A Statistical Method for Detecting Significant Temporal Hotspots Using LISA Statistics

This work presents a method for detecting statistically significant temporal hotspots, i.e. the date and time of events, which is useful for improved planning of response activities. Temporal hotspots are calculated using Local Indicators of Spatial Association (LISA) statistics. The temporal data is in a 7x24 matrix that represents a temporal resolution of weekdays and hours-in-the-day. Swedish residential burglary events are used in this work for testing the temporal hotspot detection approach. Although, the presented method is also useful for other events as long as they contain temporal information, e.g. attack attempts recorded by intrusion detection systems. By using the method for detecting significant temporal hotspots it is possible for domain-experts to gain knowledge about the temporal distribution of the events, and also to learn at which times mitigating actions could be implemented.