Asymptotic properties of self-consistent estimators with mixed interval-censored data

被引:11
|
作者
Yu, QQ
Wong, GYC
Li, LX
机构
[1] SUNY Binghamton, Dept Math Sci, Binghamton, NY 13902 USA
[2] Cornell Univ, Coll Med, Strang Canc Prevent Ctr, New York, NY 10021 USA
[3] Univ New Orleans, Dept Math, New Orleans, LA 70148 USA
关键词
asymptotic normality; generalized maximum likelihood estimator; mixture distribution; strong consistency;
D O I
10.1023/A:1014656726982
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
Mixed interval-censored (MIC) data consist of n intervals with endpoints L-i and R-i, i = 1,..., n. At least one of them is a singleton set and one is a finite non-singleton interval. The survival time X-i is only known to lie between L-i and R-i, i = 1, 2,..., n. Peto (1973, Applied Statistics, 22, 86-91) and Turnbull (1976, J. Roy. Statist. Soc. Ser. B, 38, 290-295) obtained, respectively, the generalized MLE (GMLE) and the self-consistent estimator (SCE) of the distribution function of X with MIC data. In this paper, we introduce a model for MIC data and establish strong consistency, asymptotic normality and asymptotic efficiency of the SCE and GMLE with MIC data under this model with mild conditions.
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页码:469 / 486
页数:18
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