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A WEIGHTED RANK MEASURE OF CORRELATION

机译:加权的相关度度量

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Spearman's rank correlation coefficient is not entirely suitable for measuring the correlation between two rankings in some applications because it treats all ranks equally. In 2000, Blest proposed an alternative measure of correlation that gives more importance to higher ranks but has some drawbacks. This paper proposes a weighted rank measure of correlation that weights the distance between two ranks using a linear function of those ranks, giving more importance to higher ranks than lower ones. It analyses its distribution and provides a table of critical values to test whether a given value of the coefficient is significantly different from zero. The paper also summarizes a number of applications for which the new measure is more suitable than Spearman's.
机译:在某些应用中,Spearman的等级相关系数并不完全适合于测量两个等级之间的相关性,因为它平等地对待所有等级。在2000年,Blest提出了另一种相关性度量方法,该方法对较高的排名更为重视,但也有一些缺点。本文提出了一种相关性的加权等级度量,该度量使用那些等级的线性函数对两个等级之间的距离进行加权,从而给予较高等级的重要性高于较低等级的重要性。它分析其分布并提供临界值表,以测试系数的给定值是否显着不同于零。本文还总结了许多应用,这些新方法比Spearman的方法更适合。

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