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Precise asymptotics of error variance estimator in partially linear models

Precise asymptotics of error variance estimator in partially linear models In this paper, we focus our attention on the precise asymptotics of error variance estimator in partially linear regression models, y i = x i τ β + g(t i ) + ε i , 1 ≤ i ≤ n, {ε i , i = 1, ⋯ n} are i.i.d random errors with mean 0 and positive finite variance σ 2. Following the ideas of Allan Gut and Aurel Spătaru[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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Acta Mathematicae Applicatae Sinica Springer Journals

Precise asymptotics of error variance estimator in partially linear models

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References (23)

Publisher
Springer Journals
Copyright
Copyright © 2008 by Springer-Verlag
Subject
Mathematics; Applications of Mathematics; Math Applications in Computer Science; Theoretical, Mathematical and Computational Physics
ISSN
0168-9673
eISSN
1618-3932
DOI
10.1007/s10255-005-5241-5
Publisher site
See Article on Publisher Site

Abstract

In this paper, we focus our attention on the precise asymptotics of error variance estimator in partially linear regression models, y i = x i τ β + g(t i ) + ε i , 1 ≤ i ≤ n, {ε i , i = 1, ⋯ n} are i.i.d random errors with mean 0 and positive finite variance σ 2. Following the ideas of Allan Gut and Aurel Spătaru[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.

Journal

Acta Mathematicae Applicatae SinicaSpringer Journals

Published: Mar 13, 2008

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