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Self-Exciting Point Process Modeling of Crime

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Cited by:

  1. Nishio, Kazuki & Hoshino, Takahiro, 2022. "Joint modeling of effects of customer tier program on customer purchase duration and purchase amount," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
  2. Kajita, Mami & Kajita, Seiji, 2020. "Crime prediction by data-driven Green’s function method," International Journal of Forecasting, Elsevier, vol. 36(2), pages 480-488.
  3. Raimundo, Silvia Martorano & Yang, Hyun Mo & Rubio, Felipe Alves & Greenhalgh, David & Massad, Eduardo, 2023. "Modeling criminal careers of different levels of offence," Applied Mathematics and Computation, Elsevier, vol. 453(C).
  4. Mateo Dulce Rubio, 2019. "Predicting criminal behavior with Lévy flights using real data from Bogotá," Documentos CEDE 17198, Universidad de los Andes, Facultad de Economía, CEDE.
  5. Alex Reinhart & Joel Greenhouse, 2018. "Self‐exciting point processes with spatial covariates: modelling the dynamics of crime," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(5), pages 1305-1329, November.
  6. Didier Sornette & Thomas Maillart & Giacomo Ghezzi, 2014. "How Much Is the Whole Really More than the Sum of Its Parts? 1 ⊞ 1 = 2.5: Superlinear Productivity in Collective Group Actions," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-15, August.
  7. Chen, Zezhun & Dassios, Angelos, 2022. "Cluster point processes and Poisson thinning INARMA," LSE Research Online Documents on Economics 113652, London School of Economics and Political Science, LSE Library.
  8. Seppo Virtanen & Mark Girolami, 2021. "Spatio‐temporal mixed membership models for criminal activity," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1220-1244, October.
  9. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2018. "Modeling extreme risks in commodities and commodity currencies," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 108-120.
  10. Chenlong Li & Kaiyan Cui, 2024. "Multivariate Hawkes processes with spatial covariates for spatiotemporal event data analysis," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 76(4), pages 535-578, August.
  11. Briz-Redón, Álvaro & Iftimi, Adina & Montes, Francisco, 2022. "Accounting for previous events to model and predict traffic accidents at the road segment level: A study in Valencia (Spain)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 585(C).
  12. H Juliette T Unwin & Isobel Routledge & Seth Flaxman & Marian-Andrei Rizoiu & Shengjie Lai & Justin Cohen & Daniel J Weiss & Swapnil Mishra & Samir Bhatt, 2021. "Using Hawkes Processes to model imported and local malaria cases in near-elimination settings," PLOS Computational Biology, Public Library of Science, vol. 17(4), pages 1-18, April.
  13. Tata Subba Rao & Granville Tunnicliffe Wilson & Michael Eichler & Rainer Dahlhaus & Johannes Dueck, 2017. "Graphical Modeling for Multivariate Hawkes Processes with Nonparametric Link Functions," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(2), pages 225-242, March.
  14. Sobin Joseph & Shashi Jain, 2023. "A neural network based model for multi-dimensional nonlinear Hawkes processes," Papers 2303.03073, arXiv.org.
  15. David Payares-Garcia & Javier Platero & Jorge Mateu, 2023. "A Dynamic Spatio-Temporal Stochastic Modeling Approach of Emergency Calls in an Urban Context," Mathematics, MDPI, vol. 11(4), pages 1-28, February.
  16. Baichuan Yuan & Frederic P. Schoenberg & Andrea L. Bertozzi, 2021. "Fast estimation of multivariate spatiotemporal Hawkes processes and network reconstruction," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 73(6), pages 1127-1152, December.
  17. Cavaliere, Giuseppe & Lu, Ye & Rahbek, Anders & Stærk-Østergaard, Jacob, 2023. "Bootstrap inference for Hawkes and general point processes," Journal of Econometrics, Elsevier, vol. 235(1), pages 133-165.
  18. Amanda S. Hering & Sean Bair, 2014. "Characterizing spatial and chronological target selection of serial offenders," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(1), pages 123-140, January.
