An R package to fit Bayesian regression models with shrinkage priors.
Linear regression models with global shrinkage priors:
- normal-inverse-Gamma
- normal-beta prime (which includes normal–half Cauchy)
- normal-inverse-Gaussian
- normal-Gamma
- normal with empirical Bayes (closed-form inference)
Linear regression models with local shrinkage priors, which accommodate grouped variables and some sparse-inducing priors:
- normal-inverse-Gamma (Armagan and Zaretzki, 2010)
- normal-Gamma (Griffin and Brown, 2010)
- normal-inverse-Gaussian (Caron and Doucet, 2008)
- normal-Beta-Prime (Bai and Gosh, 2019)
To install shrinkage from R:
# Install/load R package devtools
install.packages("devtools")
library(devtools)
# Install/load R package beam from github
install_github("gleday/shrinkage")
library(shrinkage)
Vignette describing in details the implemented algorithms:
vignette("Algorithms", package = "shrinkage")
Vignette providing code for fitting models using Stan via the R package rstan:
vignette("Stan", package = "shrinkage")