A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output
A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output
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DOI：
10.1080/00401706.1999.10485594
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发表时间：
1999-02
期刊：
影响因子：
2.5
通讯作者：
Andrea Saltelli;S. Tarantola;K. Chan
中科院分区：
文献类型：
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作者：
Andrea Saltelli;S. Tarantola;K. Chan
提出了一种新的模型输出灵敏度分析方法。它基于傅立叶幅度灵敏度测试（FAST），并允许计算每个输入因子对输出方差的总贡献。这里的术语“总计”意味着包括因子的主效应以及涉及该因子的所有交互作用项。虽然计算上不同，但Sobol指数提供了非常相同的灵敏度度量。扩展FAST的主要优点是其鲁棒性，特别是在低样本量下，以及其计算效率。扩展FAST的计算方面进行了说明。这些包括（1）用于探索输入空间的搜索曲线的新参数方程组的定义，（2）用于参数方程的频率的选择，以及（3）用于估计总贡献的程序。我们还讨论了其他全球SA方法的局限性，并建议总效应指数是相同的。
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 id...