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 |
| Author: |
Stephanie van der Pas [cre, aut],
James Scott [aut],
Antik Chakraborty [aut],
Anirban Bhattacharya [aut] |
| Maintainer: |
Stephanie van der Pas <svdpas at math.leidenuniv.nl> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| Materials: |
NEWS |
| CRAN checks: |
horseshoe results |
Documentation:
Downloads:
Reverse dependencies:
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