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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">160407</article-id>
      <article-id pub-id-type="doi">10.6339/JDS.201810_16(4).00007</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>The Exponentiated Generalized Extended Pareto Distribution</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Andrade</surname>
            <given-names>Thiago A. N. De</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_000"/>
        </contrib>
        <aff id="j_JDS_aff_000">Universidade Federal de Pernambuco Departamento de Estatstica, Cidade Universit´aria, 50740-540, Recife, PE, Brazil</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Zea</surname>
            <given-names>Luz M.</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_001"/>
        </contrib>
        <aff id="j_JDS_aff_001">Universidade Federal do Rio Grande do Norte Departamento de Estatstica, Lagoa Nova, 59078-970, Natal, RN, Brazil</aff>
      </contrib-group>
      <volume>16</volume>
      <issue>4</issue>
      <fpage>781</fpage>
      <lpage>800</lpage>
      <permissions>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
      </permissions>
      <abstract>
        <p>We define and study a three-parameter model with positive real support called the exponentiated generalized extended Pareto distribution. We provide a comprehensive mathematical treatment and prove that the formulas related to the new model are simple and manageable. We study the behaviour of the maximum likelihood estimates for the model parameters using Monte Carlo simulation. We take advantage of applied studies and offer two applications to real data sets that proves empirically the power of adjustment of the new model when compared to another twelve lifetime distributions.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>Applied studies</kwd>
        <kwd>Exponentiated generalized model</kwd>
        <kwd>Extended Pareto distribution</kwd>
        <kwd>Lehmann’s alternatives</kwd>
        <kwd>Monte Carlo simulation</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
