Abstract
A methodology is developed for constructing linear biplots for a class of nonmetric multidimensional scaling methods for multivariate data. The nonlinear transformations of nonmetric scaling manifest themselves in irregularly spaced calibration markers. Two approaches are examined, one based on Procrustean embedding, the other on a modification of the popular regression method. The widespread use of an unmodified regression method in association with nonlinear transformations is questioned. An example is given. The methodology presented here could potentially be developed to give an optimal represention of a matrix in fewer geometric dimensions than its rank.
Similar content being viewed by others
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Gower, J., Meulman, J. & Arnold, G. Nonmetric Linear Biplots. J. of Classification 16, 181–196 (1999). https://doi.org/10.1007/s003579900053
Published:
Issue Date:
DOI: https://doi.org/10.1007/s003579900053