Some results for a superiority problem in misspecified restricted linear models

被引：0

作者：

Gupta, AK

Kabe, DG

机构：

[1] BOWLING GREEN STATE UNIV,BOWLING GREEN,OH 43403

[2] ST MARYS UNIV,HALIFAX,NS B3H 3C3,CANADA

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 1997年 / 26卷 / 04期

关键词：

misspecified linear regression model; positive definiteness; linear restrictions; estimated covariance matrix; error prediction covariance matrix; loss of efficiency;

D O I：

10.1080/03610919708813438

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：

Razzaghi (1987) conjectured that a wrong choice of covariance matrix in a restricted linear model results in loss of efficiency. This conjecture was proved correct by Kabe and Gupta (1989) for a wrong choice of constant covariance matrix. The present paper demonstrates that this loss of efficiency persists even with an estimated covariance matrix, thereby resulting in inefficient estimation, prediction, and confidence intervals.

引用

页码：1241 / 1249

页数：9

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