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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.9-355</article-id>
      <article-id pub-id-type="doi">10.6339/JDS.201907_17(3).0009</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Estimation Methods for the New Weibull-Pareto Distribution: Simulation and Application</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Almetwally</surname>
            <given-names>Ehab. M.</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_000"/>
        </contrib>
        <aff id="j_JDS_aff_000">Department of Statistics, Higher Institute of Computer and Management Information Systems</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Almongy</surname>
            <given-names>Hisham. M.</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_001"/>
        </contrib>
        <aff id="j_JDS_aff_001">Department of Applied Statistics, Faculty of Commerce Mansoura University</aff>
      </contrib-group>
      <volume>17</volume>
      <issue>3</issue>
      <fpage>613</fpage>
      <lpage>632</lpage>
      <permissions>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
      </permissions>
      <abstract>
        <p>In this paper, we introduce the alternative methods to estimation for the new weibull-pareto distribution parameters. We discussed of point estimation and interval estimation for parameters of the new weibull-pareto distribution. We have also discussed the method of Maximum Likelihood estimation, the method of Least Squares estimation, the method of Weighted Least Squares estimation and the method of Maximum Product Spacing estimation. In addition, we discussed the raw moment of random variable X and the reliability functions (survival and hazard functions). Further, we compared between the results of the methods that have been discussed using Monte Carlo Simulation method and application study.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>The new Weibull-Pareto Distribution</kwd>
        <kwd>Maximum Likelihood Estimation</kwd>
        <kwd>least-squares Estimation</kwd>
        <kwd>weighted least-squares Estimation</kwd>
        <kwd>Maximum Product Spacing method</kwd>
        <kwd>Interval Estimation</kwd>
        <kwd>Bootstrap and Reliability Functions</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
