STRONG CONVERGENCE RATES OF SEVERAL ESTIMATORS IN SEMIPARAMETRIC VARYING-COEFFICIENT PARTIALLY LINEAR MODELS

被引：0
|
作者：
周勇
尤进红
王晓婧
机构：
[1] Academy of Mathematics and Systems Science, Chinese Academy of Science
[2] Department of Statistics, Shanghai University of Finance and Economics
[3] Department of Biostatistics,University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
来源：
Acta Mathematica Scientia | 2009年 / 29卷 / 05期
基金：
国家杰出青年科学基金; 中国国家自然科学基金;
关键词：
partially linear regression model; varying-coeffcient; profile leastsquares; er- ror variance; strong convergence rate; law of iterated logarithm;
D O I：
暂无
中图分类号：
O212 [数理统计];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
This article is concerned with the estimating problem of semiparametric varying- coeffcient partially linear regression models. By combining the local polynomial and least squares procedures Fan and Huang (2005) proposed a profile least squares estimator for the parametric component and established its asymptotic normality. We further show that the profile least squares estimator can achieve the law of iterated logarithm. Moreover, we study the estimators of the functions characterizing the non-linear part as well as the error variance. The strong convergence rate and the law of iterated logarithm are derived for them, respectively.
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页码：1113 / 1127
页数：15
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