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        <identifier>oai.jstatsoft/v31/i04</identifier>
        <datestamp>2009-08-04</datestamp>
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          <dc:title>Gifi Methods for Optimal Scaling in R: The Package homals</dc:title>
          <dc:creator>Jan de Leeuw</dc:creator>
          <dc:creator>Patrick Mair</dc:creator>
          <dc:date>2009-08-04</dc:date>
          <dc:publisher>Journal of Statistical Software</dc:publisher>
          <dc:description>
            <![CDATA[Vol. 31, Issue 4, Aug 2009
Abstract:
Homogeneity analysis combines the idea of maximizing the correlations between variables of a multivariate data set with that of optimal scaling. In this article we present methodological and practical issues of the <b>R</b> package <b>homals</b> which performs homogeneity analysis and various extensions. By setting rank constraints nonlinear principal component analysis can be performed. The variables can be partitioned into sets such that homogeneity analysis is extended to nonlinear canonical correlation analysis or to predictive models which emulate discriminant analysis and regression models. For each model the scale level of the variables can be taken into account by setting level constraints. All algorithms allow for missing values.]]>
          </dc:description>
          <dc:subject>Statistics</dc:subject>
          <dc:subject>Software</dc:subject>
          <dc:identifier>http://www.jstatsoft.org/v31/i04</dc:identifier>
          <dc:source>http://www.jstatsoft.org/v31/i04/paper</dc:source>
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