Our method was tested on several different simulated maps partitioned into different numbers of components (ranging from 2 to 4). The relative risks for each component were chosen as 3 sigma, (3 sigma and 0 sigma, corresponding respectively to high-, low-and neutral-risk spots. We evaluate the power of detection and matching (a measure of overlap between the real and detected partitions) for each set of 1000 Monte Carlo replications. The average power varies from 0.686 to 0.803, and matching varies from 0.566 to 0.850 for the several sets of simulations.