A quantitative model-independent method for global sensitivity analysis of model output

被引:1578
作者
Saltelli, A [1 ]
Tarantola, S [1 ]
Chan, KPS [1 ]
机构
[1] Commiss European Communities, Joint Res Ctr, I-21020 Ispra, VA, Italy
关键词
computational model; Fourier amplitude sensitivity test (FAST); nonlinear and; nonmonotonic models; total sensitivity indices;
D O I
10.2307/1270993
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
A new method for sensitivity analysis (SA) of model output is introduced. It is based on the Fourier amplitude sensitivity test (FAST) and allows the computation of the total contribution of each input factor to the output's variance. The term "total" here means that the factor's main effect, as well as all the interaction terms involving that factor, are included. Although computationally different, the very same measure of sensitivity is offered by the indices of Sobol'. The main advantages of the extended FAST are its robustness, especially at low sample size, and its computational efficiency. The computational aspects of the extended FAST are described. These include (1) the definition of new sets of parametric equations for the search-curve exploring the input space, (2) the selection of frequencies for the parametric equations, and (3) the procedure adopted to estimate the total contributions. We also address the limitations of other global SA methods and suggest that the total-effect indices are ideally suited to perform a global, quantitative, model-independent sensitivity analysis.
引用
收藏
页码:39 / 56
页数:18
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