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

Last updated: January 11,2025

1. Install "r-cran-brglm" package

Here is a brief guide to show you how to install r-cran-brglm on Kali Linux


    
        
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                sudo apt update
            
                    
    
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            $
        

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

Please follow the step by step instructions below to uninstall r-cran-brglm on Kali Linux:


    
        
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                sudo apt remove
            
                        
                r-cran-brglm
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

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

Package: r-cran-brglm
Source: r-cran-brglm (0.7.2-1)
Version: 0.7.2-1+b1
Installed-Size: 179
Maintainer: Debian R Packages Maintainers
Architecture: amd64
Depends: r-base-core (>= 4.2.1-2), r-api-4.0, r-cran-profilemodel
Suggests: r-cran-mass
Size: 124608
SHA256: 672ddf2c7890bd5d8fee71defcffed7b17a57cb584db87c4f90fdbc2f4c86db2
SHA1: 9aa581e9a047e7d5c2d6b644e25ed09171f548ee
MD5sum: 38321fbaaf1d5227eac535668443c975
Description: GNU R package for bias reduction in binomial-response GLMs
Fit generalized linear models with binomial responses using either an
adjusted-score approach to bias reduction or maximum penalized
likelihood where penalization is by Jeffreys invariant prior. These
procedures return estimates with improved frequentist properties
(bias, mean squared error) that are always finite even in cases where
the maximum likelihood estimates are infinite (data separation).
Fitting takes place by fitting generalized linear models on
iteratively updated pseudo-data. The interface is essentially the same
as 'glm'. More flexibility is provided by the fact that custom
pseudo-data representations can be specified and used for model
fitting. Functions are provided for the construction of confidence
intervals for the reduced-bias estimates.
Description-md5:
Homepage: https://cran.r-project.org/package=brglm
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-cran-brglm/r-cran-brglm_0.7.2-1+b1_amd64.deb