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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">090304</article-id>
      <article-id pub-id-type="doi">10.6339/JDS.201107_09(3).0004</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Measuring Local Influential Observations in Modified Ridge Regression</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <name>
            <surname>Jahufer</surname>
            <given-names>Aboobacker</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_000"/>
        </contrib>
        <aff id="j_JDS_aff_000">South Eastern University</aff>
        <contrib contrib-type="author">
          <name>
            <surname>Chen</surname>
            <given-names>Jianbao</given-names>
          </name>
          <xref ref-type="aff" rid="j_JDS_aff_001"/>
        </contrib>
        <aff id="j_JDS_aff_001">Xiamen University</aff>
      </contrib-group>
      <volume>9</volume>
      <issue>3</issue>
      <fpage>359</fpage>
      <lpage>372</lpage>
      <permissions>
        <ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/>
      </permissions>
      <abstract>
        <p>Abstract: In this paper, we use generalized influence function and generalized Cook distance to measure the local influence of minor perturbation on the modified ridge regression estimator in ridge type linear regression model. The diagnostics under the perturbation of constant variance and individual explanatory variables are obtained when multicollinearity presents among the regressors. Also we proposed a statistic that reveals the influential cases for Mallow’s method which is used to choose modified ridge regression estimator biasing parameter. Two real data sets are used to illustrate our methodologies.</p>
      </abstract>
      <kwd-group>
        <label>Keywords</label>
        <kwd>Local influential observations</kwd>
        <kwd>modified ridge regression</kwd>
        <kwd>perturbation scheme</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
