Bayes Inference in Constant Partially Accelerated Life Tests for the Generalized Exponential Distribution with Progressive Censoring

被引：22
|
作者：
Jaheen, Z. F. [1 ]
Moustafa, H. M. [2 ]
Abd El-Monem, G. H. [2 ]
机构：
[1] King Abdulaziz Univ, Fac Sci, Dept Stat, Jeddah 21413, Saudi Arabia
[2] Assiut Univ, Fac Sci, Dept Math, Assiut 71516, Egypt
来源：
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2014年 / 43卷 / 14期
关键词：
Bayesian estimation; Constant partially accelerated life tests; Generalized exponential distribution; Maximum likelihood estimation; Monte Carlo simulation; Progressive Type-II censoring; FINITE MIXTURE-MODELS; INTERVAL ESTIMATION; STRESS; STEP; PARAMETERS;
D O I：
10.1080/03610926.2012.687068
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：
In this paper, the problem of constant partially accelerated life tests when the lifetime follows the generalized exponential distribution is considered. Based on progressive type-II censoring scheme, the maximum likelihood and Bayes methods of estimation are used for estimating the distribution parameters and acceleration factor. A Monte Carlo simulation study is carried out to examine the performance of the obtained estimates.
引用
收藏
页码：2973 / 2988
页数：16
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