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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">140301</article-id>
      <article-id pub-id-type="doi">10.6339/JDS.201607_14(3).0001</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 Exponential Distribution</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Andrade</surname>
            <given-names>Thiago A. N. de</given-names>
          </name>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Bourguignon</surname>
            <given-names>Marcelo</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_001"/>
        </contrib>
        <aff id="j_JDS_aff_001">Departamento de Estat´ıstica, Universidade Federal do Rio Grande do Norte</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Cordeiro</surname>
            <given-names>Gauss M.</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_002"/>
        </contrib>
        <aff id="j_JDS_aff_002">Departamento de Estat´ıstica, Universidade Federal de Pernambuco</aff>
      </contrib-group>
      <volume>14</volume>
      <issue>3</issue>
      <fpage>393</fpage>
      <lpage>414</lpage>
      <permissions>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
      </permissions>
      <abstract>
        <p>Abstract: We introduce and study a new four-parameter lifetime model named the exponentiated generalized extended exponential distribution. The proposed model has the advantage of including as special cases the exponential and exponentiated exponential distributions, among others, and its hazard function can take the classic shapes: bathtub, inverted bathtub, increasing, decreasing and constant, among others. We derive some mathematical properties of the new model such as a representation for the density function as a double mixture of Erlang densities, explicit expressions for the quantile function, ordinary and incomplete moments, mean deviations, Bonferroni and Lorenz curves, generating function, R´enyi entropy, density of order statistics and reliability. We use the maximum likelihood method to estimate the model parameters. Two applications to real data illustrate the flexibility of the proposed model.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>Erlang distribution</kwd>
        <kwd>Extended exponential distribution</kwd>
        <kwd>Moments</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
