Kriging-based adaptive Importance Sampling algorithms for rare event estimation

Very efficient sampling algorithms have been proposed to estimate rare event probabilities, such as Importance Sampling or Importance Splitting. Even if the number of samples required to apply these techniques is relatively low compared to Monte-Carlo simulations of same efficiency, it is often diff...

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Bibliographic Details
Published in:	Structural safety Vol. 44; pp. 1 - 10
Main Authors:	Balesdent, Mathieu, Morio, Jérôme, Marzat, Julien
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier Ltd 01.09.2013 Elsevier
Subjects:	Algorithms Applied sciences Computer simulation Estimates Exact sciences and technology Ground, air and sea transportation, marine construction Importance Sampling Input–output function Kriging Marine construction Rare event estimation Samples Sampling Statistical analysis Statistical methods Surrogate model Surrogate model Importance Sampling Input–output function Kriging Rare event estimation Estimation Aeronautics Spacecraft Probability Input-output function Rare event Modeling Adaptive method Statistics Case study Input output analysis Launching Safety Sampling
ISSN:	0167-4730, 1879-3355
Online Access:	Get full text
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