Ridge-type pretest and shrinkage estimations in partially linear models

被引：7
|
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
收藏
页码：869 / 898
页数：30
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