Wavelet estimation of conditional density with truncated, censored and dependent data

被引：9
|
作者：
Liang, Han-Ying [1 ,2 ,3 ]
de Una-Alvarez, Jacobo [2 ,3 ]
机构：
[1] Tongji Univ, Dept Math, Shanghai 200092, Peoples R China
[2] Univ Vigo, Dept Stat, Fac Ciencias Econ & Empresariales, Vigo 36310, Spain
[3] Univ Vigo, OR, Fac Ciencias Econ & Empresariales, Vigo 36310, Spain
来源：
JOURNAL OF MULTIVARIATE ANALYSIS | 2011年 / 102卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Mean integrated squared error; Asymptotic normality; Nonlinear wavelet estimator; Conditional density; Truncated and censored data; alpha-mixing; PRODUCT-LIMIT ESTIMATOR; QUANTILE ESTIMATION; BESOV-SPACES; SHRINKAGE; CONVERGENCE; MODEL;
D O I：
10.1016/j.jmva.2010.10.004
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：
In this paper we define a new nonlinear wavelet-based estimator of conditional density function for a random left truncation and right censoring model. We provide an asymptotic expression for the mean integrated squared error (MISE) of the estimator. It is assumed that the lifetime observations form a stationary alpha-mixing sequence. Unlike for kernel estimators, the MISE expression of the wavelet-based estimators is not affected by the presence of discontinuities in the curves. Also, asymptotic normality of the estimator is established. (C) 2010 Elsevier Inc. All rights reserved.
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页码：448 / 467
页数：20
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