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

Last updated: May 17,2024

1. Install "r-cran-fields" package

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


    
        
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                sudo apt update
            
                    
    
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            $
        

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

Please follow the guidelines below to uninstall r-cran-fields on Ubuntu 20.10 (Groovy Gorilla):


    
        
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                sudo apt remove
            
                        
                r-cran-fields
            
                    
    
    Copied


    
        
            $
        

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

Package: r-cran-fields
Architecture: amd64
Version: 10.3-1build1
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: 4158
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-spam, r-cran-maps, libc6 (>= 2.29)
Recommends: r-cran-runit
Filename: pool/universe/r/r-cran-fields/r-cran-fields_10.3-1build1_amd64.deb
Size: 3973096
MD5sum: 589c56a7a550c0842514b0e477dd61d4
SHA1: f74e098dcd34a07469c669a9ec7c943ac8005969
SHA256: 51bb5a5ab120a99f6fffb251741b78a959a7c7bc8005fa675ca803c6aef9f8fd
SHA512: c8a55c3595e826965ee435ff96490bfe6640db99459c89000ee4418ec570c59989fc796f7404fb54fe90f35ce711ed5eaa03580e81501b95e708e6af5da14fad
Homepage: https://cran.r-project.org/package=fields
Description-en: GNU R tools for spatial data
For curve, surface and function fitting with an emphasis on splines,
spatial data and spatial statistics. The major methods include cubic,
and thin plate splines, Kriging and compact covariances for large data
sets. The splines and Kriging methods are supported by functions that
can determine the smoothing parameter (nugget and sill variance) and
other covariance parameters by cross validation and also by restricted
maximum likelihood. For Kriging there is an easy to use function that
also estimates the correlation scale (range). A major feature is that
any covariance function implemented in R and following a simple fields
format can be used for spatial prediction. There are also many useful
functions for plotting and working with spatial data as images. This
package also contains an implementation of sparse matrix methods for
large spatial data sets.
Description-md5: 5ecc34e48d2f689d66a103a049b66698