How to Install and Uninstall r-cran-loo Package on Kali Linux

Last updated: December 24,2024

1. Install "r-cran-loo" package

Please follow the instructions below to install r-cran-loo on Kali Linux


    
        
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                sudo apt update
            
                    
    
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            $
        

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

Here is a brief guide to show you how to uninstall r-cran-loo on Kali Linux:


    
        
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                sudo apt remove
            
                        
                r-cran-loo
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the r-cran-loo package on Kali Linux

Package: r-cran-loo
Version: 2.6.0-1
Installed-Size: 4065
Maintainer: Debian R Packages Maintainers
Architecture: all
Depends: r-base-core (>= 4.3.1-1), r-api-4.0, r-cran-checkmate, r-cran-matrixstats (>= 0.52)
Recommends: r-cran-testthat (>= 2.1.0)
Suggests: r-cran-bayesplot (>= 1.7.0), r-cran-brms (>= 2.10.0), r-cran-ggplot2, r-cran-knitr, r-cran-posterior, r-cran-rmarkdown, r-cran-rstan, r-cran-rstanarm (>= 2.19.0), r-cran-rstantools, r-cran-spdep
Size: 3133912
SHA256: e04ed3f273913f44ab66f584600c4649c8e37855d0a4b722c3e6f8ede0b68c07
SHA1: 52f727146fefa3f97fc40dbe2a5720ba99b1291c
MD5sum: c1a4bec20f49365e3a2b806476b35aec
Description: GNU R leave-one-out cross-validation and WAIC for Bayesian models
Efficient approximate leave-one-out cross-validation (LOO) for Bayesian
models fit using Markov chain Monte Carlo. The approximation uses Pareto
smoothed importance sampling (PSIS), a new procedure for regularizing
importance weights. As a byproduct of the calculations, it is possible
as well to obtain approximate standard errors for estimated predictive
errors and for the comparison of predictive errors between models. The
package also provides methods for using stacking and other model
weighting techniques to average Bayesian predictive distributions.
Description-md5:
Homepage: https://cran.r-project.org/package=loo
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-cran-loo/r-cran-loo_2.6.0-1_all.deb