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：

暂无

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.

引用

页码：223 / 229

页数：6

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