Varying coefficient partially functional linear regression models

被引:22
|
作者
Peng, Qing-Yan [1 ]
Zhou, Jian-Jun [1 ]
Tang, Nian-Sheng [1 ]
机构
[1] Yunnan Univ, Dept Stat, Kunming 650091, Peoples R China
基金
高等学校博士学科点专项科研基金;
关键词
Functional linear models; Global convergence rate; Polynomial spline; Uniform convergence rate; Varying coefficient model; CONVERGENCE-RATES; TIME-SERIES; PREDICTION;
D O I
10.1007/s00362-015-0681-3
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
By relaxing the linearity assumption in partial functional linear regression models, we propose a varying coefficient partially functional linear regression model (VCPFLM), which includes varying coefficient regression models and functional linear regression models as its special cases. We study the problem of functional parameter estimation in a VCPFLM. The functional parameter is approximated by a polynomial spline, and the spline coefficients are estimated by the ordinary least squares method. Under some regular conditions, we obtain asymptotic properties of functional parameter estimators, including the global convergence rates and uniform convergence rates. Simulation studies are conducted to investigate the performance of the proposed methodologies.
引用
收藏
页码:827 / 841
页数:15
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