Skip to Main content Skip to Navigation
Journal articles

Recommendations for the tuning of rare event probability estimators

Abstract : Being able to accurately estimate rare event probabilities is a challenging issue in order to improve the reliability of complex systems. Several powerful methods such as importance sampling, importance splitting or extreme value theory have been proposed in order to reduce the computational cost and to improve the accuracy of extreme probability estimation. However, the performance of these methods is highly correlated with the choice of tuning parameters, which are very difficult to determine. In order to highlight recommended tunings for such methods, an empirical campaign of automatic tuning on a set of representative test cases is conducted for splitting methods. This allows to provide a reduced set of tuning parameters that may lead to the reliable estimation of rare event probability for various problems. The relevance of the obtained result is assessed on a series of real-world aerospace problems.
Complete list of metadata
Contributor : Julien Marzat <>
Submitted on : Monday, September 15, 2014 - 12:57:49 PM
Last modification on : Tuesday, March 16, 2021 - 3:44:42 PM
Long-term archiving on: : Tuesday, December 16, 2014 - 10:45:49 AM


Publisher files allowed on an open archive


  • HAL Id : hal-01064029, version 1



Mathieu Balesdent, Jérôme Morio, Julien Marzat. Recommendations for the tuning of rare event probability estimators. Reliability Engineering and System Safety, Elsevier, 2015, 133, pp.68-78. ⟨hal-01064029⟩



Record views


Files downloads