Importance Splitting for Finite-Time Rare Event Simulation
In this note, a general framework is proposed for using importance splitting to estimate rare event probabilities with finite-time constraints. We prove that the splitting estimator is unbiased and characterize the optimal splitting curves. A new unbiased estimator with truncated sample paths is pro...
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Veröffentlicht in: | IEEE transactions on automatic control 2018-06, Vol.63 (6), p.1760-1767 |
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Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In this note, a general framework is proposed for using importance splitting to estimate rare event probabilities with finite-time constraints. We prove that the splitting estimator is unbiased and characterize the optimal splitting curves. A new unbiased estimator with truncated sample paths is proposed to improve computational efficiency, and a pilot algorithm is provided to determine the optimal truncation and splitting curves. Numerical examples illustrate the optimality of the splitting curves and the effectiveness of the new estimator. |
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ISSN: | 0018-9286 1558-2523 |
DOI: | 10.1109/TAC.2017.2758171 |