bayesreg
Bayesian Regression Models with Global-Local Shrinkage Priors
Fits linear or generalized linear regression models using Bayesian global-local shrinkage prior hierarchies as described in Polson and Scott (2010) <doi:10.1093/acprof:oso/9780199694587.003.0017>. Provides an efficient implementation of ridge, lasso, horseshoe and horseshoe+ regression with logistic, Gaussian, Laplace, Student-t, Poisson or geometric distributed targets using the algorithms summarized in Makalic and Schmidt (2016) <doi:10.48550/arXiv.1611.06649>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.3 |
2026-04-09 windows/windows R-4.5 | bayesreg_1.3.zip |
305.1 KiB |
Dependencies (latest)
Depends
- pgdraw (>= 1.0)
- doParallel (>= 1.0.16)
- foreach (>= 1.5.1)
Imports
- stats (>= 3.0)