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Quantitative non-geometric convergence bounds for independence samplers

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Roberts, Gareth O. and Rosenthal, Jeffrey S. (Jeffrey Seth) (2009) Quantitative non-geometric convergence bounds for independence samplers. Working Paper. Coventry: University of Warwick. Centre for Research in Statistical Methodology. Working papers, Vol.2009 (No.9).

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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
Official Date: 2009
Dates:
DateEvent
2009Published
Volume: Vol.2009
Number: No.9
Number of Pages: 14
Institution: University of Warwick
Status: Not Peer Reviewed
Access rights to Published version: Open Access

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