Bayesian inference using artificial augmenting regressions

Tsionas, Michael (2009) Bayesian inference using artificial augmenting regressions. Communications in Statistics - Theory and Methods, 38 (9). pp. 1361-1370. ISSN 0361-0926

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Abstract

In this article, it is shown that many intractable problems of Bayesian inference can be cast in a form called “artificial augmenting regression” in which application of Markov Chain Monte Carlo techniques, especially Gibbs sampling with data augmentation, is rather convenient. The new techniques are illustrated using several challenging statistical problems and numerical results are presented.

Item Type:
Journal Article
Journal or Publication Title:
Communications in Statistics - Theory and Methods
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
ID Code:
65250
Deposited By:
Deposited On:
17 Jun 2013 13:21
Refereed?:
Yes
Published?:
Published
Last Modified:
01 Jan 2020 08:32