Estimating the approximation error when fixing unessential factors in global sensitivity analysis
Résumé
One of the major settings of global sensitivity analysis is that of fixing non-influential factors, in order to reduce the dimensionality of a model. However, this is often done without knowing the magnitude of the approximation error being produced. This paper presents a new theorem for the estimation of the average approximation error generated when fixing a group of non-influential factors. A simple function where analytical solutions are available is used to illustrate the theorem. The numerical estimation of small sensitivity indices is discussed.
Domaines
Mathématiques [math]| Origine | Fichiers produits par l'(les) auteur(s) |
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