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Predicting future lifetime based on random number of three parameters Weibull distribution

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  • El-Adll, Magdy E.

Abstract

In this paper, two pivotal quantities are modified to construct prediction intervals for future lifetime based on random number of three parameters Weibull distribution, which can be widely applied in reliability theory and lifetime problems. The case of fixed sample size is presented as a special case. The random number has one of three important distributions as special cases. An algorithm is constructed to explain the importance of the theoretical results in applications. Simulation studies are conducted to investigate the efficiency of the purposed results. Finally, two numerical examples for real lifetime data are presented to illustrate the paper.

Suggested Citation

  • El-Adll, Magdy E., 2011. "Predicting future lifetime based on random number of three parameters Weibull distribution," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(9), pages 1842-1854.
    • Handle: RePEc:eee:matcom:v:81:y:2011:i:9:p:1842-1854
    DOI: 10.1016/j.matcom.2011.02.003
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    References listed on IDEAS

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    1. Aboeleneen, Z.A., 2010. "Inference for Weibull distribution under generalized order statistics," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(1), pages 26-36.
    2. J. M. Buhrman, 1973. "On order statistics when the sample size has a binomial distribution," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 27(3), pages 125-126, September.
    3. Lee, Hsiu-Mei & Lee, Wen-Chuan & Lei, Chia-Ling & Wu, Jong-Wuu, 2011. "Computational procedure of assessing lifetime performance index of Weibull lifetime products with the upper record values," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(6), pages 1177-1189.
    4. K. Raghunandanan & S. A. Patil, 1972. "On order statistics for random sample size," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 26(4), pages 121-126, December.
    5. Wang, Lichun & Wang, Xuan, 2009. "The life-span prediction of a system connected in series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(5), pages 1770-1777.
    6. Yang, Zhenlin & See, Stanley P. & Xie, M., 2003. "Transformation approaches for the construction of Weibull prediction interval," Computational Statistics & Data Analysis, Elsevier, vol. 43(3), pages 357-368, July.
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    Citations

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    Cited by:

    1. Jazaa S. Al-Mutairi & Mohammad Z. Raqab, 2020. "Confidence intervals for quantiles based on samples of random sizes," Statistical Papers, Springer, vol. 61(1), pages 261-277, February.
    2. H. M. Barakat & E. M. Nigm & Magdy E. El-Adll & M. Yusuf, 2018. "Prediction of future generalized order statistics based on exponential distribution with random sample size," Statistical Papers, Springer, vol. 59(2), pages 605-631, June.
    3. Magdy El-Adll & H. M. Barakat & Amany Aly & Ning Cai, 2022. "Asymptotic Prediction for Future Observations of a Random Sample of Unknown Continuous Distribution," Complexity, Hindawi, vol. 2022, pages 1-15, April.
    4. Jorge Navarro & Francesco Buono, 2023. "Predicting future failure times by using quantile regression," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(5), pages 543-576, July.
    5. Omar M. Bdair & Mohammad Z. Raqab, 2022. "Prediction of future censored lifetimes from mixture exponential distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(7), pages 833-857, October.
    6. Amany E. Aly, 2023. "Predictive inference of dual generalized order statistics from the inverse Weibull distribution," Statistical Papers, Springer, vol. 64(1), pages 139-160, February.

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