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Moments’ Analysis in Homogeneous Markov Reward Models

Author

Listed:
  • F. Castella

    (Université de Rennes I, Campus de Beaulieu)

  • G. Dujardin

    (Université de Rennes I, Campus de Beaulieu)

  • B. Sericola

    (INRIA Rennes - Bretagne Atlantique, Campus de Beaulieu)

Abstract

We analyze the moments of the accumulated reward over the interval (0,t) in a continuous-time Markov chain. We develop a numerical procedure to compute efficiently the normalized moments using the uniformization technique. Our algorithm involves auxiliary quantities whose convergence is analyzed, and for which we provide a probabilistic interpretation.

Suggested Citation

  • F. Castella & G. Dujardin & B. Sericola, 2009. "Moments’ Analysis in Homogeneous Markov Reward Models," Methodology and Computing in Applied Probability, Springer, vol. 11(4), pages 583-601, December.
    • Handle: RePEc:spr:metcap:v:11:y:2009:i:4:d:10.1007_s11009-008-9075-5
    DOI: 10.1007/s11009-008-9075-5
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    References listed on IDEAS

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    1. Fredrik Stenberg & Raimondo Manca & Dmitrii Silvestrov, 2007. "An Algorithmic Approach to Discrete Time Non-homogeneous Backward Semi-Markov Reward Processes with an Application to Disability Insurance," Methodology and Computing in Applied Probability, Springer, vol. 9(4), pages 497-519, December.
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