<?xml version="1.0" encoding="UTF-8"?>
<article article-type="Research Article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher">journal-of-statistics-and-management-systems</journal-id>
      <journal-title-group>
        <journal-title> Journal of Statistics and Management Systems</journal-title>
      </journal-title-group>
      <issn publication-format="electronic">2169-0014</issn>
      <issn publication-format="print">0972-0510</issn>
      <publisher>
        <publisher-name>Taru Publications</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.47974/JSMS-1371</article-id>
      <title-group>
        <article-title>The new continuous distribution : Statistical properties and modelling for Covid-19 data</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes">
          <name>
            <surname>Karakaş</surname>
            <given-names>Ayşe Metin</given-names>
          </name>
          <aff>Department of Statistics, Faculty of Art and Science, Bitlis Eren University, Bitlis, 13000, Turkey</aff>
        </contrib>
      </contrib-group>
      <volume>28</volume>
      <issue>4</issue>
      <fpage>691</fpage>
      <lpage>711</lpage>
      <pub-date date-type="pub">
        <day>06</day>
        <month>05</month>
        <year>2025</year>
      </pub-date>
      <abstract>
        <p>Our research unveils a transformative distribution model: the Kumaraswamy power burr distribution. This innovative model emerges through the application of the Kumaraswamy transformation to the power burr distribution. We meticulously outline the probability and distribution functions, supported by compelling graphs and a rigorous mathematical foundation for the probability function of this novel distribution. In addition, we offer detailed equations and an extensive analysis of the statistical properties of this distribution. Parameter estimation is skillfully executed using the maximum likelihood estimation (MLE) method. Our compelling evidence shows that this newly created distribution not only enhances accuracy but also outperforms existing models significantly in analyzing COVID-19 data.</p>
      </abstract>
      <kwd-group>
        <kwd>Burr Type XII distribution</kwd>
        <kwd>Kumaraswamy distribution</kwd>
        <kwd>Hazard rate function</kwd>
        <kwd>Entropy</kwd>
      </kwd-group>
      <custom-meta-group>
        <custom-meta>
          <meta-name>access</meta-name>
          <meta-value>open</meta-value>
        </custom-meta>
        <custom-meta>
          <meta-name>retracted</meta-name>
          <meta-value>no</meta-value>
        </custom-meta>
      </custom-meta-group>
    </article-meta>
  </front>
</article>
