IDEAS home Printed from https://ideas.repec.org/a/vrs/stintr/v23y2022i3p167-184n2.html
   My bibliography  Save this article

Poisson area-biased Ailamujia Distribution and its applications in environmental and medical sciences

Author

Listed:
  • Aijaz Ahmad

    (Department of Mathematics, Bhagwant University, Ajmer, Rajasthan, India .)

  • Ain S. Qurat ul

    (Department of Mathematics, Bhagwant University, Ajmer, Rajasthan, India .)

  • Afaq Ahmad

    (Department of Mathematical Sciences, Islamic University of Science & Technology, Awantipora, Kashmir .)

  • Tripathi Rajnee

    (Department of Mathematics, Bhagwant University, Ajmer, Rajasthan, India .)

Abstract

In this paper, a new Poisson area-biased Ailamujia distribution has been formulated to analyse count data. It was created by combining two distributions: the Poisson and area-biased Ailamujia distributions, using the compounding technique. Several distributional properties of the formulated distribution were studied. Its ageing characteristics were determined and expressed explicitly. A variety of diagrams were used to demonstrate the characteristics of the probability mass function (pmf) and the cumulative distribution function (cdf). The parameter of the developed model was estimated by employing the maximum likelihood estimation approach. Finally, two data sets were used to demonstrate the effectiveness of the investigated distribution.

Suggested Citation

  • Aijaz Ahmad & Ain S. Qurat ul & Afaq Ahmad & Tripathi Rajnee, 2022. "Poisson area-biased Ailamujia Distribution and its applications in environmental and medical sciences," Statistics in Transition New Series, Polish Statistical Association, vol. 23(3), pages 167-184, September.
  • Handle: RePEc:vrs:stintr:v:23:y:2022:i:3:p:167-184:n:2
    DOI: 10.2478/stattrans-2022-0036
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/stattrans-2022-0036
    Download Restriction: no

    File URL: https://libkey.io/10.2478/stattrans-2022-0036?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
    ---><---

    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:vrs:stintr:v:23:y:2022:i:3:p:167-184:n:2. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    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.