Ridge-type pretest and shrinkage estimations in partially linear models

被引：8

作者：

Yuzbasi, Bahadir ^{[1
]}

Ahmed, S. Ejaz ^{[2
]}

Aydin, Dursun ^{[3
]}

机构：

[1] Inonu Univ, Dept Econometr, Malatya, Turkey

[2] Brock Univ, Dept Math & Stat, St Catharines, ON, Canada

[3] Mugla Sitki Kocman Univ, Dept Stat, Mugla, Turkey

来源：

STATISTICAL PAPERS | 2020年 / 61卷 / 02期

基金：

加拿大自然科学与工程研究理事会;

关键词：

Pretest estimation; Shrinkage estimation; Ridge regression; Smoothing spline; Partially linear model; SMOOTHNESS PRIORS; ABSOLUTE PENALTY; REGRESSION; SELECTION;

D O I：

10.1007/s00362-017-0967-8

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, we suggest pretest and shrinkage ridge regression estimators for a partially linear regression model, and compare their performance with some penalty estimators. We investigate the asymptotic properties of proposed estimators. We also consider a Monte Carlo simulation comparison, and a real data example is presented to illustrate the usefulness of the suggested methods.

引用

页码：869 / 898

页数：30

共 31 条

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