Theoretical Advancements on a Few New Dependence Models Based on Copulas with an Original Ratio Form

C. Chesneau
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引用次数: 2

Abstract

Copulas are well-known tools for describing the relationship between two or more quantitative variables. They have recently received a lot of attention, owing to the variable dependence complexity that appears in heterogeneous modern problems. In this paper, we offer five new copulas based on a common original ratio form. All of them are defined with a single tuning parameter, and all reduce to the independence copula when this parameter is equal to zero. Wide admissible domains for this parameter are established, and the mathematical developments primarily rely on non-trivial limits, two-dimensional differentiations, suitable factorizations, and mathematical inequalities. The corresponding functions and characteristics of the proposed copulas are looked at in some important details. In particular, as common features, it is shown that they are diagonally symmetric, but not Archimedean, not radially symmetric, and without tail dependence. The theory is illustrated with numerical tables and graphics. A final part discusses the multi-dimensional variation of our original ratio form. The contributions are primarily theoretical, but they provide the framework for cutting-edge dependence models that have potential applications across a wide range of fields. Some established two-dimensional inequalities may be of interest beyond the purposes of this paper.
基于原始比率形式的copula的几种新的依赖模型的理论进展
copula是描述两个或多个定量变量之间关系的著名工具。由于现代异构问题中出现的变量依赖复杂性,它们最近受到了广泛的关注。本文基于一种常见的原始比形式,给出了五种新的连词。它们都是用一个单一的调谐参数定义的,当这个参数等于零时,它们都简化为独立的联结。建立了该参数的广泛允许域,数学发展主要依赖于非平凡极限、二维微分、适当的分解和数学不等式。对所提出的联结的相应功能和特征进行了一些重要的细节研究。特别是,作为共同的特征,证明了它们是对角对称的,但不是阿基米德对称的,不是径向对称的,没有尾巴依赖。该理论用数值表和图形加以说明。最后一部分讨论了原始比率形式的多维变化。这些贡献主要是理论性的,但它们为在广泛领域具有潜在应用的尖端依赖模型提供了框架。一些已建立的二维不等式可能超出了本文的目的。
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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