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