关于自相似Ito过程的联结

IF 0.6 Q4 STATISTICS & PROBABILITY

Dependence Modeling Pub Date : 2021-01-01 DOI:10.1515/demo-2021-0112

P. Jaworski, Marcin Krzywda

引用次数: 1

摘要

摘要将具有随机相关Wiener边距的二维自相似Ito过程的累积分布函数和copula描述为一类椭圆型偏微分方程的解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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On copulas of self-similar Ito processes

Abstract We characterize the cumulative distribution functions and copulas of two-dimensional self-similar Ito processes, with randomly correlated Wiener margins, as solutions of certain elliptic partial differential equations.

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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