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A new rank correlation measure

机译:一种新的等级相关度量

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A new rank correlation measure β_n is proposed, so as to develop a nonparametric test of independence for two variables. β_n is shown to be the symmetrized version of a measure earlier proposed by Borroni and Zenga (Stat Methods Appl 16:289-308, 2007). More specifically, β_n is built so that it can take the opposite sign, without changing its absolute value, when the ranking of one variable is reversed. Further, the meaning of the population equivalent of β_n is discussed. It is pointed out that this latter association measure vanishes not only at independence but, more generally, at indifference, that is when the two variables do not show any "tendency" to positive or negative dependence. The null distribution of β_n needs an independent study: hence, the finite null variance and a table of critical values are determined. Moreover, the asymptotic null distribution of β_n is derived. Finally, the performance of the test based on β_n is evaluated by simulation. β_n is shown to be a good competitor of some classical tests for the same problem.
机译:提出了一种新的秩相关测度β_n,以发展两个变量的独立性的非参数检验。 β_n被证明是由Borroni和Zenga较早提出的度量的对称形式(Stat Methods Appl 16:289-308,2007)。更具体地,构建β_n,使得当一个变量的排名相反时,它可以采用相反的符号而不改变其绝对值。此外,讨论了β_n的总体当量的含义。要指出的是,后一种关联度量不仅在独立时消失,而且更普遍地在冷漠时消失,即当两个变量没有显示出对正向或负向依赖性的任何“倾向”时。 β_n的零位分布需要独立研究:因此,确定了有限的零位方差和临界值表。此外,得出β_n的渐近零分布。最后,通过仿真评估了基于β_n的测试的性能。对于相同问题,β_n被证明是一些经典测试的良好竞争者。

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