Maximum likelihood estimators in finite mixture models with censored data

被引：8

作者：

Miyata, Yoichi ^{[1
]}

机构：

[1] Takasaki City Univ Econ, Fac Econ, Gunma 3700801, Japan

来源：

JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 2011年 / 141卷 / 01期

关键词：

Censored data; Finite mixture; Maximum likelihood estimators; Strong consistency; CONSISTENCY; IDENTIFIABILITY;

D O I：

10.1016/j.jspi.2010.05.006

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：

The consistency of estimators in finite mixture models has been discussed under the topology of the quotient space obtained by collapsing the true parameter set into a single point. In this paper, we extend the results of Cheng and Liu (2001) to give conditions under which the maximum likelihood estimator (MLE) is strongly consistent in such a sense in finite mixture models with censored data. We also show that the fitted model tends to the true model under a weak condition as the sample size tends to infinity. (C) 2010 Elsevier B.V. All rights reserved.

引用

页码：56 / 64

页数：9

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