  19. Mohler, George, 2014. "Marked point process hotspot maps for homicide and gun crime prediction in Chicago," International Journal of Forecasting, Elsevier, vol. 30(3), pages 491-497.
  20. Eric W. Fox & Martin B. Short & Frederic P. Schoenberg & Kathryn D. Coronges & Andrea L. Bertozzi, 2016. "Modeling E-mail Networks and Inferring Leadership Using Self-Exciting Point Processes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 564-584, April.
  21. Dassios, Angelos & Zhao, Hongbiao, 2017. "A generalised contagion process with an application to credit risk," LSE Research Online Documents on Economics 68558, London School of Economics and Political Science, LSE Library.
  22. Gian Maria Campedelli & Alberto Aziani & Serena Favarin, 2020. "Exploring the Effects of COVID-19 Containment Policies on Crime: An Empirical Analysis of the Short-term Aftermath in Los Angeles," Papers 2003.11021, arXiv.org, revised Oct 2020.
  23. T. Rajala & D. J. Murrell & S. C. Olhede, 2018. "Detecting multivariate interactions in spatial point patterns with Gibbs models and variable selection," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(5), pages 1237-1273, November.
  24. Brantingham, P. Jeffrey & Carter, Jeremy & MacDonald, John & Melde, Chris & Mohler, George, 2021. "Is the recent surge in violence in American cities due to contagion?," Journal of Criminal Justice, Elsevier, vol. 76(C).
  25. Peter Boyd & James Molyneux, 2021. "Assessing the contagiousness of mass shootings with nonparametric Hawkes processes," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-18, March.
  26. Lizhen Xu & Jason A. Duan & Andrew Whinston, 2014. "Path to Purchase: A Mutually Exciting Point Process Model for Online Advertising and Conversion," Management Science, INFORMS, vol. 60(6), pages 1392-1412, June.
  27. Boswijk, H. Peter & Laeven, Roger J.A. & Yang, Xiye, 2018. "Testing for self-excitation in jumps," Journal of Econometrics, Elsevier, vol. 203(2), pages 256-266.
  28. Laurent Lesage & Madalina Deaconu & Antoine Lejay & Jorge Augusto Meira & Geoffrey Nichil & Radu State, 2022. "Hawkes processes framework with a Gamma density as excitation function: application to natural disasters for insurance," Post-Print hal-03040090, HAL.
  29. Mohammed A. A. Al-qaness & Ahmed A. Ewees & Hong Fan & Mohamed Abd Elaziz, 2020. "Optimized Forecasting Method for Weekly Influenza Confirmed Cases," IJERPH, MDPI, vol. 17(10), pages 1-12, May.
  30. Naveed Chehrazi & Thomas A. Weber, 2015. "Dynamic Valuation of Delinquent Credit-Card Accounts," Management Science, INFORMS, vol. 61(12), pages 3077-3096, December.
  31. Emmanuel Bacry & Jean-Francois Muzy, 2014. "Second order statistics characterization of Hawkes processes and non-parametric estimation," Papers 1401.0903, arXiv.org, revised Feb 2015.
  32. Philip A. White & Alan E. Gelfand, 2021. "Generalized Evolutionary Point Processes: Model Specifications and Model Comparison," Methodology and Computing in Applied Probability, Springer, vol. 23(3), pages 1001-1021, September.
  33. Chevallier, Julien, 2017. "Mean-field limit of generalized Hawkes processes," Stochastic Processes and their Applications, Elsevier, vol. 127(12), pages 3870-3912.
  34. Frederic Paik Schoenberg & Marc Hoffmann & Ryan J. Harrigan, 2019. "A recursive point process model for infectious diseases," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(5), pages 1271-1287, October.
  35. Alsenafi, Abdulaziz & Barbaro, Alethea B.T., 2018. "A convection–diffusion model for gang territoriality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 765-786.
  36. Rummens, Anneleen & Hardyns, Wim, 2021. "The effect of spatiotemporal resolution on predictive policing model performance," International Journal of Forecasting, Elsevier, vol. 37(1), pages 125-133.
