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Limiting Distributions of a Non-Homogeneous Markov System in a Stochastic Environment in Continuous Time

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  • P. -C. G. Vassiliou

    (Department of Statistical Sciences, University College London, Gower St., London WC1E 6BT, UK)

Abstract

The stochastic process non-homogeneous Markov system in a stochastic environment in continuous time (S-NHMSC) is introduced in the present paper. The ordinary non-homogeneous Markov process is a very special case of an S-NHMSC. I studied the expected population structure of the S-NHMSC, the first central classical problem of finding the conditions under which the asymptotic behavior of the expected population structure exists and the second central problem of finding which expected relative population structures are possible limiting ones, provided that the limiting vector of input probabilities into the population is controlled. Finally, the rate of convergence was studied.

Suggested Citation

  • P. -C. G. Vassiliou, 2022. "Limiting Distributions of a Non-Homogeneous Markov System in a Stochastic Environment in Continuous Time," Mathematics, MDPI, vol. 10(8), pages 1-16, April.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:8:p:1214-:d:789063
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    References listed on IDEAS

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    1. Zeifman, A. I. & Isaacson, Dean L., 1994. "On strong ergodicity for nonhomogeneous continuous-time Markov chains," Stochastic Processes and their Applications, Elsevier, vol. 50(2), pages 263-273, April.
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    9. Zeifman, A.I. & Korolev, V.Yu. & Satin, Ya.A. & Kiseleva, K.M., 2018. "Lower bounds for the rate of convergence for continuous-time inhomogeneous Markov chains with a finite state space," Statistics & Probability Letters, Elsevier, vol. 137(C), pages 84-90.
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