Scaling analysis of multiple-try MCMC methods

Multiple-try methods are extensions of the Metropolis algorithm in which the next state of the Markov chain is selected among a pool of proposals. These techniques have witnessed a recent surge of interest because they lend themselves easily to parallel implementations. We consider extended versions of these methods in which some dependence structure is introduced in the proposal set, extending earlier work by Craiu and Lemieux (2007).

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Year of publication:	2012
Authors:	Bédard, Mylène ; Douc, Randal ; Moulines, Eric
Published in:	Stochastic Processes and their Applications. - Elsevier, ISSN 0304-4149. - Vol. 122.2012, 3, p. 758-786
Publisher:	Elsevier
Subject:	Random walk Metropolis \| Weak convergence \| Diffusion \| Correlated proposals \| Auxiliary random variables

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

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010875056