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) <arXiv:1611.06649>.
| Version: |
1.2 |
| Imports: |
stats (≥ 3.0), pgdraw (≥ 1.0) |
| Published: |
2021-03-29 |
| 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 |
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