Maximum Likelihood Estimator for Hidden Markov Models in continuous time

Details Maximum Likelihood Estimator for Hidden Markov Models in continuous time Maximum Likelihood Estimator for Hidden Markov Models in continuous time

2007-07-02

arxiv.org/abs/0707.0271v4

Statistical Inference for Stochastic Processes, Volume 12, Number 2 / June, 2009, pp. 139-163

Mathematics

Probability

Warning: due to a flaw in the publishing process, some of the references in the published version of the article are confused

Scientific paper

10.1007/s11203-008-9025-4

The paper studies large sample asymptotic properties of the Maximum Likelihood Estimator (MLE) for the parameter of a continuous time Markov chain, observed in white noise. Using the method of weak convergence of likelihoods due to I.Ibragimov and R.Khasminskii, consistency, asymptotic normality and convergence of moments are established for MLE under certain strong ergodicity conditions of the chain.

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