基于ANOVA高维模型的正交设计的优良性

Optimal Properties of Orthogonal Arrays Based on ANOVA High-Dimensional Model Representation

  • 摘要: 全局敏感性指标在全局敏感性分析中占有重要的地位, Wang等(2012)证明了正交设计在估计参数时具有A最优, 本文论证了正交设计在估计参数时的一些其他最优性质, 包括估计参数的E最优和估计参数的一致最优性. 在模拟论证中, 我们提出了用随机化正交表来替代一般的正交表, 并得到了较好的性质, 如减少了偏差并且提高了精度.

     

    Abstract: Global sensitivity indices play important roles in global sensitivity analysis based on ANOVA high-dimensional representation, Wang et al. (2012) showed that orthogonal arrays are A-optimality designs for the estimation of parameter , the definition of which can be seen in Section 2. This paper presented several other optimal properties of orthogonal arrays under ANOVA high-dimensional representation, including E-optimality for the estimation of and universal optimality for the estimation of , where is the independent parameters of . Simulation study showed that randomized orthogonal arrays have less biased and more precise in estimating the confidence intervals comparing with other methods.

     

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