Penalized Spline Varying-Coefficient Single-Index Model

被引:7
|
作者
Li, Jianbo [2 ]
Zhang, Riquan [1 ,3 ]
机构
[1] E China Normal Univ, Sch Finance & Stat, Shanghai 200241, Peoples R China
[2] Chinese Univ Hong Kong, Dept Stat, Hong Kong, Hong Kong, Peoples R China
[3] Shanxi Datong Univ, Dept Math, Datong, Peoples R China
基金
中国国家自然科学基金;
关键词
Asymptotic normality; Consistency; P-spline; Varying-coefficient single-index model; REGRESSION;
D O I
10.1080/03610910903411177
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, the varying-coefficient single-index model (VCSIM) is discussed based on penalized spline estimation method. All the coefficient functions are fitted by P-spline and all parameters in P-spline varying-coefficient model can be estimated simultaneously by penalized nonlinear least squares. The detailed algorithm is given, including choosing smoothing parameters and knots. The approach is rapid and computationally stable. root n consistency and asymptotic normality of the estimators of all the parameters are showed. Both simulated and real data examples are given to illustrate the proposed estimation methodology.
引用
收藏
页码:221 / 239
页数:19
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