关于结合系词的收敛性及相关结果

IF 0.6 Q4 STATISTICS & PROBABILITY Dependence Modeling Pub Date : 2021-01-01 DOI:10.1515/demo-2021-0114
Thimo M. Kasper, S. Fuchs, W. Trutschnig
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引用次数: 1

摘要

最近的一篇文章建立了令人惊讶的结果,即在二元阿基米德copulas类中𝒞ar不同的收敛概念-标准一致收敛,关于度量D1的收敛,以及所谓的弱条件收敛-重合,在当前的贡献中,我们解决了一个自然问题,即所获得的等价是否也适用于更大的结合copulas类𝒞a。基于每个结合式可以表示为(有限或可数无限)阿基米德联结和最小联结M的有序和这一事实,我们证明了标准一致收敛和关于D1的收敛在𝒞a中确实是等价的。该等价是否也适用于弱条件收敛仍然是一个悬而未决的问题。作为证明主要结果所需的一些初步步骤的副产品,我们回答了Durante等人的两个猜想,并表明,在Baire范畴的语言中,当处理D1时,典型的结合式联结是阿基米德的,而典型的阿基米德联结是严格的。
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On convergence of associative copulas and related results
Abstract Triggered by a recent article establishing the surprising result that within the class of bivariate Archimedean copulas 𝒞ar different notions of convergence - standard uniform convergence, convergence with respect to the metric D1, and so-called weak conditional convergence - coincide, in the current contribution we tackle the natural question, whether the obtained equivalence also holds in the larger class of associative copulas 𝒞a. Building upon the fact that each associative copula can be expressed as (finite or countably infinite) ordinal sum of Archimedean copulas and the minimum copula M we show that standard uniform convergence and convergence with respect to D1 are indeed equivalent in 𝒞a. It remains an open question whether the equivalence also extends to weak conditional convergence. As by-products of some preliminary steps needed for the proof of the main result we answer two conjectures going back to Durante et al. and show that, in the language of Baire categories, when working with D1 a typical associative copula is Archimedean and a typical Archimedean copula is strict.
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来源期刊
Dependence Modeling
Dependence Modeling STATISTICS & PROBABILITY-
CiteScore
1.00
自引率
0.00%
发文量
18
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
期刊最新文献
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