Deconvolution kernel estimator for mean transformation with ordinary smooth error

	Deconvolution kernel estimator for mean transformation with ordinary smooth error
	Qin, HZ ; Feng, SY
刊名	STATISTICS & PROBABILITY LETTERS
	2003-02-15
卷号	61 期号:4 页码:337-346
关键词	measurement error bandwidth selection super population rates of convergence
ISSN号	0167-7152
英文摘要	Consider the convolution model Y = X + epsilon in which e is the ordinary smooth measurement error with a known distribution. The estimator of mean transformation theta = E[G(X)] is constructed by deconvolution kernel technique. Moment and weak convergence rates of the proposed estimator are derived under some mild regularity conditions. Simulation results indicate that the underlying estimator is highly accurate and robust. (C) 2002 Elsevier Science B.V. All rights reserved.
WOS研究方向	Mathematics
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000181313500001
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/18577]
专题	中国科学院数学与系统科学研究院
作者单位	1.Beijing Normal Univ, Dept Math, Beijing 100875, Peoples R China 2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Qin, HZ,Feng, SY. Deconvolution kernel estimator for mean transformation with ordinary smooth error[J]. STATISTICS & PROBABILITY LETTERS,2003,61(4):337-346.
APA	Qin, HZ,&Feng, SY.(2003).Deconvolution kernel estimator for mean transformation with ordinary smooth error.STATISTICS & PROBABILITY LETTERS,61(4),337-346.
MLA	Qin, HZ,et al."Deconvolution kernel estimator for mean transformation with ordinary smooth error".STATISTICS & PROBABILITY LETTERS 61.4(2003):337-346.