Title :
Importance sampling in Markovian settings
Author :
Sandmann, Werner
Author_Institution :
Dept. of Inf. Syst. & Appl. Comput. Sci., Bamberg Univ., Germany
Abstract :
Rare event simulation for stochastic models of complex systems is still a great challenge even for Markovian models. We review results in importance sampling for Markov chains, provide new viewpoints and insights, and we pose some future research directions.
Keywords :
Markov processes; discrete event simulation; importance sampling; Markov chains; Markov model; complex system; importance sampling; rare event simulation; stochastic model; Computational modeling; Computer simulation; Density measurement; Discrete event simulation; Markov processes; Monte Carlo methods; Power system reliability; Stochastic processes; Stochastic systems; Yield estimation;
Conference_Titel :
Simulation Conference, 2005 Proceedings of the Winter
Print_ISBN :
0-7803-9519-0
DOI :
10.1109/WSC.2005.1574288
