Copulas相依结构下完全和非完全样本极值的联合渐近分布
Asymptotic Distributions of Extremes of Complete and Incomplete Samples under Copulas Dependent
DOI: 10.12677/AAM.2023.1211476, PDF,  被引量    科研立项经费支持
作者: 方 圆：浙江师范大学数学科学学院，金华 浙江；嘉兴学院数据科学学院，嘉兴 浙江
关键词: 随机缺失；Copula；极值；Random Missing； Copula； Extremes
摘要: 在日常生活中，观察某一组数据时，各种偶然因素或不可避免的因素都会导致数据出现随机丢失。通过研究满足阿基米德Copula相依结构极值的联合分布，可以减少或避免极端事件发生时所带来的损失。本文研究了随机缺失情形下，随机序列满足阿基米德Copula相依结构时完全样本与非完全样本极值的联合渐近分布，并给出几种典型的示例来说明主要结论。这不仅在理论中具有重要意义，在实际生活中也具有一定的意义。
Abstract: In daily life, when observing a certain set of data, various accidental or unavoidable factors will lead to random missing. By studying the joint distribution of the extreme values of the Archimedean Copula dependence structures, the losses caused by extreme events can be reduced or avoided. This paper studies the asymptotic distributions of extremes of complete and incomplete samples under random missing. Some examples are given to illustrate the main results. This is not only of great significance in theory, but also has certain significance in real life.
文章引用：方圆. Copulas相依结构下完全和非完全样本极值的联合渐近分布[J]. 应用数学进展, 2023, 12(11): 4824-4833. https://doi.org/10.12677/AAM.2023.1211476

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