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Modeling conflict dynamics with spatiotemporal data

Author: Andrew Zammit-Mangion
Publisher: Cham : Springer, 2013.
Series: SpringerBriefs in applied sciences and technology., Mathematical methods.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
This authored monograph presents the use of dynamic spatiotemporal modeling tools for the identification of complex underlying processes in conflict, such as diffusion, relocation, heterogeneous escalation, and volatility. The authors use ideas from statistics, signal processing, and ecology, and provide a predictive framework which is able to assimilate data and give confidence estimates on the predictions. The  Read more...
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Genre/Form: Electronic books
Statistics
Additional Physical Format: Print version:
Zammit-Mangion, Andrew, author.
Modeling conflict dynamics with spatiotemporal data
(OCoLC)855200592
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Andrew Zammit-Mangion
ISBN: 9783319010380 3319010387
OCLC Number: 861183509
Description: 1 online resource.
Contents: Conflict data sets and point patterns --
Theory --
Modelling and prediction in conflict: Afghanistan.
Series Title: SpringerBriefs in applied sciences and technology., Mathematical methods.
Responsibility: Andrew Zammit-Mangion, Michael Dewar, Visakan Kadirkamanathan, Anaïd Fleskin, Guido Sanguinetti.
More information:

Abstract:

This authored monograph presents the use of dynamic spatiotemporal modeling tools for the identification of complex underlying processes in conflict, such as diffusion, relocation, heterogeneous escalation, and volatility. The authors use ideas from statistics, signal processing, and ecology, and provide a predictive framework which is able to assimilate data and give confidence estimates on the predictions. The book also demonstrates the methods on the WikiLeaks Afghan War Diary, the results showing that this approach allows deeper insights into conflict dynamics and allows a strikingly statistically accurate forward prediction of armed opposition group activity in 2010, based solely on data from preceding years. The target audience primarily comprises researchers and practitionersin the involved fields but the book may also be beneficial for graduate students.

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