对Celebioglu-Cuadras Copula的三个广义版本的理论贡献

C. Chesneau
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引用次数: 9

摘要

copula是一种概率函数,被越来越频繁地用于描述、检验和建模连续随机变量之间的相互依赖关系。在众多提出的copula中,最近对所谓的Celebioglu-Cuadras copula重新产生了兴趣。这主要是因为它的简单性、可利用的依赖性和潜在的适用性。在本文中,我们通过提出它的三个广义版本来促进该联结的发展,每个版本都涉及三个调优参数。主要结果是理论上的:它们包括确定所涉及参数的允许值的宽和可管理的区间。这些证明主要基于极限、微分和分解技术以及数学不等式。一些构型参数在文献中是新的,揭示了一些原始现象。随后,研究了所提联结的基本性质,如对称性、象限依赖性、各种展开式、一致性排序、尾部依赖性、中间相关性和Spearman相关性。详细的例子,数值表和图形被用来支持理论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Theoretical Contributions to Three Generalized Versions of the Celebioglu–Cuadras Copula
Copulas are probabilistic functions that are being used more and more frequently to describe, examine, and model the interdependence of continuous random variables. Among the numerous proposed copulas, renewed interest has recently been shown in the so-called Celebioglu–Cuadras copula. It is mainly because of its simplicity, exploitable dependence properties, and potential for applicability. In this article, we contribute to the development of this copula by proposing three generalized versions of it, each involving three tuning parameters. The main results are theoretical: they consist of determining wide and manageable intervals of admissible values for the involved parameters. The proofs are mainly based on limit, differentiation, and factorization techniques as well as mathematical inequalities. Some of the configuration parameters are new in the literature, and original phenomena are revealed. Subsequently, the basic properties of the proposed copulas are studied, such as symmetry, quadrant dependence, various expansions, concordance ordering, tail dependences, medial correlation, and Spearman correlation. Detailed examples, numerical tables, and graphics are used to support the theory.
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