Robust and efficient parametric estimation for censored survival data

被引：11
|
作者：
Basu, Srabashi
Basu, Ayanendranath
Jones, M. C.
机构：
[1] Open Univ, Dept Stat, Milton Keynes MK7 6AA, Bucks, England
[2] Indian Stat Inst, Appl Stat Unit, Kolkata 700108, W Bengal, India
[3] Skytech Solut Pvt Ltd, Kolkata 700091, W Bengal, India
来源：
ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS | 2006年 / 58卷 / 02期
关键词：
density power divergence; Kaplan-Meier; L(2)estimator; M-estimator;
D O I：
10.1007/s10463-005-0004-x
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 fit parametric models to survival data in the case of censoring and (outlier) contamination. To do so, we adapt the robust density power divergence methodology of Basu, Harris, Hjort, and Jones (Biometrika, 85, 549-559, 1998) to the case of censored survival data. Asymptotic properties, simulation performance and application to data are provided.
引用
收藏
页码：341 / 355
页数：15
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