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

Williams, D; Haworth, J; Cheng, T; (2016) Predicting public confidence in the police with spatiotemporal Bayesian hierarchical modelling. In: Proceedings of the 24th GIS Research UK (GISRUK) Conference. GIS Research UK (GISRUK): London, UK. Green open access

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Abstract

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.

Type: Proceedings paper
Title: Predicting public confidence in the police with spatiotemporal Bayesian hierarchical modelling.
Event: The 24th GIS Research UK (GISRUK) Conference (GISRUK2016)
Location: London, UK
Dates: 30 March 2017 - 01 April 2017
Open access status: An open access version is available from UCL Discovery
Publisher version: http://www.gre.ac.uk/ach/services/events/gisruk201...
Language: English
Keywords: Spatiotemporal, Bayesian hierarchical model, public confidence, policing, prediction
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1544033
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