Symmetrical Design of Experiment in Global Sensitivity Analysis Based on ANOVA High-dimensional Model Representation |
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| Authors: | Chun Luo Yingshan Zhang |
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| Institution: | 1. School of Finance and StatisticsEast China Normal University, Shanghai, P.R. China;2. School of SciencesShanghai Institute of Technology, Shanghai, P.R. China |
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| Abstract: | This article reviews symmetrical global sensitivity analysis based on the analysis of variance of high-dimensional model representation. To overcome the computational difficulties and explore the use of symmetrical design of experiment (SDOE), two methods are presented. If the form of the objective function f is known, we use SDOE to estimate the symmetrical global sensitivity indices instead of Monte Carlo or quasi-Monte Carlo simulation. Otherwise, we use the observed values of the experiment to do symmetrical global sensitivity analysis. These methods are easy to implement and can reduce the computational cost. An example is given by symmetrical design of experiment. |
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| Keywords: | Monte Carlo algorithm Symmetrical decomposition Symmetrical design of experiment Symmetrical global sensitivity analysis Symmetrical global sensitivity indices |
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