Package: VsusP 1.0.0

Nilson Chapagain

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.

Authors:Nilson Chapagain [aut, cre], Debdeep Pati [aut]

VsusP_1.0.0.tar.gz
VsusP_1.0.0.tar.gz(r-4.5-noble)VsusP_1.0.0.tar.gz(r-4.4-noble)
VsusP_1.0.0.tgz(r-4.4-emscripten)VsusP_1.0.0.tgz(r-4.3-emscripten)
VsusP.pdf |VsusP.html✨
VsusP/json (API)

# InstallVsusP in R:
install.packages('VsusP',repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/nilson01/vsusp-variable-selection-using-shrinkage-priors/issues

5 exports 0.09 score 3 dependencies 7 downloads

Last updated 9 days agofrom:941beb2657

Exports:OptimalHbiS2MVarSelectionS2MVarSelectionV1Sequential2MeansSequential2MeansBeta

Dependencies:bayesregpgdrawRcpp

Variable Selection using Shrinkage Priors (VsusP)

Nilson Chapagain, Debdeep Pati

Rendered fromVsusPVignette.Rmdusingknitr::rmarkdownon Jun 27 2024.

Last update: 2024-06-27
Started: 2024-06-27