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Convergence of conditional Metropolis-Hastings samplers
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Jones, Galin L., Roberts, Gareth O. and Rosenthal, Jeffrey S. (Jeffrey Seth) (2014) Convergence of conditional Metropolis-Hastings samplers. Advances in Applied Probability, Volume 46 (Number 2). pp. 422-445. doi:10.1239/aap/1401369701 ISSN 0001-8678.
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Official URL: http://dx.doi.org/10.1239/aap/1401369701
Abstract
We consider Markov chain Monte Carlo algorithms which combine Gibbs updates with Metropolis-Hastings updates, resulting in a conditional Metropolis-Hastings sampler (CMH sampler). We develop conditions under which the CMH sampler will be geometrically or uniformly ergodic. We illustrate our results by analysing a CMH sampler used for drawing Bayesian inferences about the entire sample path of a diffusion process, based only upon discrete observations.
Item Type: | Journal Article | ||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||
Journal or Publication Title: | Advances in Applied Probability | ||||
Publisher: | Applied Probability Trust | ||||
ISSN: | 0001-8678 | ||||
Official Date: | 29 May 2014 | ||||
Dates: |
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Volume: | Volume 46 | ||||
Number: | Number 2 | ||||
Page Range: | pp. 422-445 | ||||
DOI: | 10.1239/aap/1401369701 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access |
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