Empirical Likelihood for Generalized Linear Models with Longitudinal Data

被引：0

作者：

YIN Changming ^{[1
]}

AI Mingyao ^{[2
]}

CHEN Xia ^{[3
]}

KONG Xiangshun ^{[4
]}

机构：

[1] School of Mathematics and Information Science, Guangxi University

[2] LMAM, School of Mathematical Sciences and Center for Statistical Science, Peking University

[3] School of Mathematics and Statistics, Shaanxi Normal University

[4] School of Mathematics and Statistics, Beijing Institute of Technology

来源：

Journal of Systems Science & Complexity | 2023年 / 36卷 / 05期

基金：

中国国家社会科学基金;

关键词：

D O I：

暂无

中图分类号：

O212.1 [一般数理统计];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Generalized linear models are usually adopted to model the discrete or nonnegative responses. In this paper, empirical likelihood inference for fixed design generalized linear models with longitudinal data is investigated. Under some mild conditions, the consistency and asymptotic normality of the maximum empirical likelihood estimator are established, and the asymptotic χ2distribution of the empirical log-likelihood ratio is also obtained. Compared with the existing results, the new conditions are more weak and easy to verify. Some simulations are presented to illustrate these asymptotic properties.

引用

页码：2100 / 2124

页数：25

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