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Activity Number:
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6
- Highlights in 'Bayesian Analysis': Stories to Tell
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Type:
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Invited
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Date/Time:
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Sunday, August 8, 2021 : 1:30 PM to 3:20 PM
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Sponsor:
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Section on Bayesian Statistical Science
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Abstract #314478
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Title:
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A Bayesian Hierarchical Model of Violent Criminal Threat
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Author(s):
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Francis Oliver Bunnin* and Jim Q Smith
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Companies:
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The Alan Turing Institute and University of Warwick; The Alan Turing Institute
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Keywords:
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Chain Event Graphs;
Bayesian hierarchical models;
graphical models;
Markov switching models;
terrorism;
latent state space models
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Abstract:
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Violent criminals will often need to go through a sequence of preparatory steps before they can execute their plans. During this escalation process police have the opportunity to evaluate the threat posed by such people through what they know, observe and learn from intelligence reports about their activities. We customise a Bayesian hierarchical model to describe this process. This is able to propagate both routine and unexpected evidence in real time. The model structure comprises the latent threat state of an individual person of interest; the activities that person carries out relevant to an attack; and observable data produced by those activities. The model aims to support real-time decision making by security analysts. Specifically it aims to focus attention and allocate constrained resources on the cases that pose the greatest imminent danger.
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Authors who are presenting talks have a * after their name.
