Consistent and Asymptotically Normal Parameter Estimates for Hidden Markov Models
The Annals of Statistics · 1994 · Volume 22 · Issue 4
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.
Keywords
62E25; 62F12; 62M09; asymptotic normality; consistency; Hidden Markov model; Identifiability; Regenerative process;
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