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Journal of Probability and Statistics
Volume 2012 (2012), Article ID 194018, 12 pages
Research Article

Monitoring Murder Crime in Namibia Using Bayesian Space-Time Models

1Department of Statistics, University of Namibia, P.O. Box 13301, Windhoek, Namibia
2School of Mathematics and Southampton Statistical Sciences Research Institute, University of Southampton, Southampton SO17 1BJ, UK

Received 4 January 2012; Revised 25 April 2012; Accepted 9 May 2012

Academic Editor: Shein-chung Chow

Copyright © 2012 Isak Neema and Dankmar Böhning. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. Republic of Namibia 2001 Population and Housing Census, National Report, 2003.
  2. United Nation Interregional Crime and Justice Research Institute, “Crime in Southern Africa towards the year 2000,” Tech. Rep. 7/8, 1997. View at Google Scholar
  3. M. Schönteich, “South Africas position in Africas crime rankings,” African Security Review, vol 9, no. 4, 2000.
  4. 2007, http://www.nationmaster.com/.
  5. A. Verma and S. K. Lodha, “A topological representation of the criminal event,” Western Criminology Review, vol. 3, no. 2, 2002.
  6. I. Neema and D. Böhning, “Improved methods for surveying and monitoring crimes through the likelihood based cluster analysis,” International Journal of Criminology and Sociological Theory, vol. 3, no. 2, pp. 477–495, 2010. View at Google Scholar
  7. J. Besag, J. York, and A. Mollié, “Bayesian image restoration, with two applications in spatial statistics,” Annals of the Institute of Statistical Mathematics, vol. 43, no. 1, pp. 1–59, 1991. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  8. J. Aguero-Valverde and P. P. Jovanis, “Spatial analysis of fatal and injury crashes in Pennsylvania,” Accident Analysis and Prevention, vol. 38, pp. 618–625, 2006. View at Google Scholar
  9. A. B. Lawson, A. Biggeri, D. Böhning, E. Lesaffre, J. F. Viel, and R. Bertollini, Disease Mapping and Risk Assessment for Public Health, John Wiley and Sons, New York, NY, USA, 1999.
  10. A. B. Lawson, W. J. Browne, and C. L. Vidal Rodeiro, Disease Mapping with WinBUGS and MLwiN, John Wiley and Sons, Chichester, UK, 2003.
  11. A. B. Lawson, Bayesian Disease Mapping, CRC Press, London, UK, 2009.
  12. L. Fahrmeir and S. Lang, “Bayesian inference for generalized additive mixed models based on Markov random field priors,” Journal of the Royal Statistical Society C, vol. 50, no. 2, pp. 201–220, 2001. View at Publisher · View at Google Scholar
  13. S. Lang, E. Fronk, and L. Fahrmeir, “Function estimation with locally adaptive dynamic models,” Sondertorschungsbereich 386, paper 263.
  14. L. Zuccolo, M. M. Maule, and D. Gregori, “An epidemiological application of a Bayesian nonparametric smoother based on a GLMM with an autoregressive error component,” Metodoloski Zvezki, vol. 2, no. 2, pp. 259–270, 2005. View at Google Scholar
  15. B. Kedem and K. Fokianos, Regression Models for Time Series Analysis, Wiley-Interscience, New York, NY, USA, 2002. View at Publisher · View at Google Scholar
  16. A. Gelman and D. B. Rubin, “Inference from iterative simulation using multiple sequences,” Statistical Sciences, vol. 7, no. 4, pp. 457–472, 1992. View at Google Scholar
  17. S. P. Brooks and A. Gelman, “General methods for monitoring convergence of iterative simulations,” Journal of Computational and Graphical Statistics, vol. 7, no. 4, pp. 434–455, 1998. View at Publisher · View at Google Scholar
  18. I. Ntzoufras, Bayesian Modeling using WinBUGS, John Wiley and Sons, Hoboken, NJ, USA, 2009.
  19. D. J. Spiegelhalter, N. G. Best, B. P. Carlin, and A. van der Linde, “Bayesian measures of model complexity and fit,” Journal of the Royal Statistical Society B, vol. 64, no. 4, pp. 583–639, 2002. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  20. N. Best and S. Richardson, “Introduction to Bayesian analysis using WinBUGS,” Introduction to Bayesian Analysis and WinBUGS course, Imperial College, January 2009.
  21. P. Congdon, Applied Bayesian Modelling, John Wiley & Sons, Chichester, UK, 2003. View at Publisher · View at Google Scholar
  22. A. Gelman, J. B. Carlin, H. S. Stern, and D. B. Rubin, Bayesian Data Analysis. Text in Statistical Science, Chapman and Hall/CRC, New York, NY, USA, 2nd edition, 2004.
  23. J. Klipin and K. Harrison, The Future for Policing and Crime Prevention in SADC, International Crime Prevention Centre, Montreal, Canada, 2003.