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Interactions and computer experiments

机译:相互作用和计算机实验

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摘要

Abstract Identifying interactions and understanding the underlying generating mechanism is essential for interpreting the response of black‐box models. We offer a systematic analysis of interaction types and corresponding sources, merging results of the broad statistical literature with findings developed within the computer experiment literature. Piecewise‐definiteness emerges a self‐standing interaction mechanism, alternative to the presence of interaction terms. We find that the scale of the analysis is essential for interpretation, and that no single method is capable of providing the correct identification of the underlying interaction generating mechanisms; conversely a combined approach involving indicators at difference scales is required. We propose a graphical tool called Mikado plot that exploits the link between interaction indicators at the finite scale and global scales to ease the regional visualization of two‐factor interactions. The findings are illustrated via numerical experiments with three well‐known computer models of different dimensionality and structure.
机译:摘要 识别相互作用并理解其生成机制对于解释黑盒模型的响应至关重要。我们对相互作用类型和相应的来源进行了系统分析,将广泛的统计文献的结果与计算机实验文献中的结果相结合。分段确定性出现了一种自立的交互机制,替代了交互项的存在。我们发现,分析的规模对于解释至关重要,并且没有一种方法能够正确识别潜在的相互作用产生机制;相反,需要采取一种涉及不同尺度指标的综合方法。我们提出了一种称为Mikado图的图形工具,该工具利用有限尺度和全局尺度的交互作用指标之间的联系来简化双因素交互作用的区域可视化。这些发现通过三个不同维度和结构的著名计算机模型的数值实验得到了说明。

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