Abstract

In a bivariate data set it is easy to represent clusters, e.g. by manually circling them or separating them by lines. But many data sets have more than two variables, or they come in the form of inter-object dissimilarities. There exist methods to partition such a data set into clusters, but the resulting partition is not visual by itself. In this paper we construct a new graphical display called CLUSPLOT, in which the objects are represented as points in a bivariate plot and the clusters as ellipses of various sizes and shapes. The algorithm is implemented as an S-PLUS function. Several options are available, e.g. labelling of objects and clusters, drawing lines connecting clusters, and the use of color. We illustrate this new tool with several examples.

Keywords

Cluster analysis, Discriminant analysis, Multidimensional scaling, Principal components, Statistical software.