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A representation formula for the large deviation rate function for the empirical law of a continuous time Markov chain

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  • Baldi, Paolo
  • Piccioni, Mauro

Abstract

We prove a representation formula for the rate function of the Large Deviation Principle for the empirical distribution of an irreducible continuous time Markov process on a finite state space. We use this representation to characterize asymptotically efficient intensities for the Monte Carlo evaluation of probabilities of a large deviation for the empirical distribution.

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  • Baldi, Paolo & Piccioni, Mauro, 1999. "A representation formula for the large deviation rate function for the empirical law of a continuous time Markov chain," Statistics & Probability Letters, Elsevier, vol. 41(2), pages 107-115, January.
    • Handle: RePEc:eee:stapro:v:41:y:1999:i:2:p:107-115
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    Cited by:

    1. Macci, Claudio & Torrisi, Giovanni Luca, 2004. "Asymptotic results for perturbed risk processes with delayed claims," Insurance: Mathematics and Economics, Elsevier, vol. 34(2), pages 307-320, April.
    2. Gao, Fuqing & Yan, Jun, 2009. "Sample path large and moderate deviations for risk model with delayed claims," Insurance: Mathematics and Economics, Elsevier, vol. 45(1), pages 74-80, August.
    3. Macci, Claudio, 2009. "Convergence of large deviation rates based on a link between wave governed random motions and ruin processes," Statistics & Probability Letters, Elsevier, vol. 79(2), pages 255-263, January.

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