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Moderate deviation principle for maximum likelihood estimator for Markov processes

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  • Prakasa Rao, B.L.S.

Abstract

After a short review of the properties of the maximum likelihood estimator for discrete time Markov processes, we obtain a moderate deviation result for such an estimator under some regularity conditions using the Gärtner–Ellis theorem for random processes.

Suggested Citation

  • Prakasa Rao, B.L.S., 2018. "Moderate deviation principle for maximum likelihood estimator for Markov processes," Statistics & Probability Letters, Elsevier, vol. 132(C), pages 74-82.
    • Handle: RePEc:eee:stapro:v:132:y:2018:i:c:p:74-82
    DOI: 10.1016/j.spl.2017.09.009
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    References listed on IDEAS

    as
    1. Xiao, Zhihong & Liu, Luqin, 2006. "Moderate deviations of maximum likelihood estimator for independent not identically distributed case," Statistics & Probability Letters, Elsevier, vol. 76(10), pages 1056-1064, May.
    2. Gao, Fuqing, 2001. "Moderate deviations for the maximum likelihood estimator," Statistics & Probability Letters, Elsevier, vol. 55(4), pages 345-352, December.
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