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

Last updated: May 03,2024

1. Install "r-cran-dorng" package

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


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

Learn how to uninstall r-cran-dorng on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                r-cran-dorng
            
                    
    
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            $
        

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

Package: r-cran-dorng
Architecture: all
Version: 1.8.2-2build1
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: 354
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-foreach, r-cran-rngtools (>= 1.5), r-cran-iterators
Recommends: r-cran-testthat, r-cran-doparallel
Suggests: r-cran-devtools, r-cran-knitr, r-cran-bibtex, r-cran-pkgmaker (>= 0.31)
Filename: pool/universe/r/r-cran-dorng/r-cran-dorng_1.8.2-2build1_all.deb
Size: 285804
MD5sum: 406ef71260805cac4293fb50e8e65127
SHA1: 3134f4fb4a033b012d68dfefa545bb3744e02ef7
SHA256: 3f9f1fd7f7ac956e5ff14af8a6161249a4ca385f2acdef1a586efda6d61a6d77
SHA512: 50ef85f86f56bec50fee872ddd530d020f4c386235bae869870fd32a321ddc91ab84fb01016b59d4753939c09ebcad3e48b06cb7f97f05a439a5597ec532d31d
Homepage: https://cran.r-project.org/package=doRNG
Description-en: GNU R generic reproducible parallel backend for 'foreach' loops
This GNU R package provides functions to perform
reproducible parallel foreach loops, using independent
random streams as generated by L'Ecuyer's combined
multiple-recursive generator [L'Ecuyer (1999), ].
It enables to easily convert standard %dopar% loops into
fully reproducible loops, independently of the number
of workers, the task scheduling strategy, or the chosen
parallel environment and associated foreach backend.
Description-md5: f1f94be1edcc14c9c9feced64ab1c66d