极值copula的Kendall τ和Spearman ρ的一个尖锐不等式

IF 0.6 Q4 STATISTICS & PROBABILITY

Dependence Modeling Pub Date : 2018-12-01 DOI:10.1515/demo-2018-0021

W. Trutschnig, T. Mroz

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引用次数: 6

摘要

摘要我们导出了二维极值copula的Kendallτ和Spearmanρ之间的一个新的（下）不等式，证明了这个不等式在每一点上都是尖锐的，并得出结论，共同音和乘积copula是唯一一个著名的下Hutchinson-Lai不等式尖锐的极值copula。

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A sharp inequality for Kendall’s τ and Spearman’s ρ of Extreme-Value Copulas

Abstract We derive a new (lower) inequality between Kendall’s τ and Spearman’s ρ for two-dimensional Extreme-Value Copulas, show that this inequality is sharp in each point and conclude that the comonotonic and the product copula are the only Extreme-Value Copulas for which the well-known lower Hutchinson-Lai inequality is sharp.

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来源期刊

Dependence Modeling STATISTICS & PROBABILITY-

CiteScore

1.00

自引率

0.00%

发文量

审稿时长

12 weeks

期刊介绍： The journal Dependence Modeling aims at providing a medium for exchanging results and ideas in the area of multivariate dependence modeling. It is an open access fully peer-reviewed journal providing the readers with free, instant, and permanent access to all content worldwide. Dependence Modeling is listed by Web of Science (Emerging Sources Citation Index), Scopus, MathSciNet and Zentralblatt Math. The journal presents different types of articles: -"Research Articles" on fundamental theoretical aspects, as well as on significant applications in science, engineering, economics, finance, insurance and other fields. -"Review Articles" which present the existing literature on the specific topic from new perspectives. -"Interview articles" limited to two papers per year, covering interviews with milestone personalities in the field of Dependence Modeling. The journal topics include (but are not limited to):　 -Copula methods -Multivariate distributions -Estimation and goodness-of-fit tests -Measures of association -Quantitative risk management -Risk measures and stochastic orders -Time series -Environmental sciences -Computational methods and software -Extreme-value theory -Limit laws -Mass Transportations