Package: IBGS 1.0.0
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.
Authors:
IBGS_1.0.0.tar.gz
IBGS_1.0.0.zip(r-4.7)IBGS_1.0.0.zip(r-4.6)IBGS_1.0.0.zip(r-4.5)
IBGS_1.0.0.tgz(r-4.6-x86_64)IBGS_1.0.0.tgz(r-4.6-arm64)IBGS_1.0.0.tgz(r-4.5-x86_64)IBGS_1.0.0.tgz(r-4.5-arm64)
IBGS_1.0.0.tar.gz(r-4.7-arm64)IBGS_1.0.0.tar.gz(r-4.7-x86_64)IBGS_1.0.0.tar.gz(r-4.6-arm64)IBGS_1.0.0.tar.gz(r-4.6-x86_64)
IBGS_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
IBGS/json (API)
| # Install 'IBGS' in R: |
| install.packages('IBGS', repos = c('https://lizhongc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/lizhongc/ibgs/issues
Last updated from:993490608c. Checks:11 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | NOTE | 133 | ||
| linux-devel-x86_64 | NOTE | 100 | ||
| source / vignettes | OK | 131 | ||
| linux-release-arm64 | NOTE | 139 | ||
| linux-release-x86_64 | NOTE | 108 | ||
| macos-release-arm64 | NOTE | 132 | ||
| macos-release-x86_64 | NOTE | 285 | ||
| macos-oldrel-arm64 | NOTE | 242 | ||
| macos-oldrel-x86_64 | NOTE | 240 | ||
| windows-devel | NOTE | 90 | ||
| windows-release | NOTE | 97 | ||
| windows-oldrel | NOTE | 89 | ||
| wasm-release | OK | 108 |
Exports:coxGibbscoxIBGSglmGibbsglmIBGSlmeGibbslmeIBGSplotAutocorrplotGelmanplotICtraceplotMargProbplotModelFreq
Dependencies:
