ITERATIVE WEIGHTED LEAST-SQUARES ESTIMATORS

被引：11
|
作者：
CHEN, JH [1 ]
SHAO, J [1 ]
机构：
[1] UNIV OTTAWA,DEPT MATH,OTTAWA K1N 6N5,ONTARIO,CANADA
来源：
ANNALS OF STATISTICS | 1993年 / 21卷 / 02期
关键词：
ASYMPTOTIC NORMALITY; COMBINING GROUPS; ADAPTIVE ESTIMATOR; EFFICIENCY;
D O I：
10.1214/aos/1176349165
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：
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.
引用
收藏
页码：1071 / 1092
页数：22
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