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New weighted rank correlation coefficients sensitive to agreement on top and bottom rankings

机译:新的加权排名相关系数对上下排名的一致性很敏感

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摘要

Three new weighted rank correlation coefficients are proposed which are sensitive to both agreement on top and bottom rankings. The first one is based on the weighted rank correlation coefficient proposed by Maturi and Abdelfattah [13], the second and the third are based on the order statistics and the quantiles of the Laplace distribution, respectively. The limiting distributions of the new correlation coefficients under the null hypothesis of no association between the rankings are presented, and a summary of the exact and approximate quantiles for these coefficients is provided. Asimulation study is performed to compare the performance of Kendall's tau, Spearman's rho, and the new weighted rank correlation coefficients in detecting the agreement on the top and the bottom rankings simultaneously. Finally, examples are given for illustration purposes, including a real data set from financial market indices.
机译:提出了三个新的加权秩相关系数,它们对最高和最低排名的一致性都很敏感。第一个基于Maturi和Abdelfattah [13]提出的加权秩相关系数,第二个和第三个分别基于拉普拉斯分布的阶次统计量和分位数。提出了在等级之间没有关联的零假设下新的相关系数的极限分布,并提供了这些系数的精确分位数和近似分位数的摘要。进行模拟研究以比较Kendall的tau,Spearman的rho和新的加权秩相关系数在同时检测顶部和底部排名的一致性时的性能。最后,给出了示例以说明目的,包括来自金融市场指数的真实数据集。

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