Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis
 J. B. Kruskal
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Multidimensional scaling is the problem of representingn objects geometrically byn points, so that the interpoint distances correspond in some sense to experimental dissimilarities between objects. In just what sense distances and dissimilarities should correspond has been left rather vague in most approaches, thus leaving these approaches logically incomplete. Our fundamental hypothesis is that dissimilarities and distances are monotonically related. We define a quantitative, intuitively satisfying measure of goodness of fit to this hypothesis. Our technique of multidimensional scaling is to compute that configuration of points which optimizes the goodness of fit. A practical computer program for doing the calculations is described in a companion paper.
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 Title
 Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis
 Journal

Psychometrika
Volume 29, Issue 1 , pp 127
 Cover Date
 19640301
 DOI
 10.1007/BF02289565
 Print ISSN
 00333123
 Online ISSN
 18600980
 Publisher
 SpringerVerlag
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 Authors

 J. B. Kruskal ^{(1)}
 Author Affiliations

 1. Bell Telephone Laboratories, Murray Hill, N. J.