An Empirical Comparison of Three Ordination Techniques in Numerical Taxonomy

Abstract

This study reports on comparisons of Kruskal's nonmetric multidimensional scaling analysis, principal components analysis, and Gower's principal coordinates analysis. Nine different sets of data were used. It was found that nonmetric scaling gave better results (as measured by the correlation between the distances in the k-dimensional configuration and the original distances). It was also found that principal coordinates analysis gave a better fit than principal components analysis when missing values were present.