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Inference on Constant-Stress Accelerated Life Testing Based on Geometric Process for Extension of the Exponential Distribution under Type-II Progressive Censoring

Author(s)
M. M. Mohie El-Din Department of Mathematics, Faculty of Science Al-Azhar University, Cairo, Egypt
S. E. Abu-Youssef Department of Mathematics, Faculty of Science Al-Azhar University, Cairo, Egypt
Nahed S. A. Ali Department of Mathematics, Faculty of Education Ain Shams University, Cairo, Egypt
A. M. Abd El-Raheem Department of Mathematics, Faculty of Education Ain Shams University, Cairo, Egypt
Abstract
In this paper, the geometric process is introduced as a constant-stress accelerated model to analyze a series of life data that obtained from several increasing stress levels. The geometric process (GP) model is assumed when the lifetime of test units follows an extension of the exponential distribution. Based on progressive censoring, the maximum likelihood estimates (MLEs) and Bayes estimates (BEs) of the model parameters are obtained. Moreover, a real dataset is analyzed to illustrate the proposed procedures. In addition, the approximate, bootstrap and credible confidence intervals (CIs) of the estimators are constructed. Finally, simulation studies are carried out to investigate the precision of the MLEs and BEs for the parameters involved.
Publication Details
Page(s) 233-251
DOI DOI not available
Published Journal: Pakistan Journal of Statistics and Operation Research, Volume: 14, Issue: 2, Year: 2018

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Keywords
Accelerated life testing, Simulation study, Extension of the exponential distribution, Bayes estimation, Credible confidence interval, Geometric process, Bootstrap confidence interval, Progressive censoring
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