吉林大学学报(理学版)

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纵向数据下部分线性模型基于经验似然的变量选择

于卓熙, 李梦丽   

  1. 吉林财经大学 管理科学与信息工程学院, 吉林省互联网金融重点实验室, 长春 130117
  • 收稿日期:2018-02-07 出版日期:2018-07-26 发布日期:2018-07-31
  • 通讯作者: 于卓熙 E-mail:yzx8170561@163.com

Variable Selection Based on Empirical Likelihood forPartially Linear Models with Longitudinal Data

YU Zhuoxi, LI Mengli   

  1. School of Management Science and Information Engineering, Jilin Province Key Laboratory of Fintech,Jilin University of Finance and Economics, Changchun 130117, China
  • Received:2018-02-07 Online:2018-07-26 Published:2018-07-31
  • Contact: YU Zhuoxi E-mail:yzx8170561@163.com

摘要: 针对纵向数据下的部分线性模型, 建立基于经验似然方法的变量选择的信息准则, 证明新变量选择方法的渐近性质, 并模拟研究比较参数信息准则与基于经验似然的信息准则的有限样本性质. 结果表明, 基于经验似然方法的信息准则克服了参数似然函数有时较难得到的困难, 模型选择效果较好.

关键词: 纵向数据, 变量选择, 部分线性模型, 经然似然

Abstract: For  the  partially linear model with longitudinal data, we established the information criteria of variable selection based on empirical likelihood method, and proved the asymptotic properties of the new variable selection method. We simulated and compared the limited sample properties of parameter and information criteria based on empirical likelihood. The results show that the information criteria based on empirical likelihood method overcomes the difficulty that the parameter  likelihood functions are sometimes difficult to obtain, and the model selection effect is better.

Key words: empirical likelihood, longitudinal data, partially linear model, variable selection; 

中图分类号: 

  • O212.7