How to Install and Uninstall r-cran-brglm Package on Ubuntu 16.04 LTS (Xenial Xerus)

Last updated: September 20,2024

1. Install "r-cran-brglm" package

This guide let you learn how to install r-cran-brglm on Ubuntu 16.04 LTS (Xenial Xerus)


    
        
            $
        

        
            
                sudo apt update
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt install
            
                        
                r-cran-brglm
            
                    
    
    Copied

2. Uninstall "r-cran-brglm" package

Please follow the steps below to uninstall r-cran-brglm on Ubuntu 16.04 LTS (Xenial Xerus):


    
        
            $
        

        
            
                sudo apt remove
            
                        
                r-cran-brglm
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the r-cran-brglm package on Ubuntu 16.04 LTS (Xenial Xerus)

Package: r-cran-brglm
Priority: optional
Section: universe/gnu-r
Installed-Size: 163
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Maintainers
Architecture: amd64
Version: 0.5-9-1
Depends: r-base-core (>= 3.2.1-4), r-cran-profilemodel, r-api-3, libc6 (>= 2.2.5)
Filename: pool/universe/r/r-cran-brglm/r-cran-brglm_0.5-9-1_amd64.deb
Size: 89408
MD5sum: e3e7a77598dae08b6b4fd8ec33a58d78
SHA1: c0972c5e076b8ca046e761cc3957390506a751f7
SHA256: f325aa5c10e9696e49e27c4e14d8e2399f465e0a74c05dd13def642bf0f1aac8
Description-en: 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: 340c38cf9522c3d017fd5ca41007e4c6
Homepage: http://www.ucl.ac.uk/~ucakiko/index.html
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu