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Some complex geographic events are associated with multiple point locations. Such events include, but are not limited to, those describing linkages between and among places. The term multi-location event is used in the paper to refer to these geographical phenomena. Through formalization of the multi-location event problem, this paper situates the analysis of multi-location events within the broad context of point pattern analysis techniques. Two alternative approaches (vector autocorrelation analysis and cluster correspondence analysis) to the spatial dependence of paired-location events (i.e., two-location events) are explored, with a discussion of their appropriateness to general multi-location event problems. The research proposes a framework of cluster correspondence analysis for the detection of local non-stationarities in the spatial process generating multi-location events. A new algorithm for local analysis of cluster correspondence is proposed. It is implemented on a large-scale dataset of vehicle theft and recovery location pairs in Buffalo, New York. [ABSTRACT FROM AUTHOR]