Work

Extreme Behavior of Competing Risks with Random Sample Size

Year: 2024

Type: article

Abstract: 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.

Source: Axioms

DOI: 10.3390/axioms13080568

Authors: Long Bai, Kaihao Hu, Conghua Wen, Zhongquan Tan, Chengxiu Ling

Institutions: Xi’an Jiaotong-Liverpool University, University of Liverpool, Jiaxing University

Language: English

Topic: Statistical Distribution Estimation and Applications

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,728

Funders: National Natural Science Foundation of China, Xi’an Jiaotong-Liverpool University