Abstract

Highly clustered event sequences are observed in certain types of crime data, such as burglary and gang violence, due to crime-specific patterns of criminal behavior. Similar clustering patterns are observed by seismologists, as earthquakes are well known to increase the risk of subsequent earthquakes, or aftershocks, near the location of an initial event. Space–time clustering is modeled in seismology by self-exciting point processes and the focus of this article is to show that these methods are well suited for criminological applications. We first review self-exciting point processes in the context of seismology. Next, using residential burglary data provided by the Los Angeles Police Department, we…

Citation impact

871
total citations
FWCI
46.04
Percentile
100%
References
20
Citations per year

Authors

5

Topics & keywords

Keywords
  • Point process
  • Context (archaeology)
  • Cluster analysis
  • Event (particle physics)
  • Point (geometry)
  • Process (computing)
  • Aftershock
  • Computer science
UN Sustainable Development Goals
  • Peace, Justice and strong institutions
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