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>.

Version:	1.3
Depends:	pgdraw (≥ 1.0), doParallel (≥ 1.0.16), foreach (≥ 1.5.1)
Imports:	stats (≥ 3.0)
Published:	2024-09-30
DOI:	10.32614/CRAN.package.bayesreg
Author:	Daniel F. Schmidt [aut, cph, cre], Enes Makalic [aut, cph]
Maintainer:	Daniel F. Schmidt <daniel.schmidt at monash.edu>
License:	GPL (≥ 3)
NeedsCompilation:	no
Citation:	bayesreg citation info
CRAN checks:	bayesreg results

Documentation:

Reference manual:

bayesreg.pdf

Downloads:

Package source:	bayesreg_1.3.tar.gz
Windows binaries:	r-devel: bayesreg_1.3.zip, r-release: bayesreg_1.3.zip, r-oldrel: bayesreg_1.3.zip
macOS binaries:	r-release (arm64): bayesreg_1.3.tgz, r-oldrel (arm64): bayesreg_1.3.tgz, r-release (x86_64): bayesreg_1.3.tgz, r-oldrel (x86_64): bayesreg_1.3.tgz
Old sources:	bayesreg archive

Reverse dependencies:

Reverse imports:

VsusP

Linking:

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