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Maximum likelihood parameter estimation for latent variable models using sequential Monte Carlo
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Johansen, Adam M., Doucet, Arnaud and Davy, Manuel (2006) Maximum likelihood parameter estimation for latent variable models using sequential Monte Carlo. In: IEEE International Conference on Acoustics, Speech and Signal Processing, Toulouse , 2006 May 14-19 doi:10.1109/ICASSP.2006.1660735
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Official URL: http://dx.doi.org/10.1109/ICASSP.2006.1660735
Abstract
We present a sequential Monte Carlo (SMC) method for maximum
likelihood (ML) parameter estimation in latent variable models. Standard
methods rely on gradient algorithms such as the Expectation-
Maximization (EM) algorithm and its Monte Carlo variants. Our
approach is different and motivated by similar considerations to simulated
annealing (SA); that is we propose to sample from a sequence
of artificial distributions whose support concentrates itself on the set
of ML estimates. To achieve this we use SMC methods. We conclude
by presenting simulation results on a toy problem and a nonlinear
non-Gaussian time series model.
Item Type: | Conference Item (Paper) | ||||
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Subjects: | Q Science > QA Mathematics | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||
Library of Congress Subject Headings (LCSH): | Monte Carlo method, Parameter estimation, Latent variables | ||||
Book Title: | 2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings | ||||
Official Date: | 2006 | ||||
Dates: |
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DOI: | 10.1109/ICASSP.2006.1660735 | ||||
Status: | Peer Reviewed | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Date of first compliant deposit: | 1 August 2016 | ||||
Date of first compliant Open Access: | 1 August 2016 | ||||
Conference Paper Type: | Paper | ||||
Title of Event: | IEEE International Conference on Acoustics, Speech and Signal Processing | ||||
Type of Event: | Conference | ||||
Location of Event: | Toulouse | ||||
Date(s) of Event: | 2006 May 14-19 |
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