Quasi-likelihood Bridge estimators for high-dimensional generalized linear models

被引：3

作者：

Cui, Xiaohua ^{[1
]}

Chen, Xia ^{[1
]}

Yan, Li ^{[1
]}

机构：

[1] Shaanxi Normal Univ, Sch Math & Informat Sci, Xian 710062, Shaanxi, Peoples R China

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2017年 / 46卷 / 10期

基金：

中国国家自然科学基金;

关键词：

Bridge estimators; Generalized linear models; High-dimensional data; Quasi-likelihood; Variable selection; STRONG CONSISTENCY; VARIABLE SELECTION; ORACLE PROPERTIES; DIVERGING NUMBER; ADAPTIVE DESIGNS; REGRESSION; LASSO; PARAMETERS; SHRINKAGE;

D O I：

10.1080/03610918.2016.1271890

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 article, we consider the variable selection and estimation for high-dimensional generalized linear models when the number of parameters diverges with the sample size. We propose a penalized quasi-likelihood function with the bridge penalty. The consistency and the Oracle property of the quasi-likeiihood bridge estimators are obtained. Some simulations and a real data analysis are given to illustrate the performance of the proposed method.

引用

页码：8190 / 8204

页数：15

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