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A flexible and tractable class of one-factor copulas

机译:灵活易处理的一因素系

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摘要

Copulas are a useful tool to model multivariate distributions. While there exist various families of bivariate copulas, the construction of flexible and yet tractable copulas suitable for high-dimensional applications is much more challenging. This is even more true if one is concerned with the analysis of extreme values. In this paper, we construct a class of one-factor copulas and a family of extreme-value copulas well suited for high-dimensional applications and exhibiting a good balance between tractability and flexibility. The inference for these copulas is performed by using a least-squares estimator based on dependence coefficients. The modeling capabilities of the copulas are illustrated on simulated and real datasets.
机译:Copulas是建模多元分布的有用工具。尽管存在各种双变量联接器,但适合于高尺寸应用的柔性但易处理的联接器的构造更具挑战性。如果人们关注极值分析,则更是如此。在本文中,我们构建了一类单因子copula和一类极值copula,它们非常适合于高尺寸应用,并且在可处理性和灵活性之间表现出良好的平衡。通过使用基于相关系数的最小二乘估计器,可以对这些系动词进行推断。 copulas的建模能力在模拟和真实数据集上都有说明。

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