Bootstrap for the conditional distribution function with truncated and censored data

被引：0
|
作者：
Pérez, MCI
Manteiga, WG
机构：
[1] Univ Vigo, Escuela Univ Ingn Tecn Forestal, Dept Estadist & Invest Operat, Pontevedra 36005, Spain
[2] Univ Santiago de Compostela, Fac Matemat, Dept Estadist & Invest Operat, Santiago De Compostela 15706, Spain
来源：
ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS | 2003年 / 55卷 / 02期
关键词：
censored data; truncated data; kernel estimator; generalized product-limit estimator; bootstrapped estimator; asymptotic representation; consistency;
D O I：
暂无
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：
We propose a resampling method for left truncated and right censored data with covariables to obtain a bootstrap version of the conditional distribution function estimator. We derive an almost sure representation for this bootstrapped estimator and, as a consequence, the consistency of the bootstrap is obtained. This bootstrap approximation represents an alternative to the normal asymptotic distribution and avoids the estimation of the complicated mean and variance parameters of the latter.
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页码：331 / 357
页数：27
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