Journal
JOURNAL OF STATISTICAL PLANNING AND INFERENCE
Volume 108, Issue 1-2, Pages 365-390Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/S0378-3758(02)00318-X
Keywords
EM algorithm; hidden Markov model; incomplete data; maxinnim likelihood; maximum pseudo-likelihood; mean-field approximations; method of moments
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The problem of estimating parameters within hidden Markov models is not straightforward. In particular, calculation of maximum likelihood estimates (MLE) is nontrivial. Some variations on MLE are described that are computationally less burdensome, and detailed comparisons are drawn for the case of hidden binary isotropic Markov chains. (C) 2002 Elsevier Science B.V. All rights reserved.
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