The Annals of Statistics
- Ann. Statist.
- Volume 22, Number 4 (1994), 1884-1895.
Consistent and Asymptotically Normal Parameter Estimates for Hidden Markov Models
Hidden Markov models are today widespread for modeling of various phenomena. It has recently been shown by Leroux that the maximum-likelihood estimate (MLE) of the parameters of a such a model is consistent, and local asymptotic normality has been proved by Bickel and Ritov. In this paper we propose a new class of estimates which are consistent, asymptotically normal and almost as good as the MLE.
Ann. Statist., Volume 22, Number 4 (1994), 1884-1895.
First available in Project Euclid: 11 April 2007
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Ryden, Tobias. Consistent and Asymptotically Normal Parameter Estimates for Hidden Markov Models. Ann. Statist. 22 (1994), no. 4, 1884--1895. doi:10.1214/aos/1176325762. https://projecteuclid.org/euclid.aos/1176325762