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Last update: T_KPMS (27.04.2016)
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Last update: T_KPMS (06.05.2014)
The aim of the course is to present some advanced modern topics in spatial modeling, spatial statistics and stochastic geometry. |
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Last update: T_KPMS (06.05.2014)
A. E. Gelfand, P. Diggle, P. Guttorp, M. Fuentes (eds.): Handbook of Spatial Statistics, Chapman & Hall/CRC, Boca Raton, 2010. W. S. Kendall, I. Molchanov (eds.): New Perspectives in Stochastic Geometry, Oxford University Press, 2010. R. Schneider, W. Weil: Stochastic and Integral Geometry, Springer, Berlin, 2008. E. Spodarev (ed.): Stochastic Geometry, Spatial Statistics and Random Fields - Asymptotic Methods, Lecture Notes in Mathematics 2068, Springer, Heidelberg, 2013. |
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Last update: T_KPMS (06.05.2014)
Lecture. |
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Last update: T_KPMS (06.05.2014)
1. ergodicity and mixing for spatial point processes, limit theorems for point processes and particle processes in large domains, approximation by m-dependent random fields 2. asymptotics for Poisson processes, stabilization theory, chaos decomposition and Stein’s method 3. random fields with continuous parameter, more advanced models, statistical methods, simulation 4. statistical inference for inhomogeneous and space-time point processes |