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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">JDS</journal-id>
      <journal-title-group>
        <journal-title>Journal of Data Science</journal-title>
      </journal-title-group>
      <issn pub-type="epub">1680-743X</issn>
      <issn pub-type="ppub">1680-743X</issn>
      <publisher>
        <publisher-name>SOSRUC</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">NO2-3</article-id>
      <article-id pub-id-type="doi">10.6339/JDS.202004_18(2).0003</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>A Log-weighted Power Function Distribution and Its Statistical Properties</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Mandouh</surname>
            <given-names>Rasha Mohamed</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_000"/>
        </contrib>
        <aff id="j_JDS_aff_000">Department of Mathematical Statistics, Faculty of Graduate Studies for Statistical Research, Cairo University, Egypt</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Mohamed</surname>
            <given-names>Mahmoud Abdel-Ghaffar</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_001"/>
        </contrib>
        <aff id="j_JDS_aff_001">Department of Mathematical Statistics, Faculty of Graduate Studies for Statistical Research, Cairo University, Egypt</aff>
      </contrib-group>
      <volume>18</volume>
      <issue>2</issue>
      <fpage>257</fpage>
      <lpage>278</lpage>
      <permissions>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
      </permissions>
      <abstract>
        <p>The Power function distribution is a flexible life time distribution that has applications in finance and economics. It is, also, used to model reliability growth of complex systems or the reliability of repairable systems. A new weighted Power function distribution is proposed using a logarithmic weight function. Statistical properties of the weighted power function distribution are obtained and studied. Location measures such as mode, median and mean, reliability measures such as reliability function, hazard and reversed hazard functions and the mean residual life are derived. Shape indices such as skewness and kurtosis coefficients and order statistics are obtained. Parametric estimation is performed to obtain estimators for the parameters of the distribution using three different estimation methods; namely: the maximum likelihood method, the L-moments method and the method of moments. Numerical simulation is carried out to validate the robustness of the proposed distribution.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>Log-weighted power function distribution</kwd>
        <kwd>Weighted distributions</kwd>
        <kwd>Survival function</kwd>
        <kwd>Hazard rate function</kwd>
        <kwd>Order statistics</kwd>
        <kwd>Maximum likelihood</kwd>
        <kwd>Moments</kwd>
        <kwd>L-moments</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
