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

Last updated: May 18,2024

1. Install "r-cran-huge" package

This is a short guide on how to install r-cran-huge on Kali Linux


    
        
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                sudo apt update
            
                    
    
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            $
        

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

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


    
        
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                sudo apt remove
            
                        
                r-cran-huge
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

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

Package: r-cran-huge
Source: r-cran-huge (1.3.5-1)
Version: 1.3.5-1+b1
Installed-Size: 1610
Maintainer: Debian R Packages Maintainers
Architecture: amd64
Depends: r-base-core (>= 4.2.1-2), r-api-4.0, r-cran-matrix, r-cran-igraph, r-cran-mass, r-cran-rcpp, r-cran-rcppeigen, libc6 (>= 2.29), libgcc-s1 (>= 3.0), libgomp1 (>= 4.9), libstdc++6 (>= 5.2)
Size: 1411756
SHA256: cb701173a7f6ad14503e1b300d2655ad5a551fbe3b6905130e7564676ce6e2fe
SHA1: 8af467341cb9cc4e46a224070106ef4b3925dd48
MD5sum: 60a6798a38804fbb0af246efe78b18d7
Description: GNU R high-dimensional undirected graph estimation
Provides a general framework for high-dimensional undirected graph
estimation. It integrates data preprocessing, neighborhood screening,
graph estimation, and model selection techniques into a pipeline. In
preprocessing stage, the nonparanormal(npn) transformation is applied to
help relax the normality assumption. In the graph estimation stage, the
graph structure is estimated by Meinshausen-Buhlmann graph estimation or
the graphical lasso, and both methods can be further accelerated by the
lossy screening rule preselecting the neighborhood of each variable by
correlation thresholding.
Description-md5:
Homepage: https://cran.r-project.org/package=huge
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-cran-huge/r-cran-huge_1.3.5-1+b1_amd64.deb