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Symbolic Multidimensional Scaling

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  • Groenen, P.J.F.
  • Terada, Y.

Abstract

__Abstract__ Multidimensional scaling (MDS) is a technique that visualizes dissimilarities between pairs of objects as distances between points in a low dimensional space. In symbolic MDS, a dissimilarity is not just a value but can represent an interval or even a histogram. Here, we present an overview of developments for symbolic MDS. We discuss how interval dissimilarities they can be represented by (concentric) circles or rectangles, how replications can be represented by a three-way MDS version, and show how nested intervals of distances can be obtained for representing histogram dissimilarities. The various models are illustrated by empirical examples.

Suggested Citation

  • Groenen, P.J.F. & Terada, Y., 2015. "Symbolic Multidimensional Scaling," Econometric Institute Research Papers EI 2015-15, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:78189
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    References listed on IDEAS

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    1. Groenen, P.J.F. & Winsberg, S. & Rodriguez, O. & Diday, E., 2006. "I-Scal: Multidimensional scaling of interval dissimilarities," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 360-378, November.
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    Cited by:

    1. Pełka Marcin, 2019. "Assessment of the Development of the European Oecd Countries with the Application of Linear Ordering and Ensemble Clustering of Symbolic Data," Folia Oeconomica Stetinensia, Sciendo, vol. 19(2), pages 117-133, December.

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    Keywords

    MDS; Multidimensional Scaling;

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