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VsusP: Variable Selection using Shrinkage Priors

Bayesian variable selection using shrinkage priors to identify significant variables in high-dimensional datasets. The package includes methods for determining the number of significant variables through innovative clustering techniques of posterior distributions, specifically utilizing the 2-Means and Sequential 2-Means (S2M) approaches. The package aims to simplify the variable selection process with minimal tuning required in statistical analysis.

Version:1.0.0
Imports:bayesreg, stats
Suggests:covr,MASS,knitr,rmarkdown,tinytex,testthat (≥ 3.0.0)
Published:2024-06-25
DOI:10.32614/CRAN.package.VsusP
Author:Nilson ChapagainORCID iD [aut, cre], Debdeep Pati [aut]
Maintainer:Nilson Chapagain <nilson.chapagain at gmail.com>
BugReports:https://github.com/nilson01/VsusP-variable-selection-using-shrinkage-priors/issues
License:GPL (≥ 3)
URL:https://github.com/nilson01/VsusP-variable-selection-using-shrinkage-priors
NeedsCompilation:no
Materials:README
CRAN checks:VsusP results

Documentation:

Reference manual:VsusP.html ,VsusP.pdf
Vignettes:Variable Selection using Shrinkage Priors (VsusP) (source,R code)

Downloads:

Package source: VsusP_1.0.0.tar.gz
Windows binaries: r-devel:VsusP_1.0.0.zip, r-release:VsusP_1.0.0.zip, r-oldrel:VsusP_1.0.0.zip
macOS binaries: r-release (arm64):VsusP_1.0.0.tgz, r-oldrel (arm64):VsusP_1.0.0.tgz, r-release (x86_64):VsusP_1.0.0.tgz, r-oldrel (x86_64):VsusP_1.0.0.tgz

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=VsusPto link to this page.


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