Importance sampling for stochastic simulations
Management Science
Parallel Object Oriented Monte Carlo Simulations
ISCOPE '98 Proceedings of the Second International Symposium on Computing in Object-Oriented Parallel Environments
Multilevel Splitting for Estimating Rare Event Probabilities
Operations Research
Splitting for rare-event simulation
Proceedings of the 38th conference on Winter simulation
Simulation of stochastic hybrid systems with switching and reflecting boundaries
Proceedings of the 40th Conference on Winter Simulation
Introduction to Rare Event Simulation
Introduction to Rare Event Simulation
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Biochemical research is increasingly using formal modeling, simulation, and analysis methods to improve the understanding of complex systems. Probabilistic analysis techniques such as Monte Carlo methods can be used to determine reachability or safety probabilities for large Stochastic Hybrid System (SHS) models, but systems containing influential rare events may require prohibitively large numbers of realizations to generate accurate estimates. In this work we present a multilevel splitting variance reduction method for SHS that improves the accuracy and efficiency of Monte Carlo methods for rare events. We apply the approach for reachability analysis of a SHS model of glycolysis, which is a biochemical energy conversion process found in virtually every living cell. We also present a method for selecting the variance reduction parameters as well as accuracy and efficiency analysis of our techniques.