Abstract
Suppose you had a map of the locations of several towns. It would be a simple matter to construct a table (or matrix) of distances between them. Now consider the reverse problem, where you are given the matrix of distances between the towns and are asked to reproduce the map. Geometric techniques are available for this purpose, but considerably more effort would be needed. Essentially, MDS is a method for solving this reverse problem. However, typical applications of MDS are more complex than this simple problem would suggest. Firstly, data usually contain error or noise. Secondly, it is seldom known in advance whether a two-dimensional map will suffice or whether a map using three, four or even more dimensions is required.
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Aljandali, A. (2017). Multidimension Scaling (MDS). In: Multivariate Methods and Forecasting with IBM® SPSS® Statistics. Statistics and Econometrics for Finance. Springer, Cham. https://doi.org/10.1007/978-3-319-56481-4_7
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DOI: https://doi.org/10.1007/978-3-319-56481-4_7
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