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An effective approximation for variance-based global sensitivity analysis
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DOI：10.1016/j.ress.2013.07.010.png)
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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. (C) 2013 Elsevier Ltd. All rights reserved.
Keyword:
Variance
Dimensional reduction method
Global sensitivity analysis
Function of random variables
Conditional expectation
ANOVA
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IF:
11
论文数:
9.0K
被引数:
4.2W
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