Importance sampling for continuous time Markov chains and applications to fluid models

DOI10.1023/A:1010050800089zbMath0991.65009OpenAlexW92099507MaRDI QIDQ1973907

Paolo Baldi, Mauro Piccioni

Publication date: 1 September 2002

Published in: Methodology and Computing in Applied Probability (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1023/a:1010050800089

zbMATH Keywords

importance samplingMonte Carlo simulationlarge deviationslevel crossingasymptotic meanasymptotically efficient simulationfinite state continuous time Markov processMarkov fluid

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Queueing theory (aspects of probability theory) (60K25) Numerical analysis or methods applied to Markov chains (65C40) Large deviations (60F10) Continuous-time Markov processes on discrete state spaces (60J27)

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Convergence of large deviation rates based on a link between wave governed random motions and ruin processes ⋮ A representation formula for the large deviation rate function for the empirical law of a continuous time Markov chain ⋮ Large Deviation Results for Wave Governed Random Motions Driven by Semi-Markov Processes

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