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A distribution-free test for the relationship between model input and output when using Latin hypercube sampling

机译：使用拉丁超立方体采样时模型输入与输出之间关系的无分布测试

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摘要

A test for the detection of non-monotone relationships between the inputs and outputs of computer simulation models is described for use in sensitivity analyses employing Latin hypercube sampling. The test is based on the squared differences of the consecutive ranks of the output variable when the values of the output variable have been ordered by the corresponding values of an input variable. The test is distribution-free and does not require the values of the output variable to be independent of one another. Instead, the weaker assumption of exchangeability is used. The resulting test statistic is shown to be independent of Spearman's rank correlation coefficient, and a simple method for combining the two statistics is discussed. The test is illustrated with an example from a recent performance assessment for the Waste Isolation Pilot Plant.
机译：描述了一种用于检测计算机仿真模型的输入和输出之间的非单调关系的测试，该测试可用于采用拉丁超立方体采样的灵敏度分析。当输出变量的值已由输入变量的相应值排序时，该测试基于输出变量的连续等级的平方差。该测试是无分布的，不需要输出变量的值彼此独立。相反，使用了较弱的可交换性假设。结果表明，测试统计量与Spearman秩相关系数无关，并讨论了将两种统计量合并的简单方法。通过最近对废物隔离试验工厂的性能评估中的一个示例说明了该测试。

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