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Particle methods for maximum likelihood estimation in latent variable models
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Johansen, Adam M., Doucet, Arnaud and Davy, Manuel (2008) Particle methods for maximum likelihood estimation in latent variable models. Statistics and Computing, Vol.18 (No.1). pp. 47-57. doi:10.1007/s11222-007-9037-8 ISSN 0960-3174.
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Official URL: http://dx.doi.org/10.1007/s11222-007-9037-8
Abstract
Standard methods for maximum likelihood parameter estimation
in latent variable models rely on the Expectation-Maximization algorithm and
its Monte Carlo variants. Our approach is different and motivated by similar
considerations to simulated annealing; that is we build a sequence of artificial
distributions whose support concentrates itself on the set of maximum likelihood estimates. We sample from these distributions using a sequential Monte
Carlo approach. We demonstrate state of the art performance for several applications of the proposed approach.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||
Library of Congress Subject Headings (LCSH): | Parameter estimation, Latent variables | ||||
Journal or Publication Title: | Statistics and Computing | ||||
Publisher: | Springer | ||||
ISSN: | 0960-3174 | ||||
Official Date: | 2008 | ||||
Dates: |
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Volume: | Vol.18 | ||||
Number: | No.1 | ||||
Page Range: | pp. 47-57 | ||||
DOI: | 10.1007/s11222-007-9037-8 | ||||
Status: | Peer Reviewed | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Date of first compliant deposit: | 17 December 2015 | ||||
Date of first compliant Open Access: | 17 December 2015 |
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