Implementation of 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.


horseshoe 0.1.0

  • This is the first release of the horseshoe package.

Reference manual

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0.2.0 by Stephanie van der Pas, a year ago

Browse source code at

Authors: Stephanie van der Pas [cre, aut] , James Scott [aut] , Antik Chakraborty [aut] , Anirban Bhattacharya [aut]

Documentation:   PDF Manual  

GPL-3 license

Imports stats

Suggests Hmisc, ggplot2, knitr, rmarkdown

Imported by GWASinlps.

See at CRAN