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On the ergodic decomposition for a class of Markov chains

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  • Costa, O.L.V.
  • Dufour, F.
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    Abstract

    In this paper we present sufficient conditions for the Doeblin decomposition, and necessary and sufficient conditions for an ergodic decomposition for a Markov chain satisfying a T'-condition, which is a condition adapted from the paper (Statist. and Probab. Lett. 50 (2000) 13). Under no separability assumption on the [sigma]-field, it is shown that the T'-condition is sufficient for the condition that there are no uncountable disjoint absorbing sets and, under some hypothesis, it is also necessary. For the case in which the [sigma]-field is countable generated and separated, this condition is equivalent to the existence of a T continuous component for the Markov chain. Furthermore, under the assumption that the space is a compact separable metric space, it is shown that the Foster-Lyapunov criterion is necessary and sufficient for the existence of an invariant probability measure for the Markov chain, and that every probability measure for the Markov chain is, in this case, non-singular.

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    Bibliographic Info

    Article provided by Elsevier in its journal Stochastic Processes and their Applications.

    Volume (Year): 115 (2005)
    Issue (Month): 3 (March)
    Pages: 401-415

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    Handle: RePEc:eee:spapps:v:115:y:2005:i:3:p:401-415

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    Related research

    Keywords: Markov chain Invariant probability measures Countable ergodic decomposition;

    References

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    1. Costa, O. L. V. & Dufour, F., 2000. "Invariant probability measures for a class of Feller Markov chains," Statistics & Probability Letters, Elsevier, vol. 50(1), pages 13-21, October.
    2. Tweedie, R. L., 2001. "Drift conditions and invariant measures for Markov chains," Stochastic Processes and their Applications, Elsevier, vol. 92(2), pages 345-354, April.
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    Cited by:
    1. Frank H. Page & Myrna H. Wooders, 2009. "Endogenous Network Dynamics," Working Papers 2009.28, Fondazione Eni Enrico Mattei.

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