Bayesian Regression Models with Global-Local Shrinkage Priors R package bayesreg version 1.3 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>. Software Depends: pgdraw (>= 1.0), doParallel (>= 1.0.16), foreach (>= 1.5.1) Imports: stats (>= 3.0) Daniel F. Schmidt <daniel.schmidt@monash.edu> Comprehensive R Archive Network (CRAN) Daniel F. Schmidt [aut, cph, cre] (ORCID: <https://orcid.org/0000-0002-1788-2375>), Enes Makalic [aut, cph] (ORCID: <https://orcid.org/0000-0003-3017-0871>) GPL (>= 3) 2024-09-30 application/tgz https://CRAN.R-project.org/package=bayesreg doi:10.32614/CRAN.package.bayesreg