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Sensitivity analysis in general metric spaces

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

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.

Suggested Citation

  • Gamboa, Fabrice & Klein, Thierry & Lagnoux, Agnès & Moreno, Leonardo, 2021. "Sensitivity analysis in general metric spaces," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    • Handle: RePEc:eee:reensy:v:212:y:2021:i:c:s0951832021001563
    DOI: 10.1016/j.ress.2021.107611
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    References listed on IDEAS

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