariance matrix, with separate shrinkage for variances and correlations. The
approach is both computationally as well as statistically very efficient, it is
applicable to "small n, large p" data, and always returns a positive definite
and well-conditioned covariance matrix. In addition to inferring the
covariance matrix the package also provides shrinkage estimators for partial
correlations and partial variances. The inverse of the covariance and
correlation matrix can be efficiently computed, as well as any arbitrary power
of the shrinkage correlation matrix. Furthermore, functions are available for
fast singular value decomposition, for computing the pseudoinverse, and for
checking the rank and positive definiteness of a matrix.
Description-md5: 4a025d0a6bc28380c5310b05bc696f48