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Alessandra Menafoglio (Politecnico di Milano) Thu, 10 May, 14:00 - 15:00 S4.36, Strand Building Object Oriented Spatial Statistics for the analysis of complex spatial data The analysis of complex data distributed over large or highly textured regions poses new challenges for spatial statistics. Object Oriented Spatial Statistics (O2S2) is a recent system of ideas and methods that allows the analysis of high dimensional and complex data when their spatial dependence is an important issue. We present the key concepts of O2S2, as a general approach to analyze and predict georeferenced complex data, interpreted as objects in appropriate mathematical spaces. We discuss the extension of key geostatistical concepts (e.g., stationarity) and methods (e.g., Kriging) in the context of O2S2. We present recent extensions of the O2S2 approach to the analysis of object data distributed over complex regions. Here, we deal with the data and the domain complexities through a divide-et-impera approach, grounded on the use of random decompositions of the study domain. The presented models and methods will be illustrated through real environmental case studies. (joint work with P. Secchi) Steven Gilmour Professor of Statistics Department of Mathematics King's College London Strand | London | WC2R 2LS UK Tel +44 (0)20 7848 2698 You may leave the list at any time by sending the command SIGNOFF allstat to [log in to unmask], leaving the subject line blank.