Generalized linear-quadratic model with a change point due to a covariate threshold

被引：1

作者：

Zhang, Feipeng ^{[1
]}

Yang, Jiejing ^{[2
]}

Liu, Lei ^{[3
]}

Yu, Yuan ^{[4
]}

机构：

[1] Xi An Jiao Tong Univ, Sch Finance & Econ, Xian 710061, Peoples R China

[2] Bank Changsha, Dept Informat Technol, Changsha 410005, Peoples R China

[3] Washington Univ St Louis, Div Biostat, St Louis, MO 63110 USA

[4] Shandong Univ Finance & Econ, Sch Stat, Jinan 250014, Peoples R China

来源：

JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 2022年 / 216卷

基金：

中国国家自然科学基金;

关键词：

Change point; Generalized Linear-quadratic model; Sup likelihood ratio test; STRUCTURAL-CHANGE; REGRESSION-MODELS; TESTS; PARAMETERS;

D O I：

10.1016/j.jspi.2021.05.012

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this article, we develop a generalized linear-quadratic model with a change point due to a covariate threshold, with one line segment and another quadratic segment intersecting at a change point. A two-step method is proposed to estimate the regression coefficients and the change point. The asymptotic properties of the proposed estimator are derived by modern empirical processes theory. A sup-likelihood ratio test statistic along with its limiting distribution is used to test the existence of the change point. Simulation studies demonstrate that the proposed estimator has good finite-sample performance for different link functions. The applications of the proposed method on Down Syndrome data and Heart failure clinical records data reveal interesting insights. (C) 2021 Elsevier B.V. All rights reserved.

引用

页码：194 / 206

页数：13