A simple sampler for the horseshoe estimator

Enes Makalic, Daniel F. Schmidt

Research output: Contribution to journalArticleResearchpeer-review

20 Citations (Scopus)

Abstract

In this note we derive a simple Bayesian sampler for linear regression with the horseshoe hierarchy. A new interpretation of the horseshoe model is presented, and extensions to logistic regression and alternative hierarchies, such as horseshoe+, are discussed. Due to the conjugacy of the proposed hierarchy, Chib's algorithm may be used to easily compute the marginal likelihood of the model.

Original languageEnglish
Article number23882
Pages (from-to)179-182
Number of pages4
JournalIEEE Signal Processing Letters
Volume23
Issue number1
DOIs
Publication statusPublished - Jan 2016
Externally publishedYes

Keywords

  • Bayesian regression
  • Horseshoe estimator
  • Markov chain Monte Carlo sampling

Cite this

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A simple sampler for the horseshoe estimator. / Makalic, Enes; Schmidt, Daniel F.

In: IEEE Signal Processing Letters, Vol. 23, No. 1, 23882, 01.2016, p. 179-182.

Research output: Contribution to journalArticleResearchpeer-review

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