Sequential data assimilation for 1D self-exciting processes with application to urban crime data
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DOI: 10.1016/j.csda.2018.06.014
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References listed on IDEAS
- José Da Fonseca & Riadh Zaatour, 2014. "Hawkes Process: Fast Calibration, Application to Trade Clustering, and Diffusive Limit," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(6), pages 548-579, June.
- G. O. Mohler & M. B. Short & Sean Malinowski & Mark Johnson & G. E. Tita & Andrea L. Bertozzi & P. J. Brantingham, 2015. "Randomized Controlled Field Trials of Predictive Policing," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1399-1411, December.
- Mohler, G. O. & Short, M. B. & Brantingham, P. J. & Schoenberg, F. P. & Tita, G. E., 2011. "Self-Exciting Point Process Modeling of Crime," Journal of the American Statistical Association, American Statistical Association, vol. 106(493), pages 100-108.
- Taddy, Matthew A., 2010. "Autoregressive Mixture Models for Dynamic Spatial Poisson Processes: Application to Tracking Intensity of Violent Crime," Journal of the American Statistical Association, American Statistical Association, vol. 105(492), pages 1403-1417.
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Cited by:
- Santitissadeekorn, Naratip & Lloyd, David J.B. & Short, Martin B. & Delahaies, Sylvain, 2020. "Approximate filtering of conditional intensity process for Poisson count data: Application to urban crime," Computational Statistics & Data Analysis, Elsevier, vol. 144(C).
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Keywords
Nonlinear filtering; Hawkes process; Joint state-parameter estimation; Count data; Particle filtering; Ensemble Kalman filter;All these keywords.
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