Adaptive design of experiments for sobol indices estimation based on quadratic metamodel

Evgeny Burnaev, Ivan Panin

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

8 Citations (Scopus)

Abstract

Sensitivity analysis aims to identify which input parameters of a given mathematical model are the most important. One of the well-known sensitivity metrics is the Sobol sensitivity index. There is a number of approaches to Sobol indices estimation. In general, these approaches can be divided into two groups: Monte Carlo methods and methods based on metamodeling. Monte Carlo methods have well-established mathematical apparatus and statistical properties. However, they require a lot of model runs. Methods based on metamodeling allow to reduce a required number of model runs, but may be difficult for analysis. In this work, we focus on metamodeling approach for Sobol indices estimation, and particularly, on the initial step of this approach — design of experiments. Based on the concept of D-optimality, we propose a method for construction of an adaptive experimental design, effective for calculation of Sobol indices from a quadratic metamodel. Comparison of the proposed design of experiments with other methods is performed.

Original languageEnglish
Title of host publicationStatistical Learning and Data Sciences - 3rd International Symposium, SLDS 2015, Proceedings
EditorsAlexander Gammerman, Vladimir Vovk, Harris Papadopoulos
PublisherSpringer Verlag
Pages86-95
Number of pages10
Volume9047
ISBN (Print)9783319170909
DOIs
Publication statusPublished - 2015
Externally publishedYes
Event3rd International Symposium on Statistical Learning and Data Sciences, SLDS 2015 - Egham, United Kingdom
Duration: 20 Apr 201523 Apr 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9047
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Symposium on Statistical Learning and Data Sciences, SLDS 2015
Country/TerritoryUnited Kingdom
CityEgham
Period20/04/1523/04/15

Keywords

  • Active learning
  • Adaptive design of experiments
  • D-optimality
  • Global sensitivity analysis
  • Sobol indices

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