Support indices: Measuring the effect of input variables over their supports

Abstract : Two new sensitivity indices are presented which give an original solution to the question in sensitivity analysis of how to determine regions within the input space for which the model variation is high. The indices, as functions over the input domain, give insight into the local in uence of input variables over the whole domain when the other variables lie in the global domain. They can serve as an informative extension to a standard analysis and in addition are especially helpful in the specification of the input domain, a critical, but often vaguely handled issue in sensitivity analysis. In the usual framework of independent continuous input variables, we present theoretical results that show an asymptotic connection between the presented indices and Sobol' indices, valid for general probability distribution functions. Finally, we show how the indices can be successfully applied on analytical examples and on a real application.
Document type :
Preprints, Working Papers, ...
Liste complète des métadonnées

Cited literature [6 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01113555
Contributor : Jana Fruth <>
Submitted on : Wednesday, September 26, 2018 - 9:46:25 AM
Last modification on : Tuesday, October 23, 2018 - 2:36:09 PM
Document(s) archivé(s) le : Thursday, December 27, 2018 - 6:47:06 PM

File

FruRouKuh_RESS.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01113555, version 4

Collections

Citation

J Fruth, O Roustant, S Kuhnt. Support indices: Measuring the effect of input variables over their supports. 2018. ⟨hal-01113555v4⟩

Share

Metrics

Record views

47

Files downloads

38