Probabilistic models for warning of national security crises
Abstract/Contents
- Abstract
- Intelligence analysts have experimented with static forms of Bayesian inference since the late 1960's. However, their static probabilistic approaches have proven unsuitable for warning analysis. In this dissertation, I develop an analytic framework for crisis early warning that addresses four challenges: (i) it has the flexibility to incorporate geographical variation; (ii) it reflects the dynamics of a crisis in order to enable lead time estimation; (iii) it incorporates conditional dependencies among signals and data; (iv) it treats an analyst's decision of when to warn, and type of warning to give, in decision-theoretic terms. The framework is rooted in a general warning system developed by Paté-Cornell and expands on the work of Schrodt. The models comprising the framework are illustrated using a historical example, the lead up to Japan's attack on Pearl Harbor in 1941. They are then demonstrated through a contemporary case study, the warning of violence against civilians in Guatemala being perpetrated by a transnational criminal organization. From the Pearl Harbor illustration, using parameters that are entirely illustrative, the model would have issued an alert for an attack on Oahu on December 2, 1941. Despite the illustrative nature of the results, the exercise highlights the importance of incorporating decision analytic techniques in the warning process. It also demonstrates the process of entity tracking through the inference of signals, which is broadly applicable. From the transnational criminal organization case study, I demonstrate how one's belief regarding the likelihood of violence in particular municipalities, distributed over time, changes with the observation of successive signals of organizational activities. I also identify two routes spanning the width of Guatemala, which, over the period February 1 to August 31, 2012, are consistently the most secure smuggling routes.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2012 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Blum, David Melbourne |
|---|---|
| Associated with | Stanford University, Department of Management Science and Engineering |
| Primary advisor | Paté-Cornell, M. Elisabeth (Marie Elisabeth) |
| Thesis advisor | Paté-Cornell, M. Elisabeth (Marie Elisabeth) |
| Thesis advisor | Hecker, Siegfried S |
| Thesis advisor | Oliver, Robert |
| Advisor | Hecker, Siegfried S |
| Advisor | Oliver, Robert |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | David Melbourne Blum. |
|---|---|
| Note | Submitted to the Department of Management Science and Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2012. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2012 by David Melbourne Blum
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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