1. A method for detecting clusters comprising: receiving input data on occurrences of a phenomenon at locations and times and data on characteristics of the locations and times; determining actual occurrences of the phenomenon at the three-dimensional space-time points according to the input data; determining expected occurrences in the absence of any clustering of the phenomenon at the points according to the characteristics of the occurrences using a domain dependent model for the phenomenon; selecting a convex container shape for determining a cluster in the input data; and determining a solution represented as a set of points that conforms to the selected convex container shape for a cluster with a desirable strength.