On reparametrization and the Gibbs sampler

Gibbs samplers derived under different parametrizations of the target density can have radically different rates of convergence. In this article, we specify conditions under which reparametrization leaves the convergence rate of a Gibbs chain unchanged. An example illustrates how these results can be exploited in convergence rate analyses.

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Year of publication:	2014
Authors:	Román, Jorge Carlos ; Hobert, James P. ; Presnell, Brett
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 91.2014, C, p. 110-116
Publisher:	Elsevier
Subject:	Markov chain \| Geometric ergodicity \| Monte Carlo \| Convergence rate \| Parametrization

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011039965