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Partially Accelerated Model for Analyzing Competing Risks Data from Gompertz Population under Type-I Generalized Hybrid Censoring Scheme

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  • Abdulaziz S. Alghamdi
  • Ahmed Mostafa Khalil

Abstract

In reliability engineering and lifetime analysis, many units of the product fail with different causes of failure, and some tests require stress higher than normal stress. Also, we need to design the life experiments which present methodology for formulating scientific and engineering problems using statistical models. So, in this paper, we adopted a partially constant stress accelerated life test model to present times to failure in a small period of time for Gompertz life products. Also, considering that, units are failing with the only two independent causes of failure and tested under type-I generalized hybrid censoring scheme the data built. Obtained data are analyzed with two methods of estimations, maximum likelihood and Bayes methods. These two methods are used to construct the point and interval estimators with the help of the MCMC method. The developed results are measured and compared under Monte Carlo studying. Also, a data set is analyzed for illustration purposes. Finally, some comments are presented to describe the numerical results.

Suggested Citation

  • Abdulaziz S. Alghamdi & Ahmed Mostafa Khalil, 2021. "Partially Accelerated Model for Analyzing Competing Risks Data from Gompertz Population under Type-I Generalized Hybrid Censoring Scheme," Complexity, Hindawi, vol. 2021, pages 1-12, May.
    • Handle: RePEc:hin:complx:9925094
    DOI: 10.1155/2021/9925094
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    Cited by:

    1. Saieed F. Ateya & Abdulaziz S. Alghamdi & Abd Allah A. Mousa, 2022. "Future Failure Time Prediction Based on a Unified Hybrid Censoring Scheme for the Burr-X Model with Engineering Applications," Mathematics, MDPI, vol. 10(9), pages 1-23, April.
    2. Yuan Ma & Wenhao Gui, 2021. "Competing Risks Step-Stress Model with Lagged Effect under Gompertz Distribution," Mathematics, MDPI, vol. 9(24), pages 1-26, December.
    3. Zhang, Chunfang & Wang, Liang & Bai, Xuchao & Huang, Jianan, 2022. "Bayesian reliability analysis for copula based step-stress partially accelerated dependent competing risks model," Reliability Engineering and System Safety, Elsevier, vol. 227(C).

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