Precise asymptotics of error variance estimator in partially linear models

被引：0

作者：

Guo, Shao-jun ^{[1
]}

Chen, Min ^{[1
]}

Liu, Feng ^{[2
]}

机构：

[1] Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China

[2] Chongqing Inst Technol, Dept Stat, Chongqing 630000, Peoples R China

来源：

ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES | 2008年 / 24卷 / 01期

关键词：

precise asymptotics; partially linear models; error variance estimator;

D O I：

10.1007/s10255-005-5241-5

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, we focus our attention on the precise asymptotics of error variance estimator in partially linear regression models, y(i) = x(i)(tau)beta + g(t(i)) + epsilon(i), 1 <= i <= n, {epsilon(i), i, ... , n} are i.i.d random errors with mean 0 and positive finite variance sigma(2). Following the ideas of Allan Gut and Aurel Spataru([7,8]) and Zhang([21]), on precise asymptotics in the Baum-Katz and Davis laws of large numbers and precise rate in laws of the iterated logarithm, respectively, and subject to some regular conditions, we obtain the corresponding results in partially linear regression models.

引用

页码：59 / 74

页数：16

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