Copulas、稳定的尾部依赖函数和多元单调性

IF 0.6 Q4 STATISTICS & PROBABILITY
P. Ressel
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引用次数: 8

摘要

摘要对于多个变量的函数,存在许多单调性的概念,其中三个是各自的特征。分布、生存和共同生存功能。在每种情况下,单调性的“程度”只是整个尺度的基本程度。Copulas是一种特殊的分布函数,稳定的尾部依赖函数是一种特别的共生存函数。事实证明,对于这两个类,除了(平凡的)独立函数之外,基本单调度是唯一可能的。因此,此类函数的“嵌套”取决于特定情况。对于嵌套阿基米德交配,迄今为止已知的相当严格的条件被大大削弱了。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Copulas, stable tail dependence functions, and multivariate monotonicity
Abstract For functions of several variables there exist many notions of monotonicity, three of them being characteristic for resp. distribution, survival and co-survival functions. In each case the “degree” of monotonicity is just the basic one of a whole scale. Copulas are special distribution functions, and stable tail dependence functions are special co-survival functions. It will turn out that for both classes the basic degree of monotonicity is the only one possible, apart from the (trivial) independence functions. As a consequence a “nesting” of such functions depends on particular circumstances. For nested Archimedean copulas the rather restrictive conditions known so far are considerably weakened.
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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
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