An effective approximation for variance-based global sensitivity analysis

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• 作者：Xufang Zhang ; Mahesh D. P ; ey
• 关键词：Variance ; Dimensional reduction method ; Global sensitivity analysis ; Function of random variables ; Conditional expectation ; ANOVA
• 刊名：Reliability Engineering and System Safety
• 出版年：2014
• 出版时间：January, 2014
• 年：2014
• 卷：121
• 期：Complete
• 页码：164-174
• 全文大小：519 K

文摘

The paper presents a fairly efficient approximation for the computation of variance-based sensitivity measures associated with a general, n-dimensional function of random variables. The proposed approach is based on a multiplicative version of the dimensional reduction method (M-DRM), in which a given complex function is approximated by a product of low dimensional functions. Together with the Gaussian quadrature, the use of M-DRM significantly reduces the computation effort associated with global sensitivity analysis. An important and practical benefit of the M-DRM is the algebraic simplicity and closed-form nature of sensitivity coefficient formulas. Several examples are presented to show that the M-DRM method is as accurate as results obtained from simulations and other approximations reported in the literature.