A review on global sensitivity analysis methods

@inproceedings{Iooss2017ARO,
  title={A review on global sensitivity analysis methods},
  author={Bertrand Iooss and Paul Lem{\^a}ıtre},
  year={2017}
}
This chapter makes a review, in a complete methodological framework, of various global sensitivity analysis methods of model output. Numerous statistical and probabilistic tools (regression, smoothing, tests, statistical learning, Monte Carlo, . . . ) aim at determining the model input variables which mostly contribute to an interest quantity depending on model output. This quantity can be for instance the variance of an output variable. Three kinds of methods are distinguished: the screening… CONTINUE READING
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The design and analysis of computer experiments

  • T. Santner, B. Williams, W. Notz
  • Springer,
  • 2003
Highly Influential
7 Excerpts

Revue sur l’analyse de sensibilité globale de modèles numériques

  • B. Iooss
  • Journal de la Société Française de Statistique…
  • 2011
Highly Influential
8 Excerpts

Global sensitivity analysis based on entropy

  • B. Auder, B. Iooss
  • In S. Martorell, C. Guedes Soares, and J. Barnett…
  • 2008
Highly Influential
9 Excerpts

Review of sensitivity analysis methods

  • F. Pappenberger, M. Ratto, V. Vandenberghe
  • In P.A. Vanrolleghem, editor, Modelling aspects…
  • 2010
Highly Influential
3 Excerpts

La mâıtrise des incertitudes dans un contexte industriel - 1ère partie : une approche méthodologique globale basée sur des exemples

  • E. de Rocquigny
  • Journal de la Société Française de Statistique…
  • 2006
Highly Influential
5 Excerpts

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