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

机译:一种用于重要性分析的新依赖性度量:应用于环境模型

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摘要

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元概率积分变换(MPIT)的重要性分析新的依赖度量,该度量可以评估单个输入或一组输入对模型输出整体不确定性的影响。推导并讨论了新度量的数学性质。提出了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级模型,将新措施的有效性分别与著名的德尔塔指数和扩展德尔塔指数进行了比较。结果表明,在这三个示例中,提出的索引可以产生与增量和扩展增量索引相同的重要性等级。然而,由于MPIT的单变量性质,所提议措施的计算非常容易处理。结果还表明,所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的估计。 (C)2019 Elsevier Inc.保留所有权利。

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