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Reliability Models Using the Composite Generalizers of Weibull Distribution

Author

Listed:
  • Gokarna R. Aryal

    (Purdue University Northwest)

  • Keshav P. Pokhrel

    (University of Michigan- Dearborn)

  • Netra Khanal

    (The University of Tampa)

  • Chris P. Tsokos

    (University of South Florida)

Abstract

In this article, we study the composite generalizers of Weibull distribution using exponentiated, Kumaraswamy, transmuted and beta distributions. The composite generalizers are constructed using both forward and reverse order of each of these distributions. The usefulness and effectiveness of the composite generalizers and their order of composition is investigated by studying the reliability behavior of the resulting distributions. Two sets of real-world data are analyzed using the proposed generalized Weibull distributions.

Suggested Citation

  • Gokarna R. Aryal & Keshav P. Pokhrel & Netra Khanal & Chris P. Tsokos, 2019. "Reliability Models Using the Composite Generalizers of Weibull Distribution," Annals of Data Science, Springer, vol. 6(4), pages 807-829, December.
    • Handle: RePEc:spr:aodasc:v:6:y:2019:i:4:d:10.1007_s40745-019-00205-8
    DOI: 10.1007/s40745-019-00205-8
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    References listed on IDEAS

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    1. Alexander, Carol & Cordeiro, Gauss M. & Ortega, Edwin M.M. & Sarabia, José María, 2012. "Generalized beta-generated distributions," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 1880-1897.
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    Cited by:

    1. B. Singh & R. U. Khan & A. N. Khan, 2022. "Moments of Dual Generalized Order Statistics from Topp Leone Weighted Weibull Distribution and Characterization," Annals of Data Science, Springer, vol. 9(6), pages 1129-1148, December.
    2. Aliyu Ismail Ishaq & Alfred Adewole Abiodun, 2020. "The Maxwell–Weibull Distribution in Modeling Lifetime Datasets," Annals of Data Science, Springer, vol. 7(4), pages 639-662, December.
    3. Hassan M. Okasha & Abdulkareem M. Basheer & A. H. El-Baz, 2021. "Marshall–Olkin Extended Inverse Weibull Distribution: Different Methods of Estimations," Annals of Data Science, Springer, vol. 8(4), pages 769-784, December.

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