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IBGS: Iterated Block Gibbs Sampler for Ultrahigh-Dimensional Variable Selection and Model Averaging

Variable selection for generalized linear models and the Cox proportional-hazards model in ultrahigh dimensions via the iterated block Gibbs sampler (IBGS). The sampler is implemented in C with parallel block screening through 'OpenMP', and supports the gaussian, binomial and poisson families (fitted by least squares or iteratively reweighted least squares) as well as the Cox model for survival analysis (fitted by its Efron partial likelihood), together with the AIC, BIC, AICc and extended BIC model selection criteria.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: graphics, stats
Published: 2026-07-04
DOI: 10.32614/CRAN.package.IBGS
Author: Lizhong Chen [aut, cre]
Maintainer: Lizhong Chen <chen.l at wehi.edu.au>
License: GPL-3
NeedsCompilation: yes
Materials: README, NEWS
CRAN checks: IBGS results

Documentation:

Reference manual: IBGS.html , IBGS.pdf
Vignettes: Getting started with IBGS (source, R code)

Downloads:

Package source: IBGS_1.0.0.tar.gz
Windows binaries: r-devel: IBGS_1.0.0.zip, r-release: IBGS_1.0.0.zip, r-oldrel: IBGS_1.0.0.zip
macOS binaries: r-release (arm64): IBGS_1.0.0.tgz, r-oldrel (arm64): IBGS_1.0.0.tgz, r-release (x86_64): IBGS_1.0.0.tgz, r-oldrel (x86_64): IBGS_1.0.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=IBGS to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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