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Modeling conflict dynamics with spatiotemporal data

Autore: Andrew Zammit-Mangion; Michael Dewar; Visakan Kadirkamanathan; Anaïd Flesken; Guido Sanguinetti
Editore: Cham : Springer, 2013.
Serie: SpringerBriefs in applied sciences and technology., Mathematical methods.
Edizione/Formato:   eBook : Document : EnglishVedi tutte le edizioni e i formati
Banca dati:WorldCat
Sommario:
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  Per saperne di più…
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Dettagli

Genere/forma: Statistics
Electronic books
Informazioni aggiuntive sul formato: Print version:
Zammit-Mangion, Andrew.
Modeling conflict dynamics with spatiotemporal data
(OCoLC)855200592
Tipo materiale: Document, Risorsa internet
Tipo documento Risorsa Internet, Computer file
Tutti gli autori / Collaboratori: Andrew Zammit-Mangion; Michael Dewar; Visakan Kadirkamanathan; Anaïd Flesken; Guido Sanguinetti
{0} 9783319010380 3319010387 3319010379 9783319010373
Numero OCLC: 861183509
Descrizione: 1 online resource.
Contenuti: Conflict data sets and point patterns --
Theory --
Modelling and prediction in conflict: Afghanistan.
Titolo della serie: SpringerBriefs in applied sciences and technology., Mathematical methods.
Responsabilità: Andrew Zammit-Mangion, Michael Dewar, Visakan Kadirkamanathan, Anaïd Fleskin, Guido Sanguinetti.

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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