A new method of detecting clustering in the data

The present study describes a new method of detecting clustering in a data set. For each object in the data, the distances to all other objects are calculated, sorted in ascending order, normalized and plotted as so called distance curves. n curves are obtained for data containing n objects. The shape of these curves, together with their distribution, give information on clustering of the data and possible distribution. It is also possible to evaluate the populations of the clusters. The method, however, fails for very close clusters and for elongated clusters whose separation distance is much smaller than the range of their greatest variability. The method is explained using simulated and real data.