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A class of multivariate copulas based on products of bivariate copulas

机译:一类基于双变量copulas乘积的copulas

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摘要

Copulas are a useful tool to model multivariate distributions. While there exist various families of bivariate copulas, much less work has been done when the dimension is higher. We propose a class of multivariate copulas based on products of transformed bivariate copulas. The analytical forms of the copulas within this class allow to naturally associate a graphical structure which helps to visualize the dependencies and to compute the full joint likelihood even in high dimension. Numerical experiments are conducted both on simulated and real data thanks to a dedicated R package. (C) 2015 Elsevier Inc. All rights reserved.
机译:Copulas是建模多元分布的有用工具。尽管存在各种双变量系动眼科,但当维数较高时,所做的工作要少得多。我们提出了一类基于转换后的双变量copulas的多元copulas。此类中的系动词的分析形式可以自然地关联图形结构,这有助于可视化依存关系,甚至在高维情况下也可以计算出完整的关节可能性。借助专用的R包,可以对模拟数据和实际数据进行数值实验。 (C)2015 Elsevier Inc.保留所有权利。

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