Roberts, Gareth O. and Rosenthal, Jeffrey S. (Jeffrey Seth) (2009) Quantitative non-geometric convergence bounds for independence samplers. Working Paper. University of Warwick. Centre for Research in Statistical Methodology, Coventry.

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Abstract

Markov chain Monte Carlo (MCMC) algorithms are widely used in statistics, physics, and computer science, to sample from complicated high-dimensional probability distributions. A central question is how quickly the chain converges to the target (stationarity) distribution. In this paper, we consider this question for a particular class of MCMC algorithms, independence samplers (Hastings, 1970; Tierney, 1994).

Item Type:	Working or Discussion Paper (Working Paper)
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH):	Distribution (Probability theory), Markov processes, Monte Carlo method
Series Name:	Working papers
Publisher:	University of Warwick. Centre for Research in Statistical Methodology
Place of Publication:	Coventry
Date:	2009
Volume:	Vol.2009
Number:	No.9
Number of Pages:	14
Status:	Not Peer Reviewed
Access rights to Published version:	Open Access
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URI:	http://wrap.warwick.ac.uk/id/eprint/35200

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