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Population-based reversible jump Markov chain Monte Carlo

Abstract:

We present an extension of population-based Markov chain Monte Carlo to the transdimensional case. A major challenge is that of simulating from high- and transdimensional target measures. In such cases, Markov chain Monte Carlo methods may not adequately traverse the support of the target; the simulation results will be unreliable. We develop population methods to deal with such problems, and give a result proving the uniform ergodicity of these population algorithms, under mild assumptions. ...

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Publication status:
Published

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Publisher copy:
10.1093/biomet/asm069

Authors


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Institution:
University of Oxford
Division:
MSD
Department:
NDM
Role:
Author
Journal:
BIOMETRIKA More from this journal
Volume:
94
Issue:
4
Pages:
787-807
Publication date:
2007-12-01
DOI:
EISSN:
1464-3510
ISSN:
0006-3444
Language:
English
Keywords:
Pubs id:
pubs:97531
UUID:
uuid:e918d67f-4331-4712-9e71-df3ae357ac11
Local pid:
pubs:97531
Source identifiers:
97531
Deposit date:
2012-12-19

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