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Reliability Estimation of XLindley Constant-Stress Partially Accelerated Life Tests using Progressively Censored Samples

Author

Listed:
  • Mazen Nassar

    (Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah 21589, Saudi Arabia
    Department of Statistics, Faculty of Commerce, Zagazig University, Zagazig 44519, Egypt)

  • Refah Alotaibi

    (Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia)

  • Ahmed Elshahhat

    (Faculty of Technology and Development, Zagazig University, Zagazig 44519, Egypt)

Abstract

It often takes a lot of time to conduct life-testing studies on products or components. Units can be tested under more severe circumstances than usual, known as accelerated life tests, to reduce the testing period. This study’s goal is to look into certain estimation issues related to point and interval estimations for XLindley distribution under constant stress partially accelerated life tests with progressive Type-II censored samples. The maximum likelihood approach is utilized to acquire the point and interval estimates of the model parameters as well as the reliability function under normal use conditions. The Bayesian estimation method using the Monte Carlo Markov Chain procedure using the squared error loss function is also provided. Moreover, the Bayes credible intervals as well as the highest posterior density credible intervals of the different parameters are considered. To make comparisons between the proposed methods, a simulation study is conducted with various sample sizes and different censoring schemes. The usefulness of the suggested methodologies is then demonstrated by the analysis of two data sets. A summary of the major findings of the study can be found in the conclusion.

Suggested Citation

  • Mazen Nassar & Refah Alotaibi & Ahmed Elshahhat, 2023. "Reliability Estimation of XLindley Constant-Stress Partially Accelerated Life Tests using Progressively Censored Samples," Mathematics, MDPI, vol. 11(6), pages 1-24, March.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:6:p:1331-:d:1092462
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    References listed on IDEAS

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    1. N. Balakrishnan, 2007. "Progressive censoring methodology: an appraisal," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(2), pages 211-259, August.
    2. N. Balakrishnan, 2007. "Rejoinder on: Progressive censoring methodology: an appraisal," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 16(2), pages 290-296, August.
    3. Sanku Dey & Liang Wang & Mazen Nassar, 2022. "Inference on Nadarajah–Haghighi distribution with constant stress partially accelerated life tests under progressive type-II censoring," Journal of Applied Statistics, Taylor & Francis Journals, vol. 49(11), pages 2891-2912, August.
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    5. Refah Alotaibi & Mazen Nassar & Hoda Rezk & Ahmed Elshahhat, 2022. "Inferences and Engineering Applications of Alpha Power Weibull Distribution Using Progressive Type-II Censoring," Mathematics, MDPI, vol. 10(16), pages 1-21, August.
    6. Mazen Nassar & Ahmed Elshahhat, 2023. "Statistical Analysis of Inverse Weibull Constant-Stress Partially Accelerated Life Tests with Adaptive Progressively Type I Censored Data," Mathematics, MDPI, vol. 11(2), pages 1-29, January.
    7. Pareek, Bhuvanesh & Kundu, Debasis & Kumar, Sumit, 2009. "On progressively censored competing risks data for Weibull distributions," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4083-4094, October.
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    Cited by:

    1. Amel Abd-El-Monem & Mohamed S. Eliwa & Mahmoud El-Morshedy & Afrah Al-Bossly & Rashad M. EL-Sagheer, 2023. "Statistical Analysis and Theoretical Framework for a Partially Accelerated Life Test Model with Progressive First Failure Censoring Utilizing a Power Hazard Distribution," Mathematics, MDPI, vol. 11(20), pages 1-21, October.

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