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Modified Beta Inverse Flexible Weibull Extension Distribution

Author

Listed:
  • Abdul Ghaniyyu Abubakari

    (C.K. Tedam University of Technology and Applied Sciences)

  • Claudio Chadli Kandza-Tadi

    (African Institute for Mathematical Sciences)

  • Edwin Moyo

    (Mulungushi University)

Abstract

In this article, a new five parameter distribution, known as the modified beta flexible Weibull extension distribution, is derived and studied. Several properties of the distribution including the quantile function, moments, moment generating function, entropies and order statistics are derived. The density function and hazard rate function plots for different parameter values are obtained. It is observed that the density function plots of the distribution exhibit varying shapes and degrees of kurtosis. Also, the hazard rate function plots exhibit different shapes including decreasing, increasing, bathtub, J and reserved J shapes. The parameter estimators of the distribution are obtained using maximum likelihood estimation. The estimators are found to be consistent via a simulation study. Finally, three data sets are used to assess the usefulness of the distribution. It is observed that the distribution can serve as an alternative to modelling failure time data with different characteristics.

Suggested Citation

  • Abdul Ghaniyyu Abubakari & Claudio Chadli Kandza-Tadi & Edwin Moyo, 2023. "Modified Beta Inverse Flexible Weibull Extension Distribution," Annals of Data Science, Springer, vol. 10(3), pages 589-617, June.
    • Handle: RePEc:spr:aodasc:v:10:y:2023:i:3:d:10.1007_s40745-021-00330-3
    DOI: 10.1007/s40745-021-00330-3
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    References listed on IDEAS

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    1. Md. Mahabubur Rahman & Bander Al-Zahrani & Muhammad Qaiser Shahbaz, 2019. "Cubic Transmuted Weibull Distribution: Properties and Applications," Annals of Data Science, Springer, vol. 6(1), pages 83-102, March.
    2. Bebbington, Mark & Lai, Chin-Diew & Zitikis, RiÄ ardas, 2007. "A flexible Weibull extension," Reliability Engineering and System Safety, Elsevier, vol. 92(6), pages 719-726.
    3. Ehab Mohamed Almetwally & Hiba Zeyada Muhammed & El-Sayed A. El-Sherpieny, 2020. "Bivariate Weibull Distribution: Properties and Different Methods of Estimation," Annals of Data Science, Springer, vol. 7(1), pages 163-193, March.
    4. Ahmed Z. Afify & Gauss M. Cordeiro & Edwin M. M. Ortega & Haitham M. Yousof & Nadeem Shafique Butt, 2018. "The four-parameter Burr XII distribution: Properties, regression model, and applications," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 47(11), pages 2605-2624, June.
    5. Ahmad, Abd EL-Baset A. & Ghazal, M.G.M., 2020. "Exponentiated additive Weibull distribution," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    6. Abdus Saboor & Muhammad Nauman Khan & Gauss M. Cordeiro & Marcelino A. R. Pascoa & Juliano Bortolini & Shahid Mubeen, 2019. "Modified beta modified-Weibull distribution," Computational Statistics, Springer, vol. 34(1), pages 173-199, March.
    7. Sarhan, Ammar M. & Apaloo, Joseph, 2013. "Exponentiated modified Weibull extension distribution," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 137-144.
    8. Singla, Neetu & Jain, Kanchan & Kumar Sharma, Suresh, 2012. "The Beta Generalized Weibull distribution: Properties and applications," Reliability Engineering and System Safety, Elsevier, vol. 102(C), pages 5-15.
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