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

被引：8

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.

引用

页码：448 / 467

页数：20

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