Quasi-minimax estimation in the partial linear model

被引：1

作者：

Wu, Jibo ^{[1
]}

机构：

[1] Chongqing Univ Arts & Sci, Sch Math & Finances, Chongqing 402160, Peoples R China

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2017年 / 46卷 / 06期

基金：

中国国家自然科学基金;

关键词：

Ellipsoidal restrictions; Mean squared error matrix; Minimax estimator; Partial linear model; Two-step estimator; LIU-TYPE ESTIMATOR; SEMIPARAMETRIC REGRESSION; EFFICIENCY;

D O I：

10.1080/03610926.2015.1053941

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 discusses the minimax estimator in partial linear model y = Z + f + epsilon under ellipsoidal restrictions on the parameter space and quadratic loss function. The superiority of the minimax estimator over the two-step estimator is studied in the mean squared error matrix criterion.

引用

页码：2982 / 2989

页数：8

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