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首页> 外文期刊>Journal of statistical computation and simulation >Improved methods for making inferences about multiple skipped correlations
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Improved methods for making inferences about multiple skipped correlations

机译:推断多个跳过相关性的改进方法

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摘要

A skipped correlation has the advantage of dealing with outliers in a manner that takes into account the overall structure of the data cloud. For p-variate data, p = 2 , there is an extant method for testing the hypothesis of a zero correlation for each pair of variables that is designed to control the probability of one or more Type I errors. And there are methods for the related situation where the focus is on the association between a dependent variable and p explanatory variables. However, there are limitations and several concerns with extant techniques. The paper describes alternative approaches that deal with these issues.
机译:跳过的关联具有以考虑到数据云的总体结构的方式处理离群值的优势。对于p变量数据,p> = 2,存在一种用于测试每对变量零相关性假设的现存方法,该方法旨在控制一个或多个I型错误的概率。并且有一些针对相关情况的方法,其中重点放在因变量和p个解释变量之间的关联上。但是,现有技术存在局限性和一些问题。本文介绍了解决这些问题的替代方法。

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