Local estimation for varying-coefficient models with longitudinal data

被引：2

作者：

Lin, Hongmei ^{[1
]}

Zhang, Riquan ^{[2
]}

Shi, Jianhong ^{[3
]}

机构：

[1] Shanghai Univ Int Business & Econ, Sch Stat & Informat, Shanghai, Peoples R China

[2] East China Normal Univ, Sch Stat, Shanghai 200241, Peoples R China

[3] Shanxi Normal Univ, Sch Math & Comp Sci, Linfen, Peoples R China

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2017年 / 46卷 / 15期

基金：

中国国家自然科学基金; 国家教育部博士点专项基金资助;

关键词：

Cholesky decomposition; local linear regression; longitudinal data; profile least squares; varying-coefficient models; GENERALIZED LINEAR-MODELS; COVARIANCE-STRUCTURES; SERIAL-CORRELATION; LIKELIHOOD;

D O I：

10.1080/03610926.2016.1154156

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：

Varying-coefficient models are very useful for longitudinal data analysis. In this paper, we focus on varying-coefficient models for longitudinal data. We develop a new estimation procedure using Cholesky decomposition and profile least squares techniques. Asymptotic normality for the proposed estimators of varying-coefficient functions has been established. Monte Carlo simulation studies show excellent finite-sample performance. We illustrate our methods with a real data example.

引用

页码：7511 / 7528

页数：18

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