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Improved estimators for constrained Markov chain models

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  • Müller, Ursula U.
  • Schick, Anton
  • Wefelmeyer, Wolfgang
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    Abstract

    Suppose we observe an ergodic Markov chain and know that the stationary law of one or two successive observations fulfills a linear constraint. We show how to improve the given estimators exploiting this knowledge, and prove that the best of these estimators is efficient.

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    Bibliographic Info

    Article provided by Elsevier in its journal Statistics & Probability Letters.

    Volume (Year): 54 (2001)
    Issue (Month): 4 (October)
    Pages: 427-435

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    Handle: RePEc:eee:stapro:v:54:y:2001:i:4:p:427-435

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    Related research

    Keywords: Empirical estimator Asymptotically linear estimator Influence function Regular estimator Markov chain model Reversible chain Symmetric chain Linear autoregression;

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    Cited by:
    1. Jernigan, Robert W. & Baran, Robert H., 2003. "Testing lumpability in Markov chains," Statistics & Probability Letters, Elsevier, vol. 64(1), pages 17-23, August.

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