  37. Hyeon-Woo Kang & Hang-Bong Kang, 2017. "Prediction of crime occurrence from multi-modal data using deep learning," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-19, April.
  38. Panagiotis Stalidis & Theodoros Semertzidis & Petros Daras, 2021. "Examining Deep Learning Architectures for Crime Classification and Prediction," Forecasting, MDPI, vol. 3(4), pages 1-22, October.
  39. Giada Adelfio & Marcello Chiodi, 2021. "Including covariates in a space-time point process with application to seismicity," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(3), pages 947-971, September.
  40. Angelos Dassios & Hongbiao Zhao, 2017. "A Generalized Contagion Process With An Application To Credit Risk," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(01), pages 1-33, February.
  41. Kieran Kalair & Colm Connaughton & Pierfrancesco Alaimo Di Loro, 2021. "A non‐parametric Hawkes process model of primary and secondary accidents on a UK smart motorway," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(1), pages 80-97, January.
  42. Anatoliy Swishchuk & Aiden Huffman, 2020. "General Compound Hawkes Processes in Limit Order Books," Risks, MDPI, vol. 8(1), pages 1-25, March.
  43. Stindl, Tom & Chen, Feng, 2018. "Likelihood based inference for the multivariate renewal Hawkes process," Computational Statistics & Data Analysis, Elsevier, vol. 123(C), pages 131-145.
  44. Ranjita Pandey & Himanshu Tolani, 2022. "Crime patterns in Delhi: a Bayesian spatio-temporal assessment," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(6), pages 2971-2980, December.
  45. Chenlong Li & Zhanjie Song & Wenjun Wang, 2020. "Space–time inhomogeneous background intensity estimators for semi-parametric space–time self-exciting point process models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(4), pages 945-967, August.
  46. Maillart, Thomas & Sornette, Didier, 2019. "Aristotle vs. Ringelmann: On superlinear production in open source software," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 964-972.
  47. Youngsoo Seol, 2023. "Large Deviations for Hawkes Processes with Randomized Baseline Intensity," Mathematics, MDPI, vol. 11(8), pages 1-10, April.
  48. Sebastian Meyer & Johannes Elias & Michael Höhle, 2012. "A Space–Time Conditional Intensity Model for Invasive Meningococcal Disease Occurrence," Biometrics, The International Biometric Society, vol. 68(2), pages 607-616, June.
  49. Dewei Wang & Chendi Jiang & Chanseok Park, 2019. "Reliability analysis of load-sharing systems with memory," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(2), pages 341-360, April.
  50. Nian Yao & Zhiqiu Li & Zhichao Ling & Junfeng Lin, 2020. "Asymptotic Smiles for an Affine Jump-Diffusion Model," Papers 2003.00334, arXiv.org, revised May 2020.
  51. Liu, Chenguang, 2020. "Statistical inference for a partially observed interacting system of Hawkes processes," Stochastic Processes and their Applications, Elsevier, vol. 130(9), pages 5636-5694.
  52. Gresnigt, Francine & Kole, Erik & Franses, Philip Hans, 2015. "Interpreting financial market crashes as earthquakes: A new Early Warning System for medium term crashes," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 123-139.
  53. Bao, Zemin & Liu, Yun & Zhang, Zhenjiang & Liu, Hui & Cheng, Junjun, 2019. "Predicting popularity via a generative model with adaptive peeking window," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 522(C), pages 54-68.
  54. Mercuri, Lorenzo & Perchiazzo, Andrea & Rroji, Edit, 2024. "A Hawkes model with CARMA(p,q) intensity," Insurance: Mathematics and Economics, Elsevier, vol. 116(C), pages 1-26.
  55. Thibault Jaisson & Mathieu Rosenbaum, 2015. "Rough fractional diffusions as scaling limits of nearly unstable heavy tailed Hawkes processes," Papers 1504.03100, arXiv.org.
