Estimation of the stationary distribution of Markov chains

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 ide...

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Bibliographic Details
Main Author: Garibotti, Gilda
Language:ENG
Published: ScholarWorks@UMass Amherst 2004
Subjects:
Online Access:https://scholarworks.umass.edu/dissertations/AAI3118300
Description
Summary: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.