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IBGS  

Iterated Block Gibbs Sampler for Ultrahigh-Dimensional Variable Selection and Model Averaging
View on CRAN: Click here


Download and install IBGS package within the R console
Install from CRAN:
install.packages("IBGS")

Install from Github:
library("remotes")
install_github("cran/IBGS")

Install by package version:
library("remotes")
install_version("IBGS", "1.0.0")



Attach the package and use:
library("IBGS")
Maintained by
Lizhong Chen
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-07-04
Latest Update: 2026-07-04
Description:
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.
How to cite:
Lizhong Chen (2026). IBGS: Iterated Block Gibbs Sampler for Ultrahigh-Dimensional Variable Selection and Model Averaging. R package version 1.0.0, https://cran.r-project.org/web/packages/IBGS. Accessed 24 Oct. 2026.
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Other packages that cited IBGS R package
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Complete documentation for IBGS
Functions, R codes and Examples using the IBGS R package
Full IBGS package functions and examples
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