Nonlinear wavelet density estimation with data missing at random when covariates are present

被引：0
|
作者：
Yu-Ye Zou
Han-Ying Liang
Jing-Jing Zhang
机构：
[1] Tongji University,Department of Mathematics
[2] University of Shanghai for Science and Technology,College of Sciences
来源：
Metrika | 2015年 / 78卷
关键词：
Nonlinear wavelet density estimator; Mean integrated squared error; Missing data; Asymptotic normality; 62G07; 62G20;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, we construct the nonlinear wavelet estimator of a density with data missing at random when covariables are present, and provide an asymptotic expression for the mean integrated squared error (MISE) of the estimator. Unlike for kernel estimators, the MISE expression of the wavelet-based estimator still holds when the density function is piecewise smooth. Also, the asymptotic normality of the estimator is established.
引用
收藏
页码：967 / 995
页数：28
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