Point process modelling of the Afghan War Diary

Proceedings of the National Academy of Sciences of the United States of America

Volumn 109, Issue 31, 2012, Pages 12414-12419

  Zammit Mangion, Andrew ^a,b   Dewar, Michael ^c   Kadirkamanathan, Visakan ^d   Sanguinetti, Guido ^a  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

^b UNIVERSITY OF EDINBURGH   (United Kingdom)

^c Columbia University ^*  (United States)

^d UNIVERSITY OF SHEFFIELD   (United Kingdom)

Author keywords

Conflict prediction; Point processes; Variational Bayes

Indexed keywords

AFGHANISTAN; ARTICLE; HUMAN; INTERNET; PARAMETERS; PRIORITY JOURNAL; WAR; WEB BROWSER;

AFGHAN CAMPAIGN 2001-; ECOLOGY; HISTORY, 21ST CENTURY; HUMANS; MODELS, THEORETICAL;

EID: 84864521921     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1203177109     Document Type: Article

References (30)

1. Raleigh C, Linke A, Hegre H, Karlsen J (2010) Introducing ACLED: an armed conflict location and event dataset. J Peace Res 47:651-660.
2. O'Loughlin J, Witmer FDW, Linke AM, Thorwardson N (2010) Peering into the fog of war: the geography of the WikiLeaks Afghanistan war logs, 2004-2009. Eurasian Geogr Econ 51:472-495.
3. O'Loughlin J, Witmer FDW, Linke AM (2010) The Afghanistan-Pakistan wars, 2008-2009: micro-geographies, conflict diffusion, and clusters of violence. Eurasian Geogr Econ 51:437-471.
4. Gleditsch KS, Weidmann NB (2012) Richardson in the information age: GIS and spatial data in international studies. Annu Rev Polit Sci 15:461-481.
5. Bohannon J (2011) Counting the dead in Afghanistan. Science 331:1256-1260.
6. Haushofer J, Biletzki A, Kanwisher N (2010) Both sides retaliate in the Israeli-Palestinian conflict. Proc Natl Acad Sci USA 107:17927-17932.
7. Weidmann NB, Ward MD (2010) Predicting conflict in space and time. J Conflict Resolut 54:883-901.
8. Schutte S,Weidmann NB (2011) Diffusion patterns of violence in civil wars. Polit Geogr 30:143-152.
9. Zhukov YM (2012) Roads and the diffusion of insurgent violence: the logistics of conflict in Russia's North Caucasus. Polit Geogr 31:144-156.
10. Moeller J, Waagepetersen R (2004) Statistical Inference and Simulation for Spatial Point Processes (CRC Press, Boca Raton).
11. Zammit Mangion A, Yuan K, Kadirkamanathan V, Niranjan M, Sanguinetti G (2011) Online variational inference for state-space models with point-process observations. Neural Comput 23:1967-1999.
12. Zammit Mangion A, Sanguinetti G, Kadirkamanathan V (2012) Variational estimation in spatiotemporal systems from continuous and point-process observations. IEEE T Signal Process 60:3449-3459.
13. Wikle CK, Holan SH (2011) Polynomial nonlinear spatio-temporal integro-difference equation models. J Time Ser Anal 32:339-350.
14. Cressie NAC, Wikle CK (2011) Statistics for Spatio-temporal Data (Wiley, New Jersey).
15. Diggle P, Rowlingson B, Su T (2005) Point process methodology for online spatio-temporal disease surveillance. Environmetrics 16:423-434. (Pubitemid 40995774)
16. Brix A, Moeller J (2001) Space-time multi type log Gaussian Cox processes with a view to modelling weeds. Scandinavian Journal of Statistics 28:471-488.
17. Rasmussen CE, Williams CKI (2006) Gaussian Processes for Machine Learning (The MIT Press, Cambridge, MA).
18. Kot M, Lewis MA, van den Driessche P (1996) Dispersal data and the spread of invading organisms. Ecology 77:2027-2042.
19. Wikle CK (2002) A kernel-based spectral model for non-Gaussian spatiotemporal processes. Stat Model 2:299-314.
20. Dewar M, Scerri K, Kadirkamanathan V (2009) Data-driven spatiotemporal modeling using the integro-difference equation. IEEE T Signal Process 57:83-91.
21. Scerri K, Dewar M, Kadirkamanathan V (2009) Estimation and model selection for an IDE-based spatio-temporal model. IEEE T Signal Process 57:482-492.
22. Rodrigues A, Diggle P (2010) A class of convolution-based models for spatiotemporal processes with non-separable covariance structure. Scandinavian Journal of Statistics 37:553-567.
23. Higdon D (1998) A process convolution approach to modelling temperatures in the North Atlantic ocean (with Discussion). Environ Ecol Stat 5:173-190.
24. Bracewell R (2000) in The Fourier Transform & its Applications (McGraw-Hill, Singapore), 3rd Ed, p 122.
25. Freestone DR, et al. (2011) A data-driven framework for neural field modeling. Neuro- Image 56:1043-1058.
26. Beal MJ (2003) Variational Algorithms for Approximate Bayesian Inference. PhD thesis (Gatsby Computational Neuroscience Unit, University College London, United Kingdom).
27. Smidl V, Quinn A (2005) The Variational Bayes Method in Signal Processing (Springer Verlag, New York).
28. Jazwinski AH (1970) Stochastic Processes and Filtering Theory (Academic Press, London).
29. Stroud JR, Mueller P, Sanso B (2001) Dynamic models for spatiotemporal data. J R Stat Soc B Stat Met 63:673-689. (Pubitemid 33402066)
30. Diggle P (1985) A kernel method for smoothing point process data. Appl Stat 34:138-147.