IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0324005.html
   My bibliography  Save this article

WLreg: A new re-parametrization of the Weighted Lindley distribution and its regression model

Author

Listed:
  • Emrah Altun
  • Christophe Chesneau
  • Hana N Alqifari

Abstract

A novel re-parametrization of the weighted Lindley distribution is introduced to develop a regression model suitable for skewed dependent variables defined on ℝ+. This new model is called the WL2 regression model. It is shown to outperform existing models such as the gamma, extended gamma, and Maxwell-Boltzmann-exponential regression models. Parameter estimation is performed using the maximum likelihood estimation technique, and the efficiency of these estimates is assessed through a simulation study. An application to a house price data set is presented to highlight the importance of the WL2 regression model. In addition, we propose the WLreg software, accessible via https://bartinuni.shinyapps.io/WLreg, to facilitate the application of the new regression model for practitioners in the field.

Suggested Citation

  • Emrah Altun & Christophe Chesneau & Hana N Alqifari, 2025. "WLreg: A new re-parametrization of the Weighted Lindley distribution and its regression model," PLOS ONE, Public Library of Science, vol. 20(6), pages 1-15, June.
    • Handle: RePEc:plo:pone00:0324005
    DOI: 10.1371/journal.pone.0324005
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0324005
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0324005&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0324005?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. Muhammad Nauman Akram & Muhammad Amin & Muhammad Qasim, 2023. "A new biased estimator for the gamma regression model: Some applications in medical sciences," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 52(11), pages 3612-3632, June.
    Full references (including those not matched with items on IDEAS)

    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.

      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:pone00:0324005. 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.