horseshoe (version 0.2.0)

Implementation of the Horseshoe Prior

Description

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.

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Install

install.packages('horseshoe')

Monthly Downloads

288

Version

0.2.0

License

GPL-3

Last Published

July 18th, 2019

Functions in horseshoe (0.2.0)