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SEQUENTIALLY INTERACTING MARKOV CHAIN MONTE CARLO METHODS

Abstract:

Sequential Monte Carlo (SMC) is a methodology for sampling approximately from a sequence of probability distributions of increasing dimension and estimating their normalizing constants. We propose here an alternative methodology named Sequentially Interacting Markov Chain Monte Carlo (SIMCMC). SIMCMC methods work by generating interacting non-Markovian sequences which behave asymptotically like independent Metropolis-Hastings (MH) Markov chains with the desired limiting distributions. Contrar...

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Publication status:
Published

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Publisher copy:
10.1214/09-AOS747

Authors


Brockwell, A More by this author
Del Moral, P More by this author
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Institution:
University of Oxford
Department:
Oxford, MPLS, Statistics
Journal:
ANNALS OF STATISTICS
Volume:
38
Issue:
6
Pages:
3387-3411
Publication date:
2010-12-05
DOI:
ISSN:
0090-5364
URN:
uuid:f72e3af9-654a-4cb8-98d3-c78f5b055042
Source identifiers:
172665
Local pid:
pubs:172665

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