A new difference-based weighted mixed Liu estimator in partially linear models

被引：11

作者：

Akdeniz, Esra ^{[1
]}

Akdeniz, Fikri ^{[2
]}

Roozbeh, Mahdi ^{[3
]}

机构：

[1] Marmara Univ, Fac Med, Div Biostat, Istanbul, Turkey

[2] Cag Univ, Dept Math & Comp Sci, Tarsus Mersin, Turkey

[3] Semnan Univ, Fac Math Stat & Comp Sci, POB 35195-363, Semnan, Iran

来源：

STATISTICS | 2018年 / 52卷 / 06期

关键词：

Difference-based estimator; generalized Liu estimator; generalized difference-based weighted mixed Liu estimator; partially linear model; weighted mixed estimator; RIDGE ESTIMATORS; REGRESSION; IMPROVEMENT; PARAMETERS; VARIANCE;

D O I：

10.1080/02331888.2018.1511715

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：

In this paper, a generalized difference-based estimator is introduced for the vector parameter beta in the partially linear model when the errors are correlated. A generalized difference-based Liu estimator is defined for the vector parameter beta. Under the linear stochastic constraint r = R beta + e, a new generalized difference-based weighted mixed Liu estimator is introduced. The performance of this estimator over the generalized difference-based weighted mixed estimator and the generalized difference-based Liu estimator in terms of the mean squared error matrix criterion is investigated. Then, a method to select the biasing parameter d and non-stochastic weight. is considered. The efficiency properties of the newestimator are illustrated by a simulation study. Finally, the performance of the new estimator is evaluated for a real data set.

引用

页码：1309 / 1327

页数：19

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