Implementation of the Horseshoe Prior
Helper function for computing the posterior mean, posterior variance
Helper function for computing the posterior mean, posterior variance
Helper function for computing the posterior mean, posterior variance
Function to implement the horseshoe shrinkage prior in Bayesian linear...
MMLE for the horseshoe prior for the sparse normal means problem.
The horseshoe prior for the sparse normal means problem
Posterior mean for the horseshoe for the normal means problem.
Posterior variance for the horseshoe for the normal means problem.
Variable selection using the horseshoe prior
Contains functions for applying the horseshoe prior to high- dimensional linear regression, yielding the posterior mean and credible intervals, amongst other things. The key parameter tau can be equipped with a prior or estimated via maximum marginal likelihood estimation (MMLE). The main function, horseshoe, is for linear regression. In addition, there are functions specifically for the sparse normal means problem, allowing for faster computation of for example the posterior mean and posterior variance. Finally, there is a function available to perform variable selection, using either a form of thresholding, or credible intervals.