IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v47y2018i11p2605-2624.html
   My bibliography  Save this article

The four-parameter Burr XII distribution: Properties, regression model, and applications

Author

Listed:
  • Ahmed Z. Afify
  • Gauss M. Cordeiro
  • Edwin M. M. Ortega
  • Haitham M. Yousof
  • Nadeem Shafique Butt

Abstract

This paper introduces a new four-parameter lifetime model called the Weibull Burr XII distribution. The new model has the advantage of being capable of modeling various shapes of aging and failure criteria. We derive some of its structural properties including ordinary and incomplete moments, quantile and generating functions, probability weighted moments, and order statistics. The new density function can be expressed as a linear mixture of Burr XII densities. We propose a log-linear regression model using a new distribution so-called the log-Weibull Burr XII distribution. The maximum likelihood method is used to estimate the model parameters. Simulation results to assess the performance of the maximum likelihood estimation are discussed. We prove empirically the importance and flexibility of the new model in modeling various types of data.

Suggested Citation

  • 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.
  • Handle: RePEc:taf:lstaxx:v:47:y:2018:i:11:p:2605-2624
    DOI: 10.1080/03610926.2016.1231821
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2016.1231821
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/03610926.2016.1231821?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Broderick Oluyede & Thatayaone Moakofi, 2023. "The Gamma-Topp-Leone-Type II-Exponentiated Half Logistic-G Family of Distributions with Applications," Stats, MDPI, vol. 6(2), pages 1-28, June.
    2. Lucas D. Ribeiro Reis & Gauss M. Cordeiro & Maria do Carmo S. Lima, 2022. "The Stacy-G Class: A New Family of Distributions with Regression Modeling and Applications to Survival Real Data," Stats, MDPI, vol. 5(1), pages 1-43, March.
    3. Gulnaz Raffiq & Iram Sajjad Dar & Muhammad Ahsan Ul Haq & Eduardo Ramos, 2022. "The Marshall–Olkin Inverted Nadarajah–Haghighi Distribution: Estimation and Applications," Annals of Data Science, Springer, vol. 9(6), pages 1323-1338, December.
    4. Ibrahim Elbatal & Emrah Altun & Ahmed Z. Afify & Gamze Ozel, 2019. "The Generalized Burr XII Power Series Distributions with Properties and Applications," Annals of Data Science, Springer, vol. 6(3), pages 571-597, September.
    5. 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.

    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:taf:lstaxx:v:47:y:2018:i:11:p:2605-2624. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/lsta .

    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.