Multivariate nonparametric test of independence

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• 作者：Yanan Fan^a ; ^{y.fan@unsw.edu.au} ; Pierre Lafaye de Micheaux^a ; ^b ; ^{pierre.lafaye-de-micheaux@ensai.fr} ; Spiridon Penev^a ; ^{s.penev@unsw.edu.au} ; Donna Salopek^a ; ^{dm.salopek@unsw.edu.au}
• 关键词：62G20 ; 62P05
• 刊名：Journal of Multivariate Analysis
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：153
• 期：Complete
• 页码：189-210
• 全文大小：617 K
• 卷排序：153

文摘

The problem of testing mutual independence of pp random vectors in a general setting where the dimensions of the vectors can be different and the distributions can be discrete, continuous or both is of great importance. We propose such a test which utilizes multivariate characteristic functions and is a generalization of known results. We characterize the limiting distribution of the test statistic under the null hypothesis. The limiting null distribution is approximated and the method is validated. Numerical results based on simulations are investigated and our methodology is implemented in the R package IndependenceTests. Power comparisons are also presented for some partial cases of our general test, where some competitive procedures exist.