Package: VsusP 1.0.0

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]

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VsusP.pdf |VsusP.html✨
VsusP/json (API)

# Install 'VsusP' in R:
install.packages('VsusP', repos = c('https://nilson01.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

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

On CRAN:

4.65 score 3 stars 6 scripts 449 downloads 5 exports 7 dependencies

Last updated 5 months agofrom:cf6f1c5246. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 26 2024
R-4.5-winNOTEOct 26 2024
R-4.5-linuxNOTEOct 26 2024
R-4.4-winNOTEOct 26 2024
R-4.4-macNOTEOct 26 2024
R-4.3-winNOTEOct 26 2024
R-4.3-macNOTEOct 26 2024

Exports:OptimalHbiS2MVarSelectionS2MVarSelectionV1Sequential2MeansSequential2MeansBeta

Dependencies:bayesregcodetoolsdoParallelforeachiteratorspgdrawRcpp

Variable Selection using Shrinkage Priors (VsusP)

Nilson Chapagain, Debdeep Pati

Rendered fromVsusPVignette.Rmdusingknitr::rmarkdownon Oct 26 2024.

Last update: 2024-06-24
Started: 2024-06-23