Analyzing Car Thefts and Recoveries with Connections to Modeling Origin-Destination Point Patterns

Understand

For a given region, we have a dataset composed of car theft locations along with a linked dataset of recovery locations which, due to partial recovery, is a relatively small subset of the set of theft locations.

• For an investigator seeking to understand the behavior of car thefts and recoveries in the region, several questions are addressed.
• Viewing the set of theft locations as a point pattern, can we propose useful models to explain the pattern? What types of predictive models can be built to learn about recovery location given theft location? Can the dependence between theft locations and recovery locations be formalized? Can the flow between theft sites and recovery sites be captured? Origin-destination modeling offers a natural framework for such problems.
• However, here the data is not for areal units but rather is a pair of point patterns, with the recovery point pattern only partially observed.