Maximum Likelihood Estimator for Hidden Markov Models in continuous time
arXiv:0707.0271 · doi:10.1007/s11203-008-9025-4
Abstract
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.
Warning: due to a flaw in the publishing process, some of the references in the published version of the article are confused