Exploring violent and property crime geographically: A comparison of the accuracy and precision of kernel density estimation and simple count

Abstract

There are multiple geographical crime prediction techniques to use and comparing different prediction techniques therefore becomes important. In the current study we compared the accuracy (Predictive Accuracy Index) and precision (Recapture Rate Index) of simply counting crimes: Simple Count with Kernel Density Estimation in the prediction of where people are reported to commit violent crimes (assault and robbery) and property crimes (residential burglary, property damage, theft, vehicle theft and arson), geographically. These predictions were done using a different number of years into the future and based on a different number of years combined to do the crime prediction, in a large Swedish municipality. The Simple Count technique performed quite well in comparison to simple Kernel Density Estimation no matter what crime was being predicted, making us conclude that it may not be necessary to use the more complex method of Kernel Density Estimation to predict where people are reported to commit crime geographically.