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A new dependence measure for importance analysis: Application to an environmental model

机译:重要性分析的新依赖措施:对环境模型的应用

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This paper presents a new dependence measure for importance analysis based on multivariate probability integral transformation (MPIT), which can assess the effect of an individual input, or a group of inputs on the whole uncertainty of model output. The mathematical properties of the new measure are derived and discussed. The nonparametric method for estimating the new measure is presented. The effectiveness of the new measure is compared with the well-known delta and extended delta indices, respectively, through a linear example, a risk assessment model and the Level E model. Results show that the proposed index can produce the same importance rankings as the delta and extended delta indices in these three examples. Yet the computation of the proposed measure is quite tractable due to the univariate nature of MPIT. The results also show that the established estimation method can provide robust estimate for the new measure in a quite efficient manner. (C) 2019 Elsevier Inc. All rights reserved.
机译:本文提出了一种基于多变量概率积分变换(MPIT)的重要性分析的新依赖性措施,其可以评估单个输入的效果,或者在模型输出的整个不确定性上的输入。派生和讨论了新度量的数学特性。提出了用于估计新度量的非参数方法。通过线性示例,风险评估模型和E型模型将新措施的有效性与众所周知的三角洲和扩展Δ指数进行比较。结果表明,该索引可以在这三个例子中产生与Δ和扩展的Delta指数相同的重视排名。然而,由于MPIT的单变量性,所提出的措施的计算是非常易无的。结果还表明,已建立的估计方法可以以相当有效的方式为新措施提供鲁棒估计。 (c)2019 Elsevier Inc.保留所有权利。

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