重访系词的最大不对称性

IF 0.8 Q4 STATISTICS & PROBABILITY

Dependence Modeling Pub Date : 2018-03-02 DOI:10.1515/demo-2018-0003

Noppadon Kamnitui, J. Fernández-Sánchez, W. Trutschnig

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引用次数: 5

摘要

摘要利用由Nelsen[11]和klement&mesiar[7]独立建立的d∞(A, At)最大的copuls A的良好表征，我们研究了基于条件的度量D1的最大不对称性，该度量可回溯到Trutschnig[12]。尽管D1(A, At)通常不容易计算，但可以同时提供所有copula A最大化D1(A, At)的表征和简便表示。然后用这个表示证明了满支持最大化D1(A, At)的联结的存在性。D1-和d∞-不对称的比较，包括一些令人惊讶的例子，使本文更加完善。

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Maximum asymmetry of copulas revisited

Abstract Motivated by the nice characterization of copulas A for which d∞(A, At) is maximal as established independently by Nelsen [11] and Klement & Mesiar [7], we study maximum asymmetry with respect to the conditioning-based metric D1 going back to Trutschnig [12]. Despite the fact that D1(A, At) is generally not straightforward to calculate, it is possible to provide both, a characterization and a handy representation of all copulas A maximizing D1(A, At). This representation is then used to prove the existence of copulas with full support maximizing D1(A, At). A comparison of D1- and d∞-asymmetry including some surprising examples rounds off the paper.

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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