On the dependence structure of order statistics
By J. Avérous, Christian Genest, Subhash C. Kochar. 2005
61 citations recorded by the source corpus.
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. 29 (1958) 588) and Kim and David (J. Statist. Plann. Inference 24 (1990) 363). 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.
Subfields: Finance, Management Science and Operations Research, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/c8a9e6d0c7904e64c590ca2a92fd47eb3149949a
Citations in the corpus
- Copulas: A Review and Recent Developments (2006, unknown): “A recent study on the degree of association of pairs of ordered random variables is provided by Avérous et al.[9].”