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Monitoring murder crime in Namibia using Bayesian space-time models

Monitoring murder crime in Namibia using Bayesian space-time models
Monitoring murder crime in Namibia using Bayesian space-time models
This paper focuses on the analysis of murder in Namibia using Bayesian spatial smoothing approach with temporal trends. The analysis was based on the reported cases from 13 regions of Namibia for the period 2002–2006 complemented with regional population sizes. The evaluated random effects include space-time structured heterogeneity measuring the effect of regional clustering, unstructured heterogeneity, time, space and time interaction and population density. The model consists of carefully chosen prior and hyper-prior distributions for parameters and hyper-parameters, with inference conducted using Gibbs sampling algorithm and sensitivity test for model validation. The posterior mean estimate of the parameters from the model using DIC as model selection criteria show that most of the variation in the relative risk of murder is due to regional clustering, while the effect of population density and time was insignificant. The sensitivity analysis indicates that both intrinsic and Laplace CAR prior can be adopted as prior distribution for the space-time heterogeneity. In addition, the relative risk map show risk structure of increasing north-south gradient, pointing to low risk in northern regions of Namibia, while Karas and Khomas region experience long-term increase in murder risk.
1687-952X
194018-[11pp]
Neema, Isak
13977c79-9f5d-43db-b8ca-7f86188461a9
Boehning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Neema, Isak
13977c79-9f5d-43db-b8ca-7f86188461a9
Boehning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1

Neema, Isak and Boehning, Dankmar (2012) Monitoring murder crime in Namibia using Bayesian space-time models. Journal of Probability and Statistics, 2012 (194018), 194018-[11pp]. (doi:10.1155/2012/194018).

Record type: Article

Abstract

This paper focuses on the analysis of murder in Namibia using Bayesian spatial smoothing approach with temporal trends. The analysis was based on the reported cases from 13 regions of Namibia for the period 2002–2006 complemented with regional population sizes. The evaluated random effects include space-time structured heterogeneity measuring the effect of regional clustering, unstructured heterogeneity, time, space and time interaction and population density. The model consists of carefully chosen prior and hyper-prior distributions for parameters and hyper-parameters, with inference conducted using Gibbs sampling algorithm and sensitivity test for model validation. The posterior mean estimate of the parameters from the model using DIC as model selection criteria show that most of the variation in the relative risk of murder is due to regional clustering, while the effect of population density and time was insignificant. The sensitivity analysis indicates that both intrinsic and Laplace CAR prior can be adopted as prior distribution for the space-time heterogeneity. In addition, the relative risk map show risk structure of increasing north-south gradient, pointing to low risk in northern regions of Namibia, while Karas and Khomas region experience long-term increase in murder risk.

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More information

Published date: 2012
Organisations: Statistics, Statistical Sciences Research Institute, Primary Care & Population Sciences

Identifiers

Local EPrints ID: 341786
URI: http://eprints.soton.ac.uk/id/eprint/341786
ISSN: 1687-952X
PURE UUID: 9088b4f6-5d1f-418e-87e5-034634306e8a
ORCID for Dankmar Boehning: ORCID iD orcid.org/0000-0003-0638-7106

Catalogue record

Date deposited: 03 Aug 2012 16:01
Last modified: 09 Nov 2021 03:24

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Author: Isak Neema

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