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Model selection by MCMC computation

Abstract:

MCMC sampling is a methodology that is becoming increasingly important in statistical signal processing. It has been of particular importance to the Bayesian-based approaches to signal processing since it extends significantly the range of problems that they can address. MCMC techniques generate samples from desired distributions by embedding them as limiting distributions of Markov chains. There are many ways of categorizing MCMC methods, but the simplest one is to classify them in one of tw...

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Publication status:
Published

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Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
Journal:
SIGNAL PROCESSING More from this journal
Volume:
81
Issue:
1
Pages:
19-37
Publication date:
2001-01-01
DOI:
ISSN:
0165-1684
Language:
English
Keywords:
Pubs id:
pubs:190621
UUID:
uuid:08d89e15-b0df-4b25-bf49-1d70c53a9829
Local pid:
pubs:190621
Source identifiers:
190621
Deposit date:
2012-12-19

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