  Bayesian penalized regression techniques, such as the Bayesian lasso and the
Bayesian horseshoe estimator, have recently received a significant amount of
attention in the statistics literature. However, software implementing
state-of-the-art Bayesian penalized regression, outside of general purpose
Markov chain Monte Carlo platforms such as STAN, is relatively rare. This paper
introduces bayesreg, a new toolbox for fitting Bayesian penalized regression
models with continuous shrinkage prior densities. The toolbox features Bayesian
linear regression with Gaussian or heavy-tailed error models and Bayesian
logistic regression with ridge, lasso, horseshoe and horseshoe$+$ estimators.
The toolbox is free, open-source and available for use with the MATLAB and R
numerical platforms.
