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.
Package details 


Author  Stephanie van der Pas [cre, aut], James Scott [aut], Antik Chakraborty [aut], Anirban Bhattacharya [aut] 
Date of publication  20161108 18:36:01 
Maintainer  Stephanie van der Pas <[email protected]> 
License  GPL3 
Version  0.1.0 
Package repository  View on CRAN 
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