IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0248312.html

New generalized-X family: Modeling the reliability engineering applications

Author

Listed:
  • Wanting Wang
  • Zubair Ahmad
  • Omid Kharazmi
  • Clement Boateng Ampadu
  • E H Hafez
  • Marwa M Mohie El-Din

Abstract

As is already known, statistical models are very important for modeling data in applied fields, particularly in engineering, medicine, and many other disciplines. In this paper, we propose a new family to introduce new distributions suitable for modeling reliability engineering data. We called our proposed family a new generalized-X family of distributions. For the practical illustration, we introduced a new special sub-model, called the new generalized-Weibull distribution, to describe the new family’s significance. For the proposed family, we introduced some mathematical reliability properties. The maximum likelihood estimators for the parameters of the new generalized-X distributions are derived. For assessing the performance of these estimators, a comprehensive Monte Carlo simulation study is carried out. To assess the efficiency of the proposed model, the new generalized-Weibull model is applied to the coating machine failure time data. Finally, Bayesian analysis and performance of Gibbs sampling for the coating machine failure time data are also carried out. Furthermore, the measures such as Gelman-Rubin, Geweke and Raftery-Lewis are used to track algorithm convergence.

Suggested Citation

  • Wanting Wang & Zubair Ahmad & Omid Kharazmi & Clement Boateng Ampadu & E H Hafez & Marwa M Mohie El-Din, 2021. "New generalized-X family: Modeling the reliability engineering applications," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-26, March.
    • Handle: RePEc:plo:pone00:0248312
    DOI: 10.1371/journal.pone.0248312
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0248312
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0248312&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0248312?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Omid Kharazmi & Ali Saadatinik & Shahla Jahangard, 2019. "Odd Hyperbolic Cosine Exponential-Exponential (OHC-EE) Distribution," Annals of Data Science, Springer, vol. 6(4), pages 765-785, December.
    2. Faton Merovci & Morad Alizadeh & Haitham M. Yousof & G. G. Hamedani, 2017. "The exponentiated transmuted-G family of distributions: Theory and applications," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(21), pages 10800-10822, November.
    3. Suleman Nasiru & Peter N. Mwita & Oscar Ngesa, 2017. "Exponentiated Generalized Transformed-Transformer Family of Distributions," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 6(4), pages 1-1.
    4. Wei Zhao & Saima K Khosa & Zubair Ahmad & Muhammad Aslam & Ahmed Z Afify, 2020. "Type-I heavy tailed family with applications in medicine, engineering and insurance," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-24, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mohammed M. A. Almazah & Kalim Ullah & Eslam Hussam & Md. Moyazzem Hossain & Ramy Aldallal & Fathy H. Riad, 2022. "New Statistical Approaches for Modeling the COVID‐19 Data Set: A Case Study in the Medical Sector," Complexity, John Wiley & Sons, vol. 2022(1).
    2. Ibrahim Alkhairy & Humaira Faqiri & Zubir Shah & Hassan Alsuhabi & M. Yusuf & Ramy Aldallal & Nicholas Makumi & Fathy H. Riad, 2022. "A New Flexible Logarithmic‐X Family of Distributions with Applications to Biological Systems," Complexity, John Wiley & Sons, vol. 2022(1).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rana Muhammad Usman & Muhammad Ahsan ul Haq, 2019. "Some Remarks on Odd Burr III Weibull Distribution," Annals of Data Science, Springer, vol. 6(1), pages 21-38, March.
    2. Rashad A. R. Bantan & Christophe Chesneau & Farrukh Jamal & Mohammed Elgarhy, 2020. "On the Analysis of New COVID-19 Cases in Pakistan Using an Exponentiated Version of the M Family of Distributions," Mathematics, MDPI, vol. 8(6), pages 1-20, June.
    3. Basma Ahmed & M. Masoom Ali & Haitham M. Yousof, 2024. "A Novel G Family for Single Acceptance Sampling Plan with Application in Quality and Risk Decisions," Annals of Data Science, Springer, vol. 11(1), pages 181-199, February.
    4. Mohamed Ibrahim & M. Masoom Ali & Haitham M. Yousof, 2023. "The Discrete Analogue of the Weibull G Family: Properties, Different Applications, Bayesian and Non-Bayesian Estimation Methods," Annals of Data Science, Springer, vol. 10(4), pages 1069-1106, August.
    5. Haitham M. Yousof & M. Masoom Ali & Hafida Goual & Mohamed Ibrahim, 2021. "A new reciprocal Rayleigh extension: properties, copulas, different methods of estimation and a modified right-censored test for validation," Statistics in Transition New Series, Polish Statistical Association, vol. 22(3), pages 99-121, September.
    6. Clement Boateng Ampadu & Suleman Nasiru & Girish Babu, 2018. "Further Developments on the T-Transmuted X Family of Distributions II," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 8(2), pages 22-24, September.
    7. Yousof Haitham M. & Masoom Ali M. & Goual Hafida & Ibrahim Mohamed, 2021. "A new reciprocal Rayleigh extension: properties, copulas, different methods of estimation and a modified right-censored test for validation," Statistics in Transition New Series, Statistics Poland, vol. 22(3), pages 99-121, September.
    8. Ebrahim Bonyadi & Lida Sarreshtehdari, 2021. "The Global Entrepreneurship Index (GEI): a critical review," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 11(1), pages 469-488, December.
    9. Lea Anzagra & Solomon Sarpong & Suleman Nasiru, 2022. "Odd Chen-G Family of Distributions," Annals of Data Science, Springer, vol. 9(2), pages 369-391, April.
    10. Nada M. Alfaer & Ahmed M. Gemeay & Hassan M. Aljohani & Ahmed Z. Afify, 2021. "The Extended Log-Logistic Distribution: Inference and Actuarial Applications," Mathematics, MDPI, vol. 9(12), pages 1-22, June.
    11. Zubir Shah & Amjad Ali & Muhammad Hamraz & Dost Muhammad Khan & Zardad Khan & M. EL-Morshedy & Afrah Al-Bossly & Zahra Almaspoor, 2022. "A New Member of T‐X Family with Applications in Different Sectors," Journal of Mathematics, John Wiley & Sons, vol. 2022(1).
    12. Suleman Nasiru & Peter N. Mwita & Oscar Ngesa, 2019. "Exponentiated Generalized Power Series Family of Distributions," Annals of Data Science, Springer, vol. 6(3), pages 463-489, September.
    13. Mohammed M. A. Almazah & Kalim Ullah & Eslam Hussam & Md. Moyazzem Hossain & Ramy Aldallal & Fathy H. Riad, 2022. "New Statistical Approaches for Modeling the COVID‐19 Data Set: A Case Study in the Medical Sector," Complexity, John Wiley & Sons, vol. 2022(1).
    14. Sudhansu S. Maiti & Molay Kumar Ruidas & Sumanta Adhya, 2024. "Natural Discrete One Parameter Polynomial Exponential Family of Distributions and the Application," Annals of Data Science, Springer, vol. 11(3), pages 1051-1076, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0248312. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.