Basic.y

<p>Helper function for computing the posterior mean, posterior variance</p>

internal

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.

Stephanie van der Pas

horseshoe

Implementation of the Horseshoe Prior

James Scott

Antik Chakraborty

Anirban Bhattacharya

Basic.y function

Helper function for computing the posterior mean, posterior variance — Basic.y

Helper function for computing the posterior mean, posterior variance

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

Description

Usage

Arguments