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Renewal characterization of Markov modulated Poisson processes

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  • Marcel F. Neuts
  • Ushio Sumita
  • Yoshitaka Takahashi

Abstract

A Markov Modulated Poisson Process (MMPP) M ( t ) defined on a Markov chain J ( t ) is a pure jump process where jumps of M ( t ) occur according to a Poisson process with intensity λ i whenever the Markov chain J ( t ) is in state i. M ( t ) is called strongly renewal ( S R ) if M ( t ) is a renewal process for an arbitrary initial probability vector of J ( t ) with full support on P = { i : λ i > 0 } . M ( t ) is called weakly renewal ( W R ) if there exists an initial probability vector of J ( t ) such that the resulting MMPP is a renewal process. The purpose of this paper is to develop general characterization theorems for the class S R and some sufficiency theorems for the class W R in terms of the first passage times of the bivariate Markov chain [ J ( t ) , M ( t ) ] . Relevance to the lumpability of J ( t ) is also studied.

Suggested Citation

  • Marcel F. Neuts & Ushio Sumita & Yoshitaka Takahashi, 1989. "Renewal characterization of Markov modulated Poisson processes," International Journal of Stochastic Analysis, Hindawi, vol. 2, pages 1-18, January.
  • Handle: RePEc:hin:jnijsa:531849
    DOI: 10.1155/S1048953389000043
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