Consistency of the semi-parametric MLE in linear regression models with interval-censored data

被引：3
|
作者：
Yu, QQ [1 ]
Wong, GYC
Kong, FH
机构：
[1] SUNY Binghamton, Dept Math Sci, Binghamton, NY 13902 USA
[2] Cornell Univ, Strang Canc Prevent Ctr, Ithaca, NY 14853 USA
[3] Wilkes Univ, Dept Math & Comp Sci, Wilkes Barre, PA 18766 USA
来源：
SCANDINAVIAN JOURNAL OF STATISTICS | 2006年 / 33卷 / 02期
关键词：
consistency; multiple linear regression; non-parametric likelihood; semi-parametric estimation;
D O I：
10.1111/j.1467-9469.2006.00491.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：
Consider the model Y =beta'X + epsilon. Let F-0 be the unknown cumulative distribution funtion of the random variable epsilon. Consistency of the semi-parametric Maximum likelihood estimator of (beta, F-0), denoted by (beta, F), has not been established under any interval censorship (IC) model. We prove in this paper that beta is consistant under the mixed case IC model and some mild assumptions.
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页码：367 / 378
页数：12
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