Orthogonal Arrays for the Estimation of Global Sensitivity Indices Based on ANOVA High-Dimensional Model Representation

被引：7

作者：

Wang, Xiaodi ^{[1
]}

Tang, Yincai ^{[1
]}

Zhang, Yingshan ^{[1
]}

机构：

[1] E China Normal Univ, Sch Finance & Stat, Shanghai 200241, Peoples R China

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2011年 / 40卷 / 09期

关键词：

Global sensitivity indices; Monte Carlo simulation; Orthogonal array; Quasi-Monte Carlo; CONSTRUCTION; DESIGNS;

D O I：

10.1080/03610918.2011.575500

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：

We present an efficient new approach to estimate global sensitivity indices based on ANOVA high-dimensional model representation. The method makes use of the properties of orthogonal arrays and extend the results of Wang et al. (2010) to a more general situation. A theorem is given to illustrate that both the non influential and significant sensitivity indices are well estimated. This new method offers higher sampling efficiency than those of Sobol and Saltelli. We test its performance on two different models, which are widely used in engineering and statistical areas.

引用

页码：1324 / 1341

页数：18

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