Local polynomial fitting in semivarying coefficient model

被引:237
作者
Zhang, WY
Lee, SY
Song, XY
机构
[1] Univ London London Sch Econ & Polit Sci, London WC2A 2AE, England
[2] Chinese Univ Hong Kong, Shatin, Hong Kong, Peoples R China
关键词
semivarying-coefficient models; varying-coefficient; models local polynomial fit; one-step method; two-step method; optimal rate of convergence; mean squared errors;
D O I
10.1006/jmva.2001.2012
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 useful extensions of the classical linear models. Under the condition that the coefficient functions possess about the same degrees of smoothness, the model can easily be estimated via simple local regression.. This leads to the one-step estimation procedure. In this paper, we consider a semivarying coefficient model which is an extension of the varying coefficient model, which is called the semivarying-coefficient model. Procedures for estimation of the linear part and the nonparametric part are developed and their associated statistical properties are studied. The proposed methods are illustrated by some simulation studies and a real example. (C) 2001 Elsevier Science (USA).
引用
收藏
页码:166 / 188
页数:23
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