Effective design for sobol indices estimation based on polynomial chaos expansions

Evgeny Burnaev, Ivan Panin, Bruno Sudret

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

Abstract

Sobol’ indices are a common metric of dependency in sensitivity analysis. It is used as a measure of confidence of input variables influence on the output of the analyzed mathematical model. We consider a problem of selection of experimental design points for Sobol’ indices estimation. Based on the concept of D-optimality, we propose a method for constructing an adaptive design of experiments, effective for the calculation of Sobol’ indices from Polynomial Chaos Expansions. We provide a set of applications that demonstrate the efficiency of the proposed approach.

Original languageEnglish
Title of host publicationConformal and Probabilistic Prediction with Applications - 5th International Symposium, COPA 2016, Proceedings
EditorsJesus Vega, Alexander Gammerman, Zhiyuan Luo, Vladimir Vovk
PublisherSpringer Verlag
Pages165-184
Number of pages20
ISBN (Print)9783319333946
DOIs
Publication statusPublished - 2016
Externally publishedYes
Event5th International Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2016 - Madrid, Spain
Duration: 20 Apr 201622 Apr 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9653
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2016
Country/TerritorySpain
CityMadrid
Period20/04/1622/04/16

Keywords

  • Active learning
  • Design of experiment
  • Polynomial chaos expansions
  • Sensitivity analysis
  • Sobol indices

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