A Direct Nondimensional Clustering Method for Binary Data

A new clustering method for binary data is proposed. The method is based on the new concept of homogeneity within a set of two or more operational taxonomic units. It should entirely replace the previous procedure of calculating a similarity coefficient, in which the results need to be worked out by a second, logically entirely different, method of cluster analysis. Homogeneity in this sense may be considered as a generalized measure of similarity. Moreover, a probability value is associated with every possible cluster and only statistically significant clusters are considered. Probability being a scalar quantity, the method allows two-dimensional graphic representation of the results without loss or distortion of information as in the methods previously proposed.