A group adaptive elastic-net approach for variable selection in high-dimensional linear regression

doi:10.1007/s11425-016-0071-x

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	A group adaptive elastic-net approach for variable selection in high-dimensional linear regression
	Hu, Jianhua 1,2; Huang, Jian 3; Qiu, Feng 1,4
刊名	SCIENCE CHINA-MATHEMATICS
	2018-01
卷号	61 期号:1 页码:173-188
关键词	high-dimensional regression group variable selection group adaptive elastic-net oracle inequalities oracle property
ISSN号	1674-7283
DOI	10.1007/s11425-016-0071-x
英文摘要	In practice, predictors possess grouping structures spontaneously. Incorporation of such useful information can improve statistical modeling and inference. In addition, the high-dimensionality often leads to the collinearity problem. The elastic net is an ideal method which is inclined to reflect a grouping effect. In this paper, we consider the problem of group selection and estimation in the sparse linear regression model in which predictors can be grouped. We investigate a group adaptive elastic-net and derive oracle inequalities and model consistency for the cases where group number is larger than the sample size. Oracle property is addressed for the case of the fixed group number. We revise the locally approximated coordinate descent algorithm to make our computation. Simulation and real data studies indicate that the group adaptive elastic-net is an alternative and competitive method for model selection of high-dimensional problems for the cases of group number being larger than the sample size.
WOS研究方向	Mathematics
语种	英语
出版者	SCIENCE PRESS
WOS记录号	WOS:000419864100010
内容类型	期刊论文
源URL	[http://10.2.47.112/handle/2XS4QKH4/805]
专题	上海财经大学
通讯作者	Hu, Jianhua
作者单位	1.Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai 200433, Peoples R China; 2.Minist Educ, Key Lab Math Econ SUFE, Shanghai 200433, Peoples R China; 3.Univ Iowa, Dept Biostat, Iowa City, IA 52242 USA; 4.Zhejiang Agr & Forestry Univ, Sci Coll, Hangzhou 311300, Zhejiang, Peoples R China
推荐引用方式 GB/T 7714	Hu, Jianhua,Huang, Jian,Qiu, Feng. A group adaptive elastic-net approach for variable selection in high-dimensional linear regression[J]. SCIENCE CHINA-MATHEMATICS,2018,61(1):173-188.
APA	Hu, Jianhua,Huang, Jian,&Qiu, Feng.(2018).A group adaptive elastic-net approach for variable selection in high-dimensional linear regression.SCIENCE CHINA-MATHEMATICS,61(1),173-188.
MLA	Hu, Jianhua,et al."A group adaptive elastic-net approach for variable selection in high-dimensional linear regression".SCIENCE CHINA-MATHEMATICS 61.1(2018):173-188.