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Modern Multidimensional Scaling Theory and Applications (Springer Series in
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Modern Multidimensional Scaling Theory and Applications (Springer Series in Statistics) Hardcover - 1996 - 1st Edition

by Borg, Ingwer.; Patrick Groenen


From the publisher

This text provides a comprehensive treatment of multidimensional scaling (MDS), a statistical technique used to anlayze the structure of similarity or dissimilarity data in multidimensional space. Such data are widespread, for example, intercorrelations of attitude items, direct ratings of similarity on choice objects, or trade indices for a set of countries. MDS models such data as distances among points in a geometric space of low dimensionality; this makes complex data sets accessible to visual exploration and thus aids in seeing structures not obvious from the numbers. Other uses of MDS interpret the geometry and, in particular, the distance function as a psychological composition rule.

First line

Multidimensional scaling (MDS) is a method that represents measurements of similarity (or dissimilarity) among pairs of objects as distances between points of a low-dimensional multidimensional space.

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  • Title Modern Multidimensional Scaling Theory and Applications (Springer Series in Statistics)
  • Author Borg, Ingwer.; Patrick Groenen
  • Binding Hardcover
  • Edition number 1st
  • Edition 1
  • Pages 496
  • Publisher Springer, New York, NY
  • Date December 20, 1996
  • ISBN 9780387948454
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Modern Multidimensional Scaling: Theory and Applications (Springer Series in Statistics)
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Modern Multidimensional Scaling: Theory and Applications (Springer Series in Statistics)

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Modern Multidimensional Scaling: Theory and Applications (Springer Series in Statistics)
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Modern Multidimensional Scaling: Theory and Applications (Springer Series in Statistics)

by Ingwer Borg; Patrick Groenen

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Modern Multidimensional Scaling: Theory and Applications (Springer Series in Statistics)

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