Extreme Behavior of Competing Risks with Random Sample Size

被引：0

作者：

Bai, Long ^{[1
]}

Hu, Kaihao ^{[2
,3
]}

Wen, Conghua ^{[1
]}

Tan, Zhongquan ^{[4
]}

Ling, Chengxiu ^{[2
,5
]}

机构：

[1] Xian Jiaotong Liverpool Univ, Sch Math & Phys, Dept Financial & Actuarial Math, Suzhou 215123, Peoples R China

[2] Xian Jiaotong Liverpool Univ, Acad Pharm, Suzhou 215123, Peoples R China

[3] Univ Liverpool, Dept Math Sci, Liverpool L69 3BX, Lancashire, England

[4] Jiaxing Univ, Coll Data Sci, Jiaxing 314001, Peoples R China

[5] Xian Jiaotong Liverpool Univ, Key Lab Jiangsu Higher Educ Inst under Construct, Suzhou 215123, Peoples R China

来源：

AXIOMS | 2024年 / 13卷 / 08期

基金：

中国国家自然科学基金;

关键词：

extreme value theory; competing risks; random sample size; max stable distribution; GENERALIZED ORDER-STATISTICS; LIMIT DISTRIBUTIONS; POWER NORMALIZATION; CONVERGENCE; MAXIMA; MODELS;

D O I：

10.3390/axioms13080568

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

The advances in science and technology have led to vast amounts of complex and heterogeneous data from multiple sources of random sample length. This paper aims to investigate the extreme behavior of competing risks with random sample sizes. Two accelerated mixed types of stable distributions are obtained as the extreme limit laws of random sampling competing risks under linear and power normalizations, respectively. The theoretical findings are well illustrated by typical examples and numerical studies. The developed methodology and models provide new insights into modeling complex data across numerous fields.

引用

页数：15

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