Quasi-stationary distributions for reducible absorbing Markov chains in discrete time

P.K. Pollett, Erik A. van Doorn

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    Abstract

    We consider discrete-time Markov chains with one coffin state and a finite set $S$ of transient states, and are interested in the limiting behaviour of such a chain as time $n \to \infty,$ conditional on survival up to $n$. It is known that, when $S$ is irreducible, the limiting conditional distribution of the chain equals the (unique) quasi-stationary distribution of the chain, while the latter is the (unique) $\rho$-invariant distribution for the one-step transition probability matrix of the (sub)Markov chain on $S,$ $\rho$ being the Perron-Frobenius eigenvalue of this matrix. Addressing similar issues in a setting in which $S$ may be reducible, we identify all quasi-stationary distributions and obtain a necessary and sufficient condition for one of them to be the unique $\rho$-invariant distribution. We also reveal conditions under which the limiting conditional distribution equals the $\rho$-invariant distribution if it is unique. We conclude with some examples.
    Original languageUndefined
    Place of PublicationEnschede
    PublisherUniversity of Twente, Department of Applied Mathematics
    Number of pages16
    Publication statusPublished - Nov 2008

    Publication series

    NameMemorandum / Department of Applied Mathematics
    PublisherUniversity of Twente, Department of Applied Mathematics
    No.10/1885
    ISSN (Print)1874-4850
    ISSN (Electronic)1874-4850

    Keywords

    • limiting conditional distribution
    • IR-65084
    • Absorbing Markov chain
    • MSC-60J10
    • EWI-14022
    • survival-time distribution
    • MSC-15A18
    • rho-invariant distribution
    • METIS-252095

    Cite this

    Pollett, P. K., & van Doorn, E. A. (2008). Quasi-stationary distributions for reducible absorbing Markov chains in discrete time. (Memorandum / Department of Applied Mathematics; No. 10/1885). Enschede: University of Twente, Department of Applied Mathematics.