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Dynamic Linkages for Multivariate Distributions with Given Nonoverlapping Multivariate Marginals

机译:具有给定的非重叠多元边际的多元分布的动态链接

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摘要

One of the most useful tools for handling multivariate distributions with given univariate marginals is the copula function. Using it, any multivariate distribution function can be represented in a way that emphasizes the separate roles of the marginals and of the dependence structure. Li et al. (1996) introduced an analogous tool, called linkage, which is useful for handling multivariate distributions with given multivariate marginals. The goal of the present paper is to introduce a new kind of linkage, called the dynamic linkage, which can usefully handle multivariate life distributions (that is, distributions of non-negative random variables) by taking advantage of the time dynamics of the underlying lifetimes. Like the linkages of Li et al. (1996), the new dynamic linkage can be used for the study of multivariate distributions with given multivariate marginals by emphasizing the separate roles of the dependence structure among the given multivariate marginals and the dependence structure within each of the nonoverlapping marginals. Preservation of some setwise positive dependence properties, from the dynamic linkage function L to the joint distribution F and vice versa, are studied. When two different distribution functions are associated with the same dynamic linkage (that is, have the same setwise dependence structure) we show that the cumulative hazard order among the corresponding multivariate marginal distributions implies an overall stochastic dominance between the two underlying distribution functions.
机译:copula函数是处理具有给定单变量边际的多元分布的最有用工具之一。使用它,可以以强调边际和依赖结构的独立角色的方式表示任何多元分布函数。 Li等。 (1996年)引入了一种类似的工具,称为链接,该工具可用于处理具有给定多元边际的多元分布。本文的目的是介绍一种称为动态链接的新型链接,该链接可以利用基础生命周期的时间动态来有效地处理多元生命分布(即非负随机变量的分布)。 。像李等人的联系。 (1996年),通过强调给定的多元边际之间的依存结构和每个非重叠边际中的依存结构,新的动态链接可用于研究具有给定的多元边际的多元分布。研究了从动态链接函数L到关节分布F以及反之亦然的一些设定的正相关性的保存。当两个不同的分布函数与同一动态链接相关联(即具有相同的setwise依存结构)时,我们表明,相应的多元边际分布之间的累积危害等级暗示着两个基础分布函数之间的总体随机优势。

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