Derivative-Based Global Sensitivity Measures

Sergey Kucherenko () and Bertrand Iooss ()
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Sergey Kucherenko: Imperial College London, Department of Chemical Engineering
Bertrand Iooss: EDF R&D, Industrial Risk Management Department

Chapter 36 in Handbook of Uncertainty Quantification, 2017, pp 1241-1263 from Springer

Abstract: Abstract The method of derivative-based global sensitivity measures (DGSM) has recently become popular among practitioners. It has a strong link with the Morris screening method and Sobol’ sensitivity indices and has several advantages over them. DGSM are very easy to implement and evaluate numerically. The computational time required for numerical evaluation of DGSM is generally much lower than that for estimation of Sobol’ sensitivity indices. This paper presents a survey of recent advances in DGSM concerning lower and upper bounds on the values of Sobol’ total sensitivity indices S i tot . Using these bounds it is possible in most cases to get a good practical estimation of the values of S i tot . Several examples are used to illustrate an application of DGSM.

Keywords: Sensitivity analysis; Sobol’ indices; Morris method; Model derivatives; DGSM; Poincaré inequality (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/978-3-319-12385-1_36

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