共轭函数的多元径向对称:i.i.d情况下的有限样本比较

IF 0.6 Q4 STATISTICS & PROBABILITY

Dependence Modeling Pub Date : 2021-01-01 DOI:10.1515/demo-2021-0102

Monica Billio, L. Frattarolo, D. Guégan

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引用次数: 1

摘要

摘要给定一个d维随机向量X = (X1，…，Xd)，如果由X的分量概率积分变换(PIT)得到的标准均匀向量U通过单位超立方体的中心具有相同的点反射分布，则称X具有copula径向对称。我们将[11]中引入的二元检验推广到更高的维度，使用三种不同的可能性来估计零下的copula导数。在一项全面的模拟研究中，我们评估了结果测试的有限样本特性，并将它们与[17]和[1]中引入的多元竞争对手的有限样本性能进行了比较。

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Multivariate radial symmetry of copula functions: finite sample comparison in the i.i.d case

Abstract Given a d-dimensional random vector X = (X1, . . ., Xd), if the standard uniform vector U obtained by the component-wise probability integral transform (PIT) of X has the same distribution of its point reflection through the center of the unit hypercube, then X is said to have copula radial symmetry. We generalize to higher dimensions the bivariate test introduced in [11], using three different possibilities for estimating copula derivatives under the null. In a comprehensive simulation study, we assess the finite-sample properties of the resulting tests, comparing them with the finite-sample performance of the multivariate competitors introduced in [17] and [1].

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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