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This paper introduces two new methods for the exploratory analysis of the spatial and temporal dynamics of residential burglary patterns. The first is a conditional spatial Markov chain which considers the extent to which a location's probability of experiencing a residential burglary in a future period is related to the prevalence of residential burglaries in its surrounding neighborhood in an initial period. The second measure extends this conditional perspective to examine the joint evolution of residential burglary in a location and its surrounding neighborhood. These methods are applied to a case study of residential burglary patterns in Mesa, Arizona over the period October 2005 through December 2009. Strong patterns of spatial clustering of burglary activity are present in each year, and this clustering is found to have an important influence on both the conditional and joint evolution of burglary activity across space and time. [ABSTRACT FROM AUTHOR]