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

被引:10
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
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
收藏
页码:448 / 467
页数:20
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