基于众数回归的变系数模型统一变量选择

兰州理工大学学报 ›› 2020, Vol. 46 ›› Issue (2): 161-165.

基于众数回归的变系数模型统一变量选择

夏亚峰, 贾馨懿

兰州理工大学理学院, 甘肃兰州 730050

收稿日期:2018-07-09 出版日期:2020-04-28 发布日期:2020-06-23
作者简介:夏亚峰(1963-),男,甘肃天水人,教授.
基金资助:
国家自然科学基金(61663024)

A unified variable selection approach forvarying coefficient models based modal regression

XIA Ya-feng, JIA Xin-yi

School of Science, Lanzhou Univ. of Tech. , Lanzhou 730050, China

Received:2018-07-09 Online:2020-04-28 Published:2020-06-23

摘要/Abstract

摘要： 研究了众数回归下变系数模型的统一变量选择问题.利用B样条基函数近似非参数部分,在众数回归下建立SCAD惩罚函数同时选择变系数模型中的重要变量并且识别具有常数效应的协变量,在一定条件下, 证明惩罚估计量相合性和稀疏性,通过数值模拟评估所提出的变量选择方法的有效性.

关键词: 众数回归, 变系数模型, 变量选择, SCAD惩罚

Abstract: A unified variable selection invarying coefficient model with modal regressionis studied. B spline basis function is adopted to approximate the nonparametric part, and SCAD penalty function is established under modal regression. The proposed procedure using SCAD penalty function to select important variables simultaneously for the varying coefficient model can also identify the covariates with constant effects. Under certain conditions, the concoherence and sparseness of penalty estimation are proved. Finally, the effectiveness of the proposed variable selection method is evaluated by numerical simulation.

Key words: Modal regression, varying coefficient model, variable selection, SCAD penalty

中图分类号:

O212.7

夏亚峰, 贾馨懿. 基于众数回归的变系数模型统一变量选择[J]. 兰州理工大学学报, 2020, 46(2): 161-165.

XIA Ya-feng, JIA Xin-yi. A unified variable selection approach forvarying coefficient models based modal regression[J]. Journal of Lanzhou University of Technology, 2020, 46(2): 161-165.

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