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Variance-Based Sensitivity Analysis: Theory and Estimation Algorithms

  • Clémentine PrieurEmail author
  • Stefano Tarantola
Reference work entry

Abstract

This section aims at presenting an overview of variance-based approaches for global sensitivity analysis. Starting from functional ANOVA, Sobol’ indices are first defined and then estimation algorithms are provided. The performance of these algorithms is theorically and practically discussed. The review includes recent results on the topic.

Keywords

FANOVA Sobol’ sensitivity indices Global sensitivity analysis Monte Carlo sampling Quasi-Monte Carlo sampling Sampling design Replication Latin hypercube sampling Orthogonal arrays (OA) Spectral methods Fourier amplitude sensitivity test Random balance design Effective algorithm for sensitivity indices Polynomial chaos expansion effective dimension Sensitivity indices with given data 

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Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  1. 1.Laboratoire Jean Kuntzmann (LJK)University of Grenoble Alpes, INRIAGrenobleFrance
  2. 2.Statistical Indicators for Policy AssessmentJoint Research Centre of the European CommissionIspra (VA)Italy

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