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Abstract: In this paper, we consider the consistency and asymptotic normality of the maximum likelihood estimator for a possibly non stationary Hidden Markov Model where the hidden state space is a separable and compact space non necessarily finite, and both the transition kernel of the hidden chain and the conditional distribution of the observations depend on a parameter `. For identifiable models, consistency and asymptotic normality of the maximum likelihood estimator is shown to follow from... (Update)
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BibTeX entry: (Update)
R. Douc and C. Matias Asymptotics of the maximum likelihood estimator for general hidden Markov models, Bernouilli, vol 3, 381-420, 2001. http://citeseer.ist.psu.edu/douc01asymptotics.html More
@misc{ douc01asymptotics,
author = "R. Douc and C. Matias",
title = "Asymptotics of the maximum likelihood estimator for general hidden Markov
models",
text = "R. Douc and C. Matias Asymptotics of the maximum likelihood estimator
for general hidden Markov models, Bernouilli, vol 3, 381-420, 2001.",
year = "2001",
url = "citeseer.ist.psu.edu/douc01asymptotics.html" }
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