Robust functional sliced inverse regression

doi:10.1007/s00362-015-0695-x

CSpace > 应用数学研究所

	Robust functional sliced inverse regression
	Wang, Guochang 1; Zhou, Jianjun 2; Wu, Wuqing 3; Chen, Min4
	2017-03-01
发表期刊	STATISTICAL PAPERS
ISSN	0932-5026
卷号	58 期号:1 页码:227-245
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.
关键词	Dimension reduction Functional regression Functional sliced inverse regression Robustness
DOI	10.1007/s00362-015-0695-x
语种	英语
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
WOS类目	Statistics & Probability
WOS记录号	WOS:000394997000012
出版者	SPRINGER
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/25066
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.