Influence function-based confidence intervals for the Kendall rank correlation coefficient

【Author】 Huang, Zhonglu; Qin, Gengsheng

【Source】COMPUTATIONAL STATISTICS

【影响因子】1.405

【Abstract】Correlation coefficients measure the association between two random variables. In circumstances in which the typically-used Pearson correlation coefficient does not suffice, the Kendall rank correlation coefficient is routinely used as an alternative measure. In this paper, using the influence function of the Kendall rank correlation coefficient, we develop a normal approximation-based confidence interval and an empirical likelihood-based confidence interval for the Kendall rank correlation coefficient. Simulation studies are conducted to show their good finite sample properties and robustness. We apply the proposed methods to a real dataset on Bitcoin financial data.

【Keywords】Empirical likelihood; Influence function; Kendall correlation coefficient

【发表时间】

【收录时间】2022-08-15

【文献类型】实证数据

【主题类别】

区块链治理-市场治理-数字货币