Predicting public confidence in the police with spatiotemporal Bayesian hierarchical modelling.

Public confidence in the police is crucial to effective policing. Estimating and predicting public confidence at the local level will better enable the police to conduct proactive confidence interventions to meet the concerns of the community. This work represents the first application of Bayesian spatiotemporal modelling to estimation and prediction of public confidence in the police at the local level. Three models of increasing spatiotemporal complexity were fitted by Markov chain Monte Carlo simulation using free software package WinBUGS. Public confidence was successfully predicted at the local level using a spatiotemporal model with an inseparable interaction structure.