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June, 1993 Iterative Weighted Least Squares Estimators
Jiahua Chen, Jun Shao
Ann. Statist. 21(2): 1071-1092 (June, 1993). DOI: 10.1214/aos/1176349165

Abstract

In a heteroscedastic linear model, we establish the asymptotic normality of the iterative weighted least squares estimators with weights constructed by using the within-group residuals obtained from the previous model fitting. An adaptive procedure is proposed which ensures that the iterative process stops after a finite number of iterations and produces an estimator asymptotically equivalent to the best estimator that can be obtained by using the iterative procedure. Theoretical and empirical results of the performance of the adaptive estimator are presented.

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Jiahua Chen. Jun Shao. "Iterative Weighted Least Squares Estimators." Ann. Statist. 21 (2) 1071 - 1092, June, 1993. https://doi.org/10.1214/aos/1176349165

Information

Published: June, 1993
First available in Project Euclid: 12 April 2007

zbMATH: 0778.62058
MathSciNet: MR1232533
Digital Object Identifier: 10.1214/aos/1176349165

Subjects:
Primary: 62J05
Secondary: 60F05

Rights: Copyright © 1993 Institute of Mathematical Statistics

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Vol.21 • No. 2 • June, 1993
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