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Entropy Maximization for Markov and Semi-Markov Processes

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  • Valerie Girardin

    (Université de Caen)

Abstract

The literature about maximum of entropy for Markov processes deals mainly with discrete-time Markov chains. Very few papers dealing with continuous-time jump Markov processes exist and none dealing with semi-Markov processes. It is the aim of this paper to contribute to fill this lack. We recall the basics concerning entropy for Markov and semi-Markov processes and we study several problems to give an overview of the possible directions of use of maximum entropy in connection with these processes. Numeric illustrations are presented, in particular in application to reliability.

Suggested Citation

  • Valerie Girardin, 2004. "Entropy Maximization for Markov and Semi-Markov Processes," Methodology and Computing in Applied Probability, Springer, vol. 6(1), pages 109-127, March.
    • Handle: RePEc:spr:metcap:v:6:y:2004:i:1:d:10.1023_b:mcap.0000012418.88825.18
    DOI: 10.1023/B:MCAP.0000012418.88825.18
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    Cited by:

    1. Valérie Girardin & Loick Lhote & Philippe Regnault, 2019. "Different Closed-Form Expressions for Generalized Entropy Rates of Markov Chains," Methodology and Computing in Applied Probability, Springer, vol. 21(4), pages 1431-1452, December.
    2. Valérie Girardin & André Sesboüé, 2009. "Comparative Construction of Plug-in Estimators of the Entropy Rate of Two-state Markov Chains," Methodology and Computing in Applied Probability, Springer, vol. 11(2), pages 181-200, June.

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