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论文类型：期刊论文

发表时间：2018-01-01

发表刊物：JOURNAL OF NONPARAMETRIC STATISTICS

收录刊物：SCIE

卷号：30

期号：4

页面范围：860-883

ISSN号：1048-5252

关键字：Spearman's; Kendall's; dependence; random variable; U statistic; 62H20; 62H10; 62H15

摘要：In this paper, we extend the traditional Spearman's and Kendall's which are widely used to measure the dependence between continuous random variables to the generalised ones that can measure the dependence between discrete or even more general random variables. Furthermore, applying these two generalised correlation coefficients to the trinomial distribution, we study how they vary with the parameter, and point out they are more reasonable than Pearson's correlation coefficient in some ways. Based on Spearman's and Kendall's , two new measures are proposed with their respective asymptotic distributions. Finally, we run a Monte Carlo experiment and give the example analysis to investigate the performance of our dependence measures.