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.

Install the latest version of this package by entering the following in R:

`install.packages("horseshoe")`

Author | Stephanie van der Pas [cre, aut], James Scott [aut], Antik Chakraborty [aut], Anirban Bhattacharya [aut] |

Date of publication | 2016-11-08 18:36:01 |

Maintainer | Stephanie van der Pas <svdpas@math.leidenuniv.nl> |

License | GPL-3 |

Version | 0.1.0 |

**Basic.integrand:** Helper function for computing the posterior mean, posterior...

**Basic.y:** Helper function for computing the posterior mean, posterior...

**Basic.y.vec:** Helper function for computing the posterior mean, posterior...

**horseshoe:** Function to implement the horseshoe shrinkage prior in...

**HS.MMLE:** MMLE for the horseshoe prior for the sparse normal means...

**HS.normal.means:** The horseshoe prior for the sparse normal means problem

**HS.post.mean:** Posterior mean for the horseshoe for the normal means...

**HS.post.var:** Posterior variance for the horseshoe for the normal means...

**HS.var.select:** Variable selection using the horseshoe prior

NAMESPACE

NEWS.md

R

R/HS_normal_means.R
R/HS_var_select.R
R/Helper_functions.R
R/HS_MMLE.R
R/HS_post_mean.R
R/horseshoe.R
R/HS_post_var.R
MD5

DESCRIPTION

man

man/HS.post.var.Rd
man/HS.var.select.Rd
man/HS.MMLE.Rd
man/HS.normal.means.Rd
man/Basic.y.vec.Rd
man/Basic.integrand.Rd
man/horseshoe.Rd
man/HS.post.mean.Rd
man/Basic.y.Rd
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