Improved pretest nonparametric estimation in a multivariate regression model

被引：3

作者：

Ahmed, SE ^{[1
]}

机构：

[1] Univ Regina, Regina, SK S4S 0A2, Canada

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 1998年 / 27卷 / 10期

基金：

加拿大自然科学与工程研究理事会;

关键词：

rank order estimators; asymptotic bias; asymptotic distributional risk; nonparametric multivariate estimation; improved pretest estimators; shrinkage restricted estimators; local alternatives; size of the pretest;

D O I：

10.1080/03610929808832234

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：

Shrinkage pretest nonparametric estimation of the location parameter vector in a multivariate regression model is considered when nonsample information (NSI) about the regression parameters is available. By using the quadratic risk criterion, the dominance of the pretest estimators over the usual estimators has been investigated. We demonstrate analytically and computationally that the proposed improved pretest estimator establishes a wider dominance range for the parameter under consideration than that of the usual pretest estimator in which it is superior over the unrestricted estimator.

引用

页码：2391 / 2421

页数：31

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