Home // International Journal On Advances in Security, volume 11, numbers 3 and 4, 2018 // View article

Crime forecasting in small city blocks using a general additive spatio-temporal model

Authors:
Maria Mahfoud
Sandjai Bhulai
Rob van der Mei

Keywords: Predictive analytics; forecasting; spatio-temporal modeling; residential burglary.

Abstract:
Spatio-temporal modeling is widely recognized as a promising means for predicting crime patterns. Despite their enormous potential, the available methods are still in their infancy. A lot of research focuses on crime hotspot detection and geographic crime clusters, while a systematic approach to include the temporal component of the underlying crime distributions is still under-researched. In this paper, we gain further insight in predictive crime modeling by including a spatio-temporal interaction component in the prediction of residential burglaries. Based on an extensive dataset, we show that including additive space-time interactions leads to significantly better predictions.

Pages: 214 to 222

Copyright: Copyright (c) to authors, 2018. Used with permission.

Publication date: December 30, 2018

Published in: journal

ISSN: 1942-2636