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Joint feature screening for ultra-high-dimensional sparse additive hazards model by the sparsity-restricted pseudo-score estimator
Chen, Xiaolin1; Liu, Yi2; Wang, Qihua3,4
2019-10-01
Source PublicationANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS
ISSN0020-3157
Volume71Issue:5Pages:1007-1031
AbstractDue to the coexistence of ultra-high dimensionality and right censoring, it is very challenging to develop feature screening procedure for ultra-high-dimensional survival data. In this paper, we propose a joint screening approach for the sparse additive hazards model with ultra-high-dimensional features. Our proposed screening is based on a sparsity-restricted pseudo-score estimator which could be obtained effectively through the iterative hard-thresholding algorithm. We establish the sure screening property of the proposed procedure theoretically under rather mild assumptions. Extensive simulation studies verify its improvements over the main existing screening approaches for ultra-high-dimensional survival data. Finally, the proposed screening method is illustrated by dataset from a breast cancer study.
KeywordAdditive hazards model Joint feature screening Iterative hard-thresholding algorithm Sure screening property
DOI10.1007/s10463-018-0675-8
Language英语
Funding ProjectNational Natural Science Foundation of China[11501573] ; National Natural Science Foundation of China[11326184] ; National Natural Science Foundation of China[11771250] ; National Natural Science Foundation of China[11171331] ; National Natural Science Foundation of China[11331011] ; National Natural Science Foundation of China[61621003] ; National Social Science Foundation of China[17BTJ019] ; Fundamental Research Funds for the Central Universities[17CX02035A] ; Key Lab of Random Complex Structure and Data Science, CAS ; Zhejiang Gongshang University
WOS Research AreaMathematics
WOS SubjectStatistics & Probability
WOS IDWOS:000481796100001
PublisherSPRINGER HEIDELBERG
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/35372
Collection应用数学研究所
Corresponding AuthorWang, Qihua
Affiliation1.Qufu Normal Univ, Sch Stat, Qufu 273165, Peoples R China
2.China Univ Petr East China, Coll Sci, Qingdao 266580, Shandong, Peoples R China
3.Zhejiang Gongshang Univ, Dept Math & Stat, Hangzhou 310018, Zhejiang, Peoples R China
4.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Chen, Xiaolin,Liu, Yi,Wang, Qihua. Joint feature screening for ultra-high-dimensional sparse additive hazards model by the sparsity-restricted pseudo-score estimator[J]. ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS,2019,71(5):1007-1031.
APA Chen, Xiaolin,Liu, Yi,&Wang, Qihua.(2019).Joint feature screening for ultra-high-dimensional sparse additive hazards model by the sparsity-restricted pseudo-score estimator.ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS,71(5),1007-1031.
MLA Chen, Xiaolin,et al."Joint feature screening for ultra-high-dimensional sparse additive hazards model by the sparsity-restricted pseudo-score estimator".ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS 71.5(2019):1007-1031.
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