bayesreg: Bayesian Regression Models with Global-Local Shrinkage Priors

Fits linear or logistic regression model using Bayesian global-local shrinkage prior hierarchies as described in Polson and Scott (2010) <doi:10.1093/acprof:oso/9780199694587.003.0017>. Handles ridge, lasso, horseshoe and horseshoe+ regression with logistic, Gaussian, Laplace or Student-t distributed targets using the algorithms summarized in Makalic and Schmidt (2016) <arXiv:1611.06649>.

Version: 1.1
Imports: stats (≥ 3.0), pgdraw (≥ 1.0)
Published: 2019-06-03
Author: Daniel F. Schmidt [aut, cph, cre], Enes Makalic [aut, cph]
Maintainer: Daniel F. Schmidt < at>
License: GPL (≥ 3)
NeedsCompilation: no
Citation: bayesreg citation info
CRAN checks: bayesreg results


Reference manual: bayesreg.pdf
Package source: bayesreg_1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: bayesreg_1.1.tgz, r-oldrel: bayesreg_1.1.tgz
Old sources: bayesreg archive


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