Deconvolution kernel estimator for mean transformation with ordinary smooth error

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	Deconvolution kernel estimator for mean transformation with ordinary smooth error
	Qin, HZ ; Feng, SY
	2003-02-15
发表期刊	STATISTICS & PROBABILITY LETTERS
ISSN	0167-7152
卷号	61 期号:4 页码:337-346
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.
关键词	measurement error bandwidth selection super population rates of convergence
语种	英语
WOS研究方向	Mathematics
WOS类目	Statistics & Probability
WOS记录号	WOS:000181313500001
出版者	ELSEVIER SCIENCE BV
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/18578
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.