Dresden 2011 – wissenschaftliches Programm
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SOE: Fachverband Physik sozio-ökonomischer Systeme
SOE 14: Networks: From Topology to Dynamics II (with BP, DY)
SOE 14.8: Vortrag
Mittwoch, 16. März 2011, 12:45–13:00, GÖR 226
Surrogates and significance testing for spatially embedded complex networks — •Jonathan F. Donges1,2, Reik V. Donner1, Norbert Marwan1, and Jürgen Kurths1,2 — 1Potsdam Institute for Climate Impact Research, P.O.Box 60 12 03, 14412 Potsdam, Germany — 2Department of Physics, Humboldt University of Berlin, Newtonstr. 15, 12489 Berlin, Germany
The analysis of spatially embedded complex networks, i.e., networks with vertices embedded in a metric space, is of increasing interest in many fields of science. Examples are power grids in electrical engineering, the internet and world wide web in computer science or social networks in social science. In many cases, there is some degree of uncertainty about the network structure, e.g., edges might be missing in the network that exist in the