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Modeling conflict dynamics with spatiotemporal data

Auteur: Andrew Zammit-Mangion
Uitgever: Cham : Springer, 2013.
Serie: SpringerBriefs in applied sciences and technology., Mathematical methods.
Editie/Formaat:   eBoek : Document : EngelsAlle edities en materiaalsoorten bekijken.
Database:WorldCat
Samenvatting:
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  Meer lezen...
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Genre/Vorm: Electronic books
Aanvullende fysieke materiaalsoort: Print version:
Zammit-Mangion, Andrew, author.
Modeling conflict dynamics with spatiotemporal data
(OCoLC)855200592
Genre: Document, Internetbron
Soort document: Internetbron, Computerbestand
Alle auteurs / medewerkers: Andrew Zammit-Mangion
ISBN: 9783319010380 3319010387
OCLC-nummer: 861183509
Beschrijving: 1 online resource.
Inhoud: Conflict data sets and point patterns --
Theory --
Modelling and prediction in conflict: Afghanistan.
Serietitel: SpringerBriefs in applied sciences and technology., Mathematical methods.
Verantwoordelijkheid: Andrew Zammit-Mangion, Michael Dewar, Visakan Kadirkamanathan, Anaïd Fleskin, Guido Sanguinetti.
Meer informatie:

Fragment:

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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