Variable Selection for Varying Coefficient Models Via Kernel Based Regularized Rank Regression

被引：0
|
作者：
Kang-ning Wang
Lu Lin
机构：
[1] Shandong Technology and Business University,School of Statistics
[2] Shandong University,Institute for Financial Studies
来源：
Acta Mathematicae Applicatae Sinica, English Series | 2020年 / 36卷
关键词：
rank regression; oracle property; variable selection; asymptotic relative efficiency; BIC-type criterion; 62G05; 62E20;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
A robust and efficient shrinkage-type variable selection procedure for varying Coefficient models is proposed, selection consistency and oracle properties are established. Furthermore, a BIC-type criterion is suggested for shrinkage parameter selection and theoretical property is discussed. Numerical studies and real data analysis also are included to illustrate the finite sample performance of our method.
引用
收藏
页码：458 / 470
页数：12
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