  56. Ginger Saltos & Mihaela Cocea, 2017. "An Exploration of Crime Prediction Using Data Mining on Open Data," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(05), pages 1155-1181, September.
  57. Haberman, Cory P. & Hatten, David & Carter, Jeremy G. & Piza, Eric L., 2021. "The sensitivity of repeat and near repeat analysis to geocoding algorithms," Journal of Criminal Justice, Elsevier, vol. 73(C).
  58. Aït-Sahalia, Yacine & Cacho-Diaz, Julio & Laeven, Roger J.A., 2015. "Modeling financial contagion using mutually exciting jump processes," Journal of Financial Economics, Elsevier, vol. 117(3), pages 585-606.
  59. Samuel N. Cohen & Robert J. Elliott, 2013. "Filters and smoothers for self-exciting Markov modulated counting processes," Papers 1311.6257, arXiv.org.
  60. E. Bacry & K. Dayri & J. F. Muzy, 2011. "Non-parametric kernel estimation for symmetric Hawkes processes. Application to high frequency financial data," Papers 1112.1838, arXiv.org.
  61. Lirong Cui & Bei Wu & Juan Yin, 2022. "Moments for Hawkes Processes with Gamma Decay Kernel Functions," Methodology and Computing in Applied Probability, Springer, vol. 24(3), pages 1565-1601, September.
  62. Jakob Gulddahl Rasmussen, 2013. "Bayesian Inference for Hawkes Processes," Methodology and Computing in Applied Probability, Springer, vol. 15(3), pages 623-642, September.
  63. Emmanuel Bacry & Thibault Jaisson & Jean-Francois Muzy, 2014. "Estimation of slowly decreasing Hawkes kernels: Application to high frequency order book modelling," Papers 1412.7096, arXiv.org.
  64. 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).
  65. Mohler, George & Carter, Jeremy & Raje, Rajeev, 2018. "Improving social harm indices with a modulated Hawkes process," International Journal of Forecasting, Elsevier, vol. 34(3), pages 431-439.
  66. A E Clements & A S Hurn & K A Lindsay & V Volkov, 2023. "Estimating a Non-parametric Memory Kernel for Mutually Exciting Point Processes," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1759-1790.
  67. Bo Jing & Shenghong Li & Yong Ma, 2020. "Pricing VIX options with volatility clustering," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(6), pages 928-944, June.
  68. Ulrich Horst & Wei Xu, 2024. "Functional Limit Theorems for Hawkes Processes," Papers 2401.11495, arXiv.org, revised Nov 2024.
  69. Harris, J. Andrew & Posner, Daniel N., 2022. "Does decentralization encourage pro-poor targeting? Evidence from Kenya’s constituencies development fund," World Development, Elsevier, vol. 155(C).
  70. Achraf Bahamou & Maud Doumergue & Philippe Donnat, 2019. "Hawkes processes for credit indices time series analysis: How random are trades arrival times?," Papers 1902.03714, arXiv.org.
  71. Carter, Jeremy G. & Mohler, George & Raje, Rajeev & Chowdhury, Nahida & Pandey, Saurabh, 2021. "The Indianapolis harmspot policing experiment," Journal of Criminal Justice, Elsevier, vol. 74(C).
  72. Mateo Dulce Rubio, 2019. "Predicting criminal behavior with Levy flights using real data from Bogota," Documentos de Trabajo 17347, Quantil.
  73. Youngsoo Seol, 2022. "Non-Markovian Inverse Hawkes Processes," Mathematics, MDPI, vol. 10(9), pages 1-12, April.
  74. Laurent Lesage & Madalina Deaconu & Antoine Lejay & Jorge Augusto Meira & Geoffrey Nichil & Radu State, 2020. "Hawkes processes framework with a Gamma density as excitation function: application to natural disasters for insurance," Working Papers hal-03040090, HAL.
  75. Santitissadeekorn, N. & Short, M.B. & Lloyd, D.J.B., 2018. "Sequential data assimilation for 1D self-exciting processes with application to urban crime data," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 163-183.
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