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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. 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

Subjects:

Q Science > QA Mathematics

Divisions:

Faculty of 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:

Date	Event
2008	Published

Volume:

Vol.18

Number:

No.1

Page Range:

pp. 47-57

Identification Number:

10.1007/s11222-007-9037-8

Status:

Peer Reviewed

Access rights to Published version:

Restricted or Subscription Access

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