In this dissertation we introduce a new estimator of the stationary probability measure of Markov processes, in the case where the transition structure depends on an unknown parameter. We prove that the proposed estimator is consistent and asymptotically normally distributed. Then we apply these ideas to Lindley processes and demonstrate via simulations the potential applicability of our estimator.
Identifier / keyword
Pure sciences, Lindley processes, Markov chains, Stationary distribution, Transition structure
Estimation of the stationary distribution of Markov chains
DAI-B 65/01, Dissertation Abstracts International
Place of publication
Country of publication
University of Massachusetts Amherst
United States -- Massachusetts
Dissertations & Theses
ProQuest document ID
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