M-estimation and B-spline approximation for varying coefficient models with longitudinal data

被引：33

作者：

Tang Qingguo ^{[1
,2
]}

Cheng Longsheng ^{[1
]}

机构：

[1] Univ Sci & Technol, Sch Econ & Management, Nanjing, Peoples R China

[2] Univ Sci & Technol, PLA, Inst Sci, Nanjing, Peoples R China

来源：

JOURNAL OF NONPARAMETRIC STATISTICS | 2008年 / 20卷 / 07期

基金：

中国国家自然科学基金;

关键词：

varying coefficient models; longitudinal data; M-estimator; B-spline functions; quantile regression; convergence rate;

D O I：

10.1080/10485250802375950

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：

A global smoothing procedure is developed using B-spline function approximations for estimating the unknown functions of a varying coefficient model with repeated measurements. A general formulation is used to treat mean, median, quantile and robust mean regressions in one setting. The global convergence rates of the M-estimators of unknown coefficient functions are established. The asymptotic distributes of M-estimators are derived and the approximate confidence intervals are also established. Various applications of the main results, including estimating conditional quantile coefficient functions and robustifying the mean regression coefficient functions are given. Finite sample properties of our procedures are studied through Monte Carlo simulations.

引用

页码：611 / 625

页数：15

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