Limit Theorems in Hidden Markov Models

Details Limit Theorems in Hidden Markov Models Limit Theorems in Hidden Markov Models

2011-02-02

arxiv.org/abs/1102.0365v2

Computer Science

Information Theory

35 pages

Scientific paper

In this paper, under mild assumptions, we derive a law of large numbers, a central limit theorem with an error estimate, an almost sure invariance principle and a variant of Chernoff bound in finite-state hidden Markov models. These limit theorems are of interest in certain ares in statistics and information theory. Particularly, we apply the limit theorems to derive the rate of convergence of the maximum likelihood estimator in finite-state hidden Markov models.

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