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

Last updated: December 25,2024

1. Install "r-cran-lhs" package

This guide covers the steps necessary to install r-cran-lhs on Ubuntu 20.10 (Groovy Gorilla)


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

This guide covers the steps necessary to uninstall r-cran-lhs on Ubuntu 20.10 (Groovy Gorilla):


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

Package: r-cran-lhs
Architecture: amd64
Version: 1.0.2-1build1
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: 775
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-rcpp, libc6 (>= 2.29), libgcc-s1 (>= 3.0), libstdc++6 (>= 5.2)
Recommends: r-cran-runit, r-cran-testthat
Suggests: r-cran-knitr, r-cran-rmarkdown, r-cran-covr
Filename: pool/universe/r/r-cran-lhs/r-cran-lhs_1.0.2-1build1_amd64.deb
Size: 328648
MD5sum: bc78670adf51a29b638384a853a82aac
SHA1: 6df24c5547e07232fcde3a597b529c5830009386
SHA256: 56c19a86107529d9f172c9d6b3e6047b70dab93bbee35ae76053011512591733
SHA512: b6f227bbebd26bf5676083b99b07168dcd1435b627036b58b2375cddb3f9e9c4e5e85d69c711e5a9f8aafd70e2488c1174f1e575085b93d999fbc69680397c51
Homepage: https://cran.r-project.org/package=lhs
Description-en: GNU R Latin Hypercube Samples
This package provides a number of methods for creating and augmenting Latin
Hypercube Samples.
.
Latin hypercube sampling (LHS) is a statistical method for generating a sample
of plausible collections of parameter values from a multidimensional
distribution. The sampling method is often used to construct computer
experiments.
Description-md5: 80d3c99c9c9ff30fdbc80cc8bae35d49