Abstract
Spatial clustering analysis has become common in many fields of research, and is most commonly used in epidemiology and criminology applications. Knox (1989, p.17) defines a spatial cluster as, ‘a geographically bounded group of occurrences of sufficient size and concentration to be unlikely to have occurred by chance.’ This is a useful operational definition, but there are very few situations when phenomena are expected to be distributed randomly in space. In most cases an implicit assumption in spatial cluster analysis is that the researcher has accounted for all the factors known to influence the variable of study. This would lead to an examination of residual spatial variation in a spatial modeling exercise. Spatial clustering analysis is carried out on raw variables or rates when there are no a priori hypotheses regarding the process.
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Aldstadt, J. (2010). Spatial Clustering. In: Fischer, M., Getis, A. (eds) Handbook of Applied Spatial Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03647-7_15
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DOI: https://doi.org/10.1007/978-3-642-03647-7_15
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