On weak consistency in linear models with equi-correlated random errors

被引：0

作者：

Jia, XW

Rao, MB

Zhang, HM ^{[1
]}

机构：

[1] Concordia Coll, Dept Math & Comp Sci, Moorhead, MN 56562 USA

[2] Univ Cincinnati, Dept Environm Hlth, Ctr Genom Informat, Cincinnati, OH 45267 USA

[3] N Dakota State Univ, Dept Stat, Fargo, ND 58105 USA

[4] Janssen Pharmaceut, Titusville, NJ 08560 USA

来源：

STATISTICS | 2003年 / 37卷 / 06期

关键词：

weak consistency; equi-correlated errors; least squares estimator; linear models;

D O I：

10.1080/02664760310001619332

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：

A new estimator in linear models with equi-correlated random errors is postulated. Consistency properties of the proposed estimator and the ordinary least squares estimator are studied. It is shown that the new estimator has smaller variance than the usual least squares estimator under some mild conditions. In addition, it is observed that the new estimator tends to be weakly consistent in many cases where the usual least squares estimator is not.

引用

页码：463 / 473

页数：11

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