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Persistent link: https://www.econbiz.de/10001928203
This paper reports simulation experiments, applying the cross entropy method suchas the importance sampling algorithm for efficient estimation of rare event probabilities in Markovian reliability systems. The method is compared to various failurebiasing schemes that have been proved to give...
Persistent link: https://www.econbiz.de/10011334846
There are various importance sampling schemes to estimate rare event probabilities in Markovian systems such as Markovian reliability models and Jackson networks. In this work, we present a general state dependent importance sampling method which partitions the state space and applies the...
Persistent link: https://www.econbiz.de/10010325747
In rare event simulation, we look for estimators such that the relative accuracy of the output is ''controlled'' when the rarity is getting more and more critical. Different robustness properties have been defined in the literature, that an estimator is expected to satisfy. Though, those...
Persistent link: https://www.econbiz.de/10010326256
There are various importance sampling schemes to estimate rare event probabilities in Markovian systems such as Markovian reliability models and Jackson networks. In this work, we present a general state dependent importance sampling method which partitions the state space and applies the...
Persistent link: https://www.econbiz.de/10014203542
Persistent link: https://www.econbiz.de/10010191281
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Persistent link: https://www.econbiz.de/10003888073
There are various importance sampling schemes to estimate rare event probabilities in Markovian systems such as Markovian reliability models and Jackson networks. In this work, we present a general state dependent importance sampling method which partitions the state space and applies the...
Persistent link: https://www.econbiz.de/10011379128