论文标题

对成对的构造中的简化假设是如何简化和灵活的 - 第三维中的分析答案和超越的瞥见

How simplifying and flexible is the simplifying assumption in pair-copula constructions -- analytic answers in dimension three and a glimpse beyond

论文作者

Mroz, Thomas, Fuchs, Sebastian, Trutschnig, Wolfgang

论文摘要

在过去的十年中,许多出版物强调的成对库结构的越来越多的动机以及看似广泛的适用性,在这项贡献中,我们解决了不可避免的问题,即如何灵活地和简化常用的“简化假设”如何从分析的角度来看,并为Nagler和Czado提供的两个相关的问题提供了一个简单的范围,该问题是在2016年列出了一个问题。三维设置。我们证明,简化的Copulas家族是灵活的,因为它在所有三维co \ - 葡萄糖的集合相对于均匀度量的$ d_ \ infty $而言,考虑到更强烈的融合概念,例如由弱的条件融合,或者是由kiull by by byeria the norliation niriation notiver ny the d_1诱导的趋于强烈的融合概念,即无处可去,因此不足以进行任何柔性近似。此外,回到$ d_ \ infty $,我们表明,部分藤蔓copula绝不是给定的,未简化的,未简化的copula $ c $的最佳简化副群,并得出了表明相应近似误差的示例,说明相应的近似误差可以显着较大,并且扩展到超过28 \%的28 \ \%。此外,对于$ d_ \ infty $(但相对于$ d_1 $和弱的条件融合)而言,映射$ψ$分配了每个三维配置库,其独特的部分藤本植物是不连续的,这意味着偏见的葡萄膜映射的敏感性令人惊讶。然后将有关$ d_ \ infty $的上述主要结果扩展到一般的多元设置。

Motivated by the increasing popularity and the seemingly broad applicability of pair-copula constructions underlined by numerous publications in the last decade, in this contribution we tackle the unavoidable question on how flexible and simplifying the commonly used `simplifying assumption' is from an analytic perspective and provide answers to two related open questions posed by Nagler and Czado in 2016. Aiming at a simplest possible setup for deriving the main results we first focus on the three-dimensional setting. We prove that the family of simplified copulas is flexible in the sense that it is dense in the set of all three-dimensional co\-pulas with respect to the uniform metric $d_\infty$ - considering stronger notions of convergence like the one induced by the metric $D_1$, by weak conditional convergence, by total variation, or by Kullback-Leibler divergence, however, the family even turn out to be nowhere dense and hence insufficient for any kind of flexible approximation. Furthermore, returning to $d_\infty$ we show that the partial vine copula is never the optimal simplified copula approximation of a given, non-simplified copula $C$, and derive examples illustrating that the corresponding approximation error can be strikingly large and extend to more than 28\% of the diameter of the metric space. Moreover, the mapping $ψ$ assigning each three-dimensional copula its unique partial vine copula turns out to be discontinuous with respect to $d_\infty$ (but continuous with respect to $D_1$ and to weak conditional convergence), implying a surprising sensitivity of partial vine copula approximations. The afore-mentioned main results concerning $d_\infty$ are then extended to the general multivariate setting.

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