论文标题
矢量库拉斯
Vector copulas
论文作者
论文摘要
本文根据测量传输理论引入了与给定的多元边缘的多元分布相关的向量copulas，并建立了SKLAR定理的向量版本。后者为使用矢量copulas来表征有限数量的随机向量（向量依赖性范围内的鲁棒），并用任何给定的非重叠多元边缘群构建多变量分布。我们构建了矢量copulas的椭圆形和肯德尔家族，得出其密度，并呈现算法以生成数据。通过对国际金融传染的程式化分析来说明矢量库co的使用。
This paper introduces vector copulas associated with multivariate distributions with given multivariate marginals, based on the theory of measure transportation, and establishes a vector version of Sklar's theorem. The latter provides a theoretical justification for the use of vector copulas to characterize nonlinear or rank dependence between a finite number of random vectors (robust to within vector dependence), and to construct multivariate distributions with any given non overlapping multivariate marginals. We construct Elliptical and Kendall families of vector copulas, derive their densities, and present algorithms to generate data from them. The use of vector copulas is illustrated with a stylized analysis of international financial contagion.
