共 50 条
Nonparametric density estimation in presence of bias and censoring
被引:13
作者:
Brunel, E.
[1
]
Comte, F.
[2
]
Guilloux, A.
[3
]
机构:
[1] IUT Paris V, MAP5, CNRS, UMR 8145, Paris, France
[2] Univ Paris 05, CNRS, MAP5, UMR 8145, Paris, France
[3] Univ Paris 06, LSTA, Paris, France
来源:
关键词:
Adaptive estimation;
Minimax rate;
Biased data;
Right-censoring;
Nonparametric penalized contrast estimator;
HAZARD RATE ESTIMATION;
SELECTION;
DISTRIBUTIONS;
SAMPLES;
BOUNDS;
D O I:
10.1007/s11749-007-0075-5
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 consider projection estimator methods for the nonparametric estimation of the density of i.i.d. biased observations with a general known bias function w and under right censoring. Adaptive procedures to catch the optimal estimator among a collection by contrast penalization are investigated and proved to give efficient estimators with optimal nonparametric rates of convergence. Monte-Carlo experiments complete the study and illustrate the method.
引用
收藏
页码:166 / 194
页数:29
相关论文
共 50 条