中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 数学与系统科学研究院
  3. 中国科学院数学与系统科学研究院
  4. 应用数学研究所
How to Make Model-free Feature Screening Approaches for Full Data Applicable to the Case of Missing Response?

文献类型：期刊论文

作者Wang, Qihua1,2; Li, Yongjin1
刊名SCANDINAVIAN JOURNAL OF STATISTICS
出版日期2018-06-01
卷号45期号:2页码:324-346
关键词borrowing missingness information missing data ultrahigh dimensionality variable screening
ISSN号0303-6898
DOI10.1111/sjos.12290
英文摘要It is quite a challenge to develop model-free feature screening approaches for missing response problems because the existing standard missing data analysis methods cannot be applied directly to high dimensional case. This paper develops some novel methods by borrowing information of missingness indicators such that any feature screening procedures for ultrahigh-dimensional covariates with full data can be applied to missing response case. The first method is the so-called missing indicator imputation screening, which is developed by proving that the set of the active predictors of interest for the response is a subset of the active predictors for the product of the response and missingness indicator under some mild conditions. As an alternative, another method called Venn diagram-based approach is also developed. The sure screening property is proven for both methods. It is shown that the complete case analysis can also keep the sure screening property of any feature screening approach with sure screening property.
资助项目National Natural Science Foundation of China[11171331] ; National Natural Science Foundation of China[11331011] ; National Natural Science Foundation of China[61621003] ; Key Lab of Random Complex Structure and Data Science, CAS ; Natural Science Foundation of SZU
WOS研究方向Mathematics
语种英语
WOS记录号WOS:000432032100005
出版者WILEY
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/30288]  
专题应用数学研究所
通讯作者Wang, Qihua
作者单位1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
2.Shenzhen Univ, Inst Stat Sci, Shenzhen, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Qihua,Li, Yongjin. How to Make Model-free Feature Screening Approaches for Full Data Applicable to the Case of Missing Response?[J]. SCANDINAVIAN JOURNAL OF STATISTICS,2018,45(2):324-346.
APA Wang, Qihua,&Li, Yongjin.(2018).How to Make Model-free Feature Screening Approaches for Full Data Applicable to the Case of Missing Response?.SCANDINAVIAN JOURNAL OF STATISTICS,45(2),324-346.
MLA Wang, Qihua,et al."How to Make Model-free Feature Screening Approaches for Full Data Applicable to the Case of Missing Response?".SCANDINAVIAN JOURNAL OF STATISTICS 45.2(2018):324-346.

入库方式： OAI收割

来源：数学与系统科学研究院

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。