Computational Challenges of t and Related Copulas

Erik Hintz, M. Hofert, C. Lemieux
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引用次数: 1

Abstract

The present paper addresses computational and numerical challenges when working with t copulas and their more complicated extensions, the grouped t and skew t copulas. We demonstrate how the R package nvmix can be used to work with these copulas. In particular, we discuss (quasi-)random sampling and fitting. We highlight the difficulties arising from using more complicated models, such as the lack of availability of a joint density function or the lack of an analytical form of the marginal quantile functions, and give possible solutions along with future research ideas.
t和相关copula的计算挑战
本文解决了计算和数值上的挑战,当处理t轴及其更复杂的扩展,分组t轴和倾斜t轴时。我们将演示如何使用R包nvmix来处理这些copula。特别地,我们讨论了(拟)随机抽样和拟合。我们强调了使用更复杂的模型所产生的困难,例如缺乏联合密度函数的可用性或缺乏边际分位数函数的分析形式,并给出了可能的解决方案以及未来的研究思路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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