An Offenders-Offenses Shared Component Spatial Model for Identifying Shared and Specific Hotspots of Offenders and Offenses: A Case Study of Juvenile Delinquents and Violent Crimes in the Greater Toronto Area

Abstract Objectives We attempted to apply the Bayesian shared component spatial modeling (SCSM) for identification of hotspots from two (offenders and offenses) instead one or variables developed three risk surfaces (1) common by both offenders offenses; (2) specific offenders, (3) offenses. Methods applied SCSM examine joint distributions juvenile delinquents (offenders) violent crime (offenses) in York Region Greater Toronto Area at dissemination area level. The autocorrelation, overdispersion, latent covariates were adjusted spatially structured unstructured random effect terms model. mapped posterior means estimated risks identifying types hotspots. Results suggest that about 50% 25% relative crimes, respectively, could be explained attributed 48% 24% total variations respectively. Contrastingly, influenced 3% 51% crimes. Conclusions presented this study identifies crime. method can other kinds offenses provide new insights into clusters high are due only.