Sensitivity Analysis and Generalized Chaos Expansions. Lower Bounds for Sobol indices - Archive ouverte HAL Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2019

Sensitivity Analysis and Generalized Chaos Expansions. Lower Bounds for Sobol indices

Résumé

The so-called polynomial chaos expansion is widely used in computer experiments. For example, it is a powerful tool to estimate Sobol' sensitivity indices. In this paper, we consider generalized chaos expansions built on general tensor Hilbert basis. In this frame, we revisit the computation of the Sobol' indices and give general lower bounds for these indices. The case of the eigenfunctions system associated with a Poincaré differential operator leads to lower bounds involving the derivatives of the analyzed function and provides an efficient tool for variable screening. These lower bounds are put in action both on toy and real life models demonstrating their accuracy.
Fichier principal
Vignette du fichier
Sobol_lower_bound.pdf (347.64 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-02140127 , version 1 (27-05-2019)

Identifiants

Citer

Olivier Roustant, Fabrice Gamboa, Bertrand Iooss. Sensitivity Analysis and Generalized Chaos Expansions. Lower Bounds for Sobol indices. 2019. ⟨hal-02140127⟩
119 Consultations
90 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More