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Interacting sequential Monte Carlo samplers for trans-dimensional simulation

Abstract:

The methodology of interacting sequential Monte Carlo (SMC) samplers is introduced. SMC samplers are methods for sampling from a sequence of densities on a common measurable space using a combination of Markov chain Monte Carlo (MCMC) and sequential importance sampling/resampling (SIR) methodology. One of the main problems with SMC samplers when simulating from trans-dimensional, multimodal static targets is that transition kernels do not mix which leads to low particle diversity. In such sit...

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Publication status:
Published

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Publisher copy:
10.1016/j.csda.2007.09.009

Authors


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Institution:
University of Oxford
Department:
Oxford, MPLS, Statistics
Stephens, DA More by this author
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Institution:
University of Oxford
Department:
Oxford, MPLS, Statistics, Clinical Medicine
Journal:
COMPUTATIONAL STATISTICS and DATA ANALYSIS
Volume:
52
Issue:
4
Pages:
1765-1791
Publication date:
2008-01-10
DOI:
ISSN:
0167-9473
URN:
uuid:4712befa-6940-470c-bb65-4b138b7833d7
Source identifiers:
97529
Local pid:
pubs:97529

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