How to Install and Uninstall r-cran-mclogit Package on Kali Linux
Last updated: December 26,2024
1. Install "r-cran-mclogit" package
Please follow the guidance below to install r-cran-mclogit on Kali Linux
$
sudo apt update
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$
sudo apt install
r-cran-mclogit
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2. Uninstall "r-cran-mclogit" package
Here is a brief guide to show you how to uninstall r-cran-mclogit on Kali Linux:
$
sudo apt remove
r-cran-mclogit
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$
sudo apt autoclean && sudo apt autoremove
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3. Information about the r-cran-mclogit package on Kali Linux
Package: r-cran-mclogit
Version: 0.9.6-2
Installed-Size: 337
Maintainer: Debian R Packages Maintainers
Architecture: all
Depends: r-base-core (>= 4.3.1-1), r-api-4.0, r-cran-matrix, r-cran-memisc
Suggests: r-cran-mass, r-cran-nnet
Size: 275976
SHA256: 8e0805f3c1e9e63c440cbad3d4d4546ae47172a1c5298960a492e4e72fc2bfd3
SHA1: 8e7ff59c365f2114798bf1c65189dc5742511af9
MD5sum: 13d1a0c474d0c2eafad71aad2ed62946
Description: GNU R multinomial logit models, with or without random effects
Multinomial Logit Models, with or without Random Effects or
Overdispersion Provides estimators for multinomial logit models in their
conditional logit and baseline logit variants, with or without random
effects, with or without overdispersion. Random effects models are
estimated using the PQL technique (based on a Laplace approximation) or
the MQL technique (based on a Solomon- Cox approximation). Estimates
should be treated with caution if the group sizes are small.
Description-md5:
Homepage: https://cran.r-project.org/package=mclogit
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-cran-mclogit/r-cran-mclogit_0.9.6-2_all.deb
Version: 0.9.6-2
Installed-Size: 337
Maintainer: Debian R Packages Maintainers
Architecture: all
Depends: r-base-core (>= 4.3.1-1), r-api-4.0, r-cran-matrix, r-cran-memisc
Suggests: r-cran-mass, r-cran-nnet
Size: 275976
SHA256: 8e0805f3c1e9e63c440cbad3d4d4546ae47172a1c5298960a492e4e72fc2bfd3
SHA1: 8e7ff59c365f2114798bf1c65189dc5742511af9
MD5sum: 13d1a0c474d0c2eafad71aad2ed62946
Description: GNU R multinomial logit models, with or without random effects
Multinomial Logit Models, with or without Random Effects or
Overdispersion Provides estimators for multinomial logit models in their
conditional logit and baseline logit variants, with or without random
effects, with or without overdispersion. Random effects models are
estimated using the PQL technique (based on a Laplace approximation) or
the MQL technique (based on a Solomon- Cox approximation). Estimates
should be treated with caution if the group sizes are small.
Description-md5:
Homepage: https://cran.r-project.org/package=mclogit
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-cran-mclogit/r-cran-mclogit_0.9.6-2_all.deb