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Non-parametric estimation of conditional moments for sensitivity analysis

Marco Ratto (), A. Pagano and P.C. Young

Reliability Engineering and System Safety, 2009, vol. 94, issue 2, 237-243

Abstract: In this paper, we consider the non-parametric estimation of conditional moments, which is useful for applications in global sensitivity analysis (GSA) and in the more general emulation framework. The estimation is based on the state-dependent parameter (SDP) estimation approach and allows for the estimation of conditional moments of order larger than unity. This allows one to identify a wider spectrum of parameter sensitivities with respect to the variance-based main effects, like shifts in the variance, skewness or kurtosis of the model output, so adding valuable information for the analyst, at a small computational cost.

Keywords: Sensitivity analysis; Non-parametric methods; Conditional moments; State-dependent parameter models (search for similar items in EconPapers)
Date: 2009
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DOI: 10.1016/j.ress.2008.02.023

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Handle: RePEc:eee:reensy:v:94:y:2009:i:2:p:237-243