Use of minimum risk approach in the estimation of regression models with missing observations

被引：0

作者：

Toutenburg, H

Shalabh

机构：

[1] Univ Munich, Inst Stat, D-80799 Munich, Germany

[2] Panjab Univ, Dept Stat, Chandigarh 160014, India

来源：

METRIKA | 2001年 / 54卷 / 03期

关键词：

regression; imcomplete response; biased imputation; minimum risk criterion; small disturbance asymptotics;

D O I：

暂无

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：

This article considers a linear regression model with some missing observations on the response variable and presents two estimators of regression coefficients employing the approach of minimum risk estimation. Small disturbance asymptotic properties of these estimators along with the traditional unbiased estimator are analyzed and conditions, that are easy to check in practice, for the superiority of one estimator over the other are derived.

引用

页码：247 / 259

页数：13