Wavelet density deconvolution estimations with heteroscedastic measurement errors

被引：3
|
作者：
Zeng, Xiaochen [1 ]
Wang, Jinru [1 ]
机构：
[1] Beijing Univ Technol, Dept Appl Math, Beijing 100124, Peoples R China
来源：
STATISTICS & PROBABILITY LETTERS | 2018年 / 134卷
基金：
中国国家自然科学基金;
关键词：
Density estimation; Wavelets; Consistency; Heteroscedastic errors;
D O I：
10.1016/j.spl.2017.10.016
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
This paper discusses the mean consistency of both theoretical and practical wavelet estimators under deconvolution model with heteroscedastic measurement errors. When the model degenerates to the classical deconvolution problem, our results coincide with Geng & Wang's theorem (2015). (C) 2017 Elsevier B.V. All rights reserved.
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页码：79 / 85
页数：7
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