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Perfect posterior simulation for mixture and hidden Markov models

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Berthelsen, Kasper K., Breyer, Laird A. and Roberts, Gareth O. (2010) Perfect posterior simulation for mixture and hidden Markov models. LMS Journal of Computation and Mathematics, Vol.13 . pp. 246-259. doi:10.1112/S1461157007000022

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Official URL: http://dx.doi.org/10.1112/S1461157007000022

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Abstract

In this paper we present an application of the read-once coupling from the past algorithm to problems in Bayesian inference for latent statistical models. We describe a method for perfect simulation from the posterior distribution of the unknown mixture weights in a mixture model. Our method is extended to a more general mixture problem, where unknown parameters exist for the mixture components, and to a hidden Markov model.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science, Engineering and Medicine > Science > Statistics
Library of Congress Subject Headings (LCSH): Mathematical models, Mathematical statistics, Distribution (Probability theory)
Journal or Publication Title: LMS Journal of Computation and Mathematics
Publisher: Cambridge University Press
ISSN: 1461-1570
Official Date: 10 August 2010
Dates:
DateEvent
10 August 2010Published
Volume: Vol.13
Number of Pages: 14
Page Range: pp. 246-259
DOI: 10.1112/S1461157007000022
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Funder: European Union (EU), Engineering and Physical Sciences Research Council (EPSRC), Statens naturvidenskabelige forskningsråd (Denmark) [Natural Science Research Council]
Grant number: ERB-FMRX-CT96-0095 (EU), 272-06-0442 (DNSRC)

Data sourced from Thomson Reuters' Web of Knowledge

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