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A New Class of Nonsymmetric Multivariate Dependence Measures

2015/11/09 by Hui Li, Li, Hui
Mathematics · #62B10 #62G99 #62H20 #94A17 #FOS: Computer and information sciences #Methodology (stat.ME) #msc:62B10 #msc:62G99 #msc:62H20 #msc:94A17 #stat.ME

paper · pdf · doi:10.48550/arxiv.1511.02744

20 pages

arxiv created 2015/12/03 · arxiv updated 2015/12/04

Abstract

Following our previous work on copula-based nonsymmetric bivariate dependence measures, we propose a new set of conditions on nonsymmetric multivariate dependence measures which characterize both independence and complete dependence of one random variable on a group of random variables. The measures are nonparametric in that they are copula-based and are invariant under continuous bijective transformations on the group of random variables. We also construct explicitly new measures that satisfy the conditions. Besides, we extend the star product on bivariate copulas to multivariate copulas and prove the DPI condition and self-equitability for the new measures. A further extension to measures of dependence of one group of random variables on another group of random variables is also discussed.

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