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Adaptive Gibbs samplers
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Łatuszyński, Krzysztof and Rosenthal, Jeffrey S. (Jeffrey Seth) (2010) Adaptive Gibbs samplers. Working Paper. Coventry: University of Warwick. Centre for Research in Statistical Methodology. Working papers, Vol.2010 (No.2).
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Official URL: http://www2.warwick.ac.uk/fac/sci/statistics/crism...
Abstract
We consider various versions of adaptive Gibbs and Metropolis-
within-Gibbs samplers, which update their selection probabilities (and perhaps also their proposal distributions) on the
fly during a run, by learning
as they go in an attempt to optimise the algorithm. We present a cautionary
example of how even a simple-seeming adaptive Gibbs sampler may fail to
converge. We then present various positive results guaranteeing convergence
of adaptive Gibbs samplers under certain conditions.
Item Type: | Working or Discussion Paper (Working Paper) | ||||
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Subjects: | Q Science > QA Mathematics | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||
Library of Congress Subject Headings (LCSH): | Sampling (Statistics) | ||||
Series Name: | Working papers | ||||
Publisher: | University of Warwick. Centre for Research in Statistical Methodology | ||||
Place of Publication: | Coventry | ||||
Official Date: | 2010 | ||||
Dates: |
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Volume: | Vol.2010 | ||||
Number: | No.2 | ||||
Number of Pages: | 30 | ||||
Status: | Not Peer Reviewed | ||||
Access rights to Published version: | Open Access (Creative Commons) | ||||
Date of first compliant deposit: | 1 August 2016 | ||||
Date of first compliant Open Access: | 1 August 2016 | ||||
Funder: | Natural Sciences and Engineering Research Council of Canada (NSERC) |
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