Approximate MLE for the scaled generalized exponential distribution under progressive type-II censoring

被引：0
|
作者：
A. Asgharzadeh
机构：
[1] University of Mazandaran,Department of Statistics, Faculty of Basic Science
[2] Statistical Research Center,undefined
来源：
Journal of the Korean Statistical Society | 2009年 / 38卷
关键词：
Bias; Confidence interval; Fisher information; Generalized exponential distribution; Maximum likelihood estimator; Monte Carlo simulation; Pivotal quantity; Progressive Type-II censoring; 62N02; 62E15;
D O I：
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中图分类号：
学科分类号：
摘要：
For the generalized exponential (GE) distribution, the maximum likelihood method does not provide an explicit estimator for the scale parameter based on a progressively Type-II censored sample. This paper provides a simple method of deriving an explicit estimator by approximating the likelihood function. A Monte Carlo simulation is used to investigate the accuracy of this estimator and two examples are given to illustrate this method of estimation.
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页码：223 / 229
页数：6
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