Abstract
A new method is proposed for identifying clusters in spatial point processes. It relies on a specific ordering of events and the definition of area spacings which have the same distribution as one-dimensional spacings. Then the spatial clusters are detected using a scan statistic adapted to the analysis of one-dimensional point processes. This flexible spatial scan test seems to be very powerful against any arbitrarily-shaped cluster alternative. These results have applications in epidemiological studies of rare diseases.
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