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Estimating and quantifying uncertainties on level sets using the vorob’ev expectation and deviation with gaussian process models
Auteur(s)
Date de parution
2013
De la page
35
A la page
43
Résumé
Several methods based on Kriging have recently been proposed for calculating a probability of failure involving costly-to-evaluate functions. A closely related problem is to estimate the set of inputs leading to a response exceeding a given threshold. Now, estimating such a level set—and not solely its volume—and quantifying uncertainties on it are not straightforward. Here we use notions from random set theory to obtain an estimate of the level set, together with a quantification of estimation uncertainty. We give explicit formulae in the Gaussian process set-up and provide a consistency result. We then illustrate how space-filling versus adaptive design strategies may sequentially reduce level set estimation uncertainty.
Notes
, 2013
Nom de l'événement
mODa 10 – Advances in Model-Oriented Design and Analysis
Lieu
Łagów Lubuski, Poland
Autre version
http://link.springer.com/chapter/10.1007%2F978-3-319-00218-7_5
Type de publication
Resource Types::text::conference output::conference proceedings::conference paper
