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