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Perfect simulation of steady-state Markov chain on mixed state space

Author

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  • Az-eddine Zakrad
  • Abdelaziz Nasroallah

Abstract

In this work, we propose to combine the standard coupling from the past and the multi-gamma coupler algorithms to allow perfect simulation of the steady-state probability of a Markov chain (MC), whose state space E is composed of a continuous part C and a finite part D. We show that for some families of mixed transition kernels of a MC on E, the computation of the steady-state probability returns to the computation of the steady-state probabilities of two MCs: Xc on C and Xd on D. A basic numerical Monte Carlo example is studied to show the smooth running of the proposed hybrid algorithm.

Suggested Citation

  • Az-eddine Zakrad & Abdelaziz Nasroallah, 2022. "Perfect simulation of steady-state Markov chain on mixed state space," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 51(6), pages 1569-1587, March.
    • Handle: RePEc:taf:lstaxx:v:51:y:2022:i:6:p:1569-1587
    DOI: 10.1080/03610926.2021.1924783
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