Self-exciting hurdle models for terrorist activity

Abstract

A predictive model of terrorist activity is developed by examining the daily number of terrorist attacks in Indonesia from 1994 through 2007. The dynamic model employs a shot noise process to explain the self-exciting nature of the terrorist activities. This estimates the probability of future attacks as a function of the times since the past attacks. In addition, the excess of nonattack days coupled with the presence of multiple coordinated attacks on the same day compelled the use of hurdle models to jointly model the probability of an attack day and corresponding number of attacks. A power law distribution with a shot noise driven parameter best modeled the number of attacks on an attack day. Interpretation of the model parameters is discussed and predictive performance of the models is evaluated.

Published in at http://dx.doi.org/10.1214/11-AOAS513 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)

References in corpus (4)

• Power-law distributions in empirical data
• Problems with Fitting to the Power-Law Distribution
• On the Frequency of Severe Terrorist Events
• Bayesian anomaly detection methods for social networks

Cited by in corpus (13)

• A Gillespie algorithm for non-Markovian stochastic processes
• Modeling and estimation of multi-source clustering in crime and security data
• A Review of Self-Exciting Spatio-Temporal Point Processes and Their Applications
• Reactive point processes: A new approach to predicting power failures in underground electrical systems
• Hidden Markov models for the activity profile of terrorist groups
• Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information
• Learning future terrorist targets through temporal meta-graphs
• Latent Self-Exciting Point Process Model for Spatial-Temporal Networks
• The Role of Governmental Weapons Procurements in Forecasting Monthly Fatalities in Intrastate Conflicts: A Semiparametric Hierarchical Hurdle Model
• Assessing the contagiousness of mass shootings with nonparametric Hawkes processes
• Discussion of "Estimating the historical and future probabilities of large terrorist events" by Aaron Clauset and Ryan Woodard
• Discussion of "Estimating the historical and future probabilities of large terrorist events" by Aaron Clauset and Ryan Woodard
• Mitigating Performance Saturation in Neural Marked Point Processes: Architectures and Loss Functions