A Mathematical Framework for Analyzing and Representing Recur and Near-recur Results in Burglary Crime Data

(Received on: 18-06-11; Accepted on: 30-06-11) -----------------------------------------------------------------------------------------------------------------------------------------------ABSTRACT In this paper develop a mathematical framework aimed at analyzing repeat and near repeat effects in crime data. Parsing burglary data from Promoter Apartments, Chennai according to different counting methods, in this paper determine the probability distribution functions for the time intervals between repeat offenses. This paper compare these observed distributions to theoretically derived distributions in which the repeat effects are due exclusively to persistent risk heterogeneity. We find that risk heterogeneity alone cannot explain the observed distributions, while a form of event belief can. Using this information, we model repeat victimization as a series of random events, the likelihood of which changes each time an offense occurs. We are able to estimate typical time scales for repeat burglary events in Promoter Apartments by fitting our data to this model. Computer simulations of this model using these observed parameters agree with the empirical data.