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Convergence of some time inhomogeneous Markov chains via spectral techniques

Author

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  • Saloff-Coste, L.
  • Zúñiga, J.

Abstract

We consider the problem of giving explicit spectral bounds for time inhomogeneous Markov chains on a finite state space. We give bounds that apply when there exists a probability [pi] such that each of the different steps corresponds to a nice ergodic Markov kernel with stationary measure [pi]. For instance, our results provide sharp bounds for models such as semi-random transpositions and semi-random insertions (in these cases [pi] is the uniform probability on the symmetric group).

Suggested Citation

  • Saloff-Coste, L. & Zúñiga, J., 2007. "Convergence of some time inhomogeneous Markov chains via spectral techniques," Stochastic Processes and their Applications, Elsevier, vol. 117(8), pages 961-979, August.
    • Handle: RePEc:eee:spapps:v:117:y:2007:i:8:p:961-979
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    Cited by:

    1. Mao, Yong-Hua & Xu, Liping & Zhang, Ming & Zhang, Yu-Hui, 2018. "Convergence in total variation distance for (in)homogeneous Markov processes," Statistics & Probability Letters, Elsevier, vol. 137(C), pages 54-62.

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