Cluster Detection in Point Event Data having Tendency Towards Spatially Repetitive Events

The analysis of point event patterns in geography, ecology and epidemiology have a long tradition (e.g. Snow, 1855; Clark & Evans, 1954; Harvey, 1966; Mantel, 1967; Cliff & Ord, 1981). The patterns detected are usually broadly classified as random, uniform or clustered. Whilst spatial randomness has traditionally been assumed to have no underlying process of interest, Phillips (1999) has pointed out that such apparent randomness may be attributable to chaotic deterministic patterns. For spatial uniformity a space-filling, mutual exclusion process can be hypothesised. Nevertheless, it is clustered patterns that raise the strongest interest and hypotheses for underlying processes. Thus cluster detection lies at the heart of spatial data mining (Murray & Estivill-Castro, 1998; Openshaw, 1998; Murray, 2000; Miller & Han, 2001).