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Short-term forecasting of crime

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  • Gorr, Wilpen
  • Olligschlaeger, Andreas
  • Thompson, Yvonne
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    File URL: http://www.sciencedirect.com/science/article/pii/S0169-2070(03)00092-X
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    Article provided by Elsevier in its journal International Journal of Forecasting.

    Volume (Year): 19 (2003)
    Issue (Month): 4 ()
    Pages: 579-594

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    Handle: RePEc:eee:intfor:v:19:y:2003:i:4:p:579-594
    Contact details of provider: Web page: http://www.elsevier.com/locate/ijforecast

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    1. A. Hirschfield & K.J. Bowers, 1997. "The Effect of Social Cohesion on Levels of Recorded Crime in Disadvantaged Areas," Urban Studies, Urban Studies Journal Limited, vol. 34(8), pages 1275-1295, July.
    2. Bunn, Derek W. & Vassilopoulos, Angelos I., 1999. "Comparison of seasonal estimation methods in multi-item short-term forecasting," International Journal of Forecasting, Elsevier, vol. 15(4), pages 431-443, October.
    3. George Duncan & Wilpen Gorr & Janusz Szczypula, 1993. "Bayesian Forecasting for Seemingly Unrelated Time Series: Application to Local Government Revenue Forecasting," Management Science, INFORMS, vol. 39(3), pages 275-293, March.
    4. Armstrong, J. Scott & Collopy, Fred, 1992. "Error measures for generalizing about forecasting methods: Empirical comparisons," International Journal of Forecasting, Elsevier, vol. 8(1), pages 69-80, June.
    5. Withycombe, Richard, 1989. "Forecasting with combined seasonal indices," International Journal of Forecasting, Elsevier, vol. 5(4), pages 547-552.
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    Cited by:

    1. Gorr, Wilpen & Harries, Richard, 2003. "Introduction to crime forecasting," International Journal of Forecasting, Elsevier, vol. 19(4), pages 551-555.
    2. Jean-François Richard, 2015. "Likelihood Based Inference and Prediction in Spatio-temporal Panel Count Models for Urban Crimes," Working Paper 5657, Department of Economics, University of Pittsburgh.
    3. Chen, Huijing & Boylan, John E., 2008. "Empirical evidence on individual, group and shrinkage seasonal indices," International Journal of Forecasting, Elsevier, vol. 24(3), pages 525-534.
    4. Gorr, Wilpen L., 2009. "Forecast accuracy measures for exception reporting using receiver operating characteristic curves," International Journal of Forecasting, Elsevier, vol. 25(1), pages 48-61.
    5. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2014. "Golden Rule of Forecasting: Be conservative," MPRA Paper 53579, University Library of Munich, Germany.
    6. Shoesmith, Gary L., 2013. "Space–time autoregressive models and forecasting national, regional and state crime rates," International Journal of Forecasting, Elsevier, vol. 29(1), pages 191-201.
    7. Cohen, Jacqueline & Garman, Samuel & Gorr, Wilpen, 2009. "Empirical calibration of time series monitoring methods using receiver operating characteristic curves," International Journal of Forecasting, Elsevier, vol. 25(3), pages 484-497, July.
    8. Vogler, Jan & Liesenfeld, Roman & Richard, Jean-Francois, 2015. "Likelihood based inference and prediction in spatio-temporal panel count models for urban crimes," Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113131, Verein für Socialpolitik / German Economic Association.
    9. Camacho-Collados, M. & Liberatore, F. & Angulo, J.M., 2015. "A multi-criteria Police Districting Problem for the efficient and effective design of patrol sector," European Journal of Operational Research, Elsevier, vol. 246(2), pages 674-684.
    10. Corcoran, Jonathan J. & Wilson, Ian D. & Ware, J. Andrew, 2003. "Predicting the geo-temporal variations of crime and disorder," International Journal of Forecasting, Elsevier, vol. 19(4), pages 623-634.
    11. Armstrong, J. Scott, 2006. "Findings from evidence-based forecasting: Methods for reducing forecast error," International Journal of Forecasting, Elsevier, vol. 22(3), pages 583-598.
    12. Huddleston, Samuel H. & Porter, John H. & Brown, Donald E., 2015. "Improving forecasts for noisy geographic time series," Journal of Business Research, Elsevier, vol. 68(8), pages 1810-1818.

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