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Introduction to crime forecasting

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  • Gorr, Wilpen
  • Harries, Richard

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  • Gorr, Wilpen & Harries, Richard, 2003. "Introduction to crime forecasting," International Journal of Forecasting, Elsevier, vol. 19(4), pages 551-555.
    • Handle: RePEc:eee:intfor:v:19:y:2003:i:4:p:551-555
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    References listed on IDEAS

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    1. Deadman, Derek, 2003. "Forecasting residential burglary," International Journal of Forecasting, Elsevier, vol. 19(4), pages 567-578.
    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. 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.
    4. Felson, Marcus & Poulsen, Erika, 2003. "Simple indicators of crime by time of day," International Journal of Forecasting, Elsevier, vol. 19(4), pages 595-601.
    5. Harries, Richard, 2003. "Modelling and predicting recorded property crime trends in England and Wales--a retrospective," International Journal of Forecasting, Elsevier, vol. 19(4), pages 557-566.
    6. Liu, Hua & Brown, Donald E., 2003. "Criminal incident prediction using a point-pattern-based density model," International Journal of Forecasting, Elsevier, vol. 19(4), pages 603-622.
    7. Gorr, Wilpen & Olligschlaeger, Andreas & Thompson, Yvonne, 2003. "Short-term forecasting of crime," International Journal of Forecasting, Elsevier, vol. 19(4), pages 579-594.
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    Cited by:

    1. Rostami-Tabar, Bahman & Ali, Mohammad M. & Hong, Tao & Hyndman, Rob J. & Porter, Michael D. & Syntetos, Aris, 2022. "Forecasting for social good," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1245-1257.
    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. Roman Liesenfeld & Jean‐François Richard & Jan Vogler, 2017. "Likelihood‐Based Inference and Prediction in Spatio‐Temporal Panel Count Models for Urban Crimes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(3), pages 600-620, April.
    4. de Blasio, Guido & D'Ignazio, Alessio & Letta, Marco, 2022. "Gotham city. Predicting ‘corrupted’ municipalities with machine learning," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    5. Neill, Daniel B., 2009. "Expectation-based scan statistics for monitoring spatial time series data," International Journal of Forecasting, Elsevier, vol. 25(3), pages 498-517, July.

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