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Robust functional sliced inverse regression

文献类型：期刊论文

作者Wang, Guochang1; Zhou, Jianjun2; Wu, Wuqing3; Chen, Min4
刊名STATISTICAL PAPERS
出版日期2017-03-01
卷号58期号:1页码:227-245
关键词Dimension reduction Functional regression Functional sliced inverse regression Robustness
ISSN号0932-5026
DOI10.1007/s00362-015-0695-x
英文摘要Functional data are infinite-dimensional statistical objects which pose significant challenges to both theorists and practitioners. To avoid the stringent constraints for parametric methods and low convergence rate for nonparametric methods, many functional dimension reduction methods have received attention in the functional data analysis literature, which, if desired, can be combined with low dimensional nonparametric regression in a later step. However, as far as we know that all of the functional dimension reduction methods are based on the classical estimates of the first and second moments of the data, and therefore sensitive to outliers. In the present paper, we propose a robust functional dimension reduction method by replacing the classical estimates with robust ones in the functional sliced inverse regression (FSIR). This leads to procedures which maintain the clever estimation scheme of the original FSIR method but can cope better with outliers. A comparison with FSIR is also made through simulation studies to show the robustness of the robust functional sliced inverse regression (RFSIR). As applications, the Orange juice data and the Tecator data are analyzed by using the proposed RFSIR method.
资助项目National Natural Science Foundation of China[11371354] ; Key Laboratory of Random Complex Structures and Data Science, Chinese Academy of Sciences, Beijing 100190, China[2008DP173182] ; National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences, Beijing 100190, China ; China Postdoctoral Science Foundation[2013M541060] ; National Science Foundation of China[11271064] ; National Science Foundation of China[71003100] ; Fundamental Research Funds for the Central Universities[12615304] ; Fundamental Research Funds for the Central Universities ; Research Funds of Renmin University of China[11XNK027] ; National Nature Science Foundation of China[11301464] ; Scientific Research Foundation of Yunnan Provincial Department of Education[2013Y360]
WOS研究方向Mathematics
语种英语
WOS记录号WOS:000394997000012
出版者SPRINGER
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/25065]  
专题应用数学研究所
通讯作者Wang, Guochang
作者单位1.Jinan Univ, Coll Econ, Guangzhou 510632, Guangdong, Peoples R China
2.Yunnan Univ, Sch Math & Stat, Kunming 650091, Peoples R China
3.Renmin Univ China, Sch Business, Beijing 100872, Peoples R China
4.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Guochang,Zhou, Jianjun,Wu, Wuqing,et al. Robust functional sliced inverse regression[J]. STATISTICAL PAPERS,2017,58(1):227-245.
APA Wang, Guochang,Zhou, Jianjun,Wu, Wuqing,&Chen, Min.(2017).Robust functional sliced inverse regression.STATISTICAL PAPERS,58(1),227-245.
MLA Wang, Guochang,et al."Robust functional sliced inverse regression".STATISTICAL PAPERS 58.1(2017):227-245.

入库方式： OAI收割

来源：数学与系统科学研究院

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