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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
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.
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页码:2973 / 2988
页数:16
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