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December, 1994 Consistent and Asymptotically Normal Parameter Estimates for Hidden Markov Models
Tobias Ryden
Ann. Statist. 22(4): 1884-1895 (December, 1994). DOI: 10.1214/aos/1176325762

Abstract

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.

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Tobias Ryden. "Consistent and Asymptotically Normal Parameter Estimates for Hidden Markov Models." Ann. Statist. 22 (4) 1884 - 1895, December, 1994. https://doi.org/10.1214/aos/1176325762

Information

Published: December, 1994
First available in Project Euclid: 11 April 2007

zbMATH: 0831.62060
MathSciNet: MR1329173
Digital Object Identifier: 10.1214/aos/1176325762

Subjects:
Primary: 62M09
Secondary: 62E25, 62F12

Rights: Copyright © 1994 Institute of Mathematical Statistics

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Vol.22 • No. 4 • December, 1994
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