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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Language: | ENG |
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ScholarWorks@UMass Amherst
2004
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Online Access: | https://scholarworks.umass.edu/dissertations/AAI3118300 |
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. |
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