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

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  • Z. F. Jaheen
  • H. M. Moustafa
  • G. H. Abd El-Monem

Abstract

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.

Suggested Citation

  • Z. F. Jaheen & H. M. Moustafa & G. H. Abd El-Monem, 2014. "Bayes Inference in Constant Partially Accelerated Life Tests for the Generalized Exponential Distribution with Progressive Censoring," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(14), pages 2973-2988, July.
    • Handle: RePEc:taf:lstaxx:v:43:y:2014:i:14:p:2973-2988
    DOI: 10.1080/03610926.2012.687068
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    Cited by:

    1. A. M. Abd El-Raheem & M. H. Abu-Moussa & Marwa M. Mohie El-Din & E. H. Hafez, 2020. "Accelerated Life Tests under Pareto-IV Lifetime Distribution: Real Data Application and Simulation Study," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
    2. M. M. Mohie El-Din & S. E. Abu-Youssef & Nahed S. A. Ali & A. M. Abd El-Raheem, 2016. "Estimation in constant-stress accelerated life tests for extension of the exponential distribution under progressive censoring," METRON, Springer;Sapienza Università di Roma, vol. 74(2), pages 253-273, August.
    3. Wenjie Zhang & Wenhao Gui, 2022. "Statistical Inference and Optimal Design of Accelerated Life Testing for the Chen Distribution under Progressive Type-II Censoring," Mathematics, MDPI, vol. 10(9), pages 1-21, May.
    4. M. M. Mohie El-Din & A. M. Abd El-Raheem & S. O. Abd El-Azeem, 2021. "On Step-Stress Accelerated Life Testing for Power Generalized Weibull Distribution Under Progressive Type-II Censoring," Annals of Data Science, Springer, vol. 8(3), pages 629-644, September.

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