Abstract
A method for multidimensional scaling that is highly resistant to the effects of outliers is described. To illustrate the efficacy of the procedure, some Monte Carlo simulation results are presented. The method is shown to perform well when outliers are present, even in relatively large numbers, and also to perform comparably to other approaches when no outliers are present.
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This research was supported by Grant A8351 from the Natural Sciences and Engineering Research Council of Canada to Ian Spence.
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Spence, I., Lewandowsky, S. Robust multidimensional scaling. Psychometrika 54, 501–513 (1989). https://doi.org/10.1007/BF02294632
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DOI: https://doi.org/10.1007/BF02294632