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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">130309</article-id>
      <article-id pub-id-type="doi">10.6339/JDS.201504_13(2).0009</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>A New Extension of the Normal Distribution</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Lima</surname>
            <given-names>Maria do Carmo S.</given-names>
          </name>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Cordeiro</surname>
            <given-names>Gauss M.</given-names>
          </name>
        </contrib>
        <contrib contrib-type="author">
          <name>
            <surname>Ortega</surname>
            <given-names>Edwin M.M.</given-names>
          </name>
        </contrib>
      </contrib-group>
      <volume>13</volume>
      <issue>2</issue>
      <fpage>385</fpage>
      <lpage>408</lpage>
      <permissions>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
      </permissions>
      <abstract>
        <p>Providing a new distribution is always precious for statisticians. A new three parameter distribution called the gamma normal distribution is defined and studied. Various structural properties of the new distribution are derived, including some explicit expressions for the moments, quantile and generating functions, mean deviations, probability weighted moments and two types of entropy. We also investigate the order statistics and their moments. Maximum likelihood techniques are used to fit the new model and to show its potentiality by means of two examples of real data. Based on three criteria, the proposed distribution provides a better fit then the skew-normal distribution.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>Gamma distribution</kwd>
        <kwd>Maximum likelihood estimation</kwd>
        <kwd>Mean deviation</kwd>
        <kwd>Normal distribution</kwd>
        <kwd>Quantile</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
