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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">03.NO.6-320</article-id>
      <article-id pub-id-type="doi">10.6339/JDS.201907_17(3).0006</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>New Modified Singh-Maddala Distribution: Development, Properties, Characterizations And Applications</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Bhatti</surname>
            <given-names>Fiaz Ahmad</given-names>
          </name>
          <email xlink:href="mailto:fiazahmad72@gmail.com">fiazahmad72@gmail.com</email>
          <xref ref-type="aff" rid="j_JDS_aff_000"/>
        </contrib>
        <aff id="j_JDS_aff_000">National College of Business Administration and Economics , Lahore Pakistan</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Hamedani</surname>
            <given-names>G.G.</given-names>
          </name>
          <email xlink:href="mailto:g.hamedani@mu.edu">g.hamedani@mu.edu</email>
          <xref ref-type="aff" rid="j_JDS_aff_001"/>
        </contrib>
        <aff id="j_JDS_aff_001">Marquette University, Milwaukee, WI 53201-1881, USA</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Korkmaz</surname>
            <given-names>Mustafa Ç.</given-names>
          </name>
          <email xlink:href="mailto:mcagatay@artvin.edu.tr">mcagatay@artvin.edu.tr</email>
          <xref ref-type="aff" rid="j_JDS_aff_002"/>
        </contrib>
        <aff id="j_JDS_aff_002">Department of Measurement and Evaluation, Artvin Çoruh University, Artvin, Turkey</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Ahmad</surname>
            <given-names>Munir</given-names>
          </name>
          <email xlink:href="mailto:mustafacagataykorkmaz@gmail.com">mustafacagataykorkmaz@gmail.com</email>
          <xref ref-type="aff" rid="j_JDS_aff_003"/>
        </contrib>
        <aff id="j_JDS_aff_003">National College of Business Administration and Economics , Lahore Pakistan</aff>
      </contrib-group>
      <volume>17</volume>
      <issue>3</issue>
      <fpage>551</fpage>
      <lpage>574</lpage>
      <permissions>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
      </permissions>
      <abstract>
        <p>In this paper, a new five-parameter extended Burr XII model called new modified Singh-Maddala (NMSM) is developed from cumulative hazard function of the modified log extended integrated beta hazard (MLEIBH) model. The NMSM density function is left-skewed, right-skewed and symmetrical. The Lambert W function is used to study descriptive measures based on quantile, moments, and moments of order statistics, incomplete moments, inequality measures and residual life function. Different reliability and uncertainty measures are also theoretically established. The NMSM distribution is characterized via different techniques and its parameters are estimated using maximum likelihood method. The simulation studies are performed on the basis of graphical results to illustrate the performance of maximum likelihood estimates (MLEs) of the parameters. The significance and flexibility of NMSM distribution is tested through different measures by application to two real data sets.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>Moments</kwd>
        <kwd>Lambert W function</kwd>
        <kwd>Reliability</kwd>
        <kwd>Characterizations</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
