Sensitivity analysis in general metric spaces

Fabrice Gamboa, Thierry Klein, Lagnoux, Agnès and Leonardo Moreno

Reliability Engineering and System Safety, 2021, vol. 212, issue C

Abstract: Sensitivity indices are commonly used to quantity the relative influence of any specific group of input variables on the output of a computer code. In this paper, we introduce new sensitivity indices adapted to outputs valued in general metric spaces. This new class of indices encompasses the classical ones; in particular, the so-called Sobol indices and the Cramér–von-Mises indices. Furthermore, we provide asymptotically Gaussian estimators of these indices based on U-statistics. Surprisingly, we prove the asymptotic normality straightforwardly. Finally, we illustrate this new procedure on a toy model and on two real-data examples.

Keywords: Sensitivity analysis; Cramér–von-Mises distance; Pick-Freeze method; U-statistics; General metric spaces (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:212:y:2021:i:c:s0951832021001563

DOI: 10.1016/j.ress.2021.107611

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