horseshoe: 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.

Version: 0.2.0
Depends: R (≥ 3.1.0)
Imports: stats
Suggests: Hmisc, ggplot2, knitr, rmarkdown
Published: 2019-07-18
DOI: 10.32614/CRAN.package.horseshoe
Author: Stephanie van der Pas [cre, aut], James Scott [aut], Antik Chakraborty [aut], Anirban Bhattacharya [aut]
Maintainer: Stephanie van der Pas <svdpas at>
License: GPL-3
NeedsCompilation: no
Materials: NEWS
CRAN checks: horseshoe results


Reference manual: horseshoe.pdf
Vignettes: Horseshoe vignette


Package source: horseshoe_0.2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): horseshoe_0.2.0.tgz, r-oldrel (arm64): horseshoe_0.2.0.tgz, r-release (x86_64): horseshoe_0.2.0.tgz, r-oldrel (x86_64): horseshoe_0.2.0.tgz
Old sources: horseshoe archive

Reverse dependencies:

Reverse imports: ebnm, GWASinlps
Reverse suggests: Mhorseshoe


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