A spatiotemporal bayesian hierarchical approach to investigating patterns of confidence in the police at the neighbourhood level

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Title: A spatiotemporal bayesian hierarchical approach to investigating patterns of confidence in the police at the neighbourhood level
Authors: Williams, D
Haworth, J
Blangiardo, MAG
Cheng, T
Item Type: Journal Article
Abstract: Public confidence in the police is crucial to effective policing. Improving understanding of public confidence at the local l evel will better enable the police to conduct proactive confidence interventions to meet the concerns of local communities. Conventional approaches do not consider that public confidence varies across geographic space as well as in time. Neighbourhood leve l approaches to modelling public confidence in the police are hampered by the small number problem and the resulting instability in the estimates and uncertainty in the results. This research illustrates a spatiotemporal Bayesian approach for estimating an d forecasting public confidence at the neighbourhood level and we use it to examine trends in public confidence in the police in London, UK, for Q2 2006 to Q3 2013. Our approach overcomes the limitations of the small number problem and specifically , we inv estigate the effect of the spatiotemporal representation structure chosen on the estimates of public confidence produced. We then investigate the use of the model for forecasting by producing one - step ahead forecasts of the final third of the time - series . The results are compared with the forecasts from traditional time - series forecasting methods like naïve, exponential smoothing, ARIMA, STARIMA and others. A model with spatially structured and unstructured random effects as well as a normally distributed s patiotemporal interaction term was the most parsimonious and produced the most realistic estimates. It also provided the best forecasts at the London - wide, Borough and neighbourhood level.
Issue Date: 1-Jan-2019
Date of Acceptance: 20-Jan-2018
URI: http://hdl.handle.net/10044/1/56651
ISSN: 0016-7363
Publisher: Wiley
Journal / Book Title: Geographical Analysis
Keywords: 0406 Physical Geography And Environmental Geoscience
1604 Human Geography
0909 Geomatic Engineering
Geography
Publication Status: Accepted
Appears in Collections:Faculty of Medicine
Epidemiology, Public Health and Primary Care



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