On the dependence structure of order statistics
By
Jean Avérous, Christian Genest and Subhash C. Kochar
ABSTRACT
Given a random sample from a continuous variable, it is observed that the copula linking any pair of order statistics is independent of the parent distribution. To compare the degree of association between two such pairs of ordered random variables, a notion of relative monotone regression dependence (or stochastic increasingness) is considered. Using this concept, it is proved that for i < j, the dependence of the jth order statistic on the ith order statistic decreases as i and j draw apart. This extends earlier results of Tukey [Ann. Math. Statist., 1958] and Kim and David [J. Statist. Plann. Inference, 1990]. The effect of the sample size on this type of dependence is also investigated, and an explicit expression is given for the population value of Kendall's coefficient of concordance between two arbitrary order statistics of a random sample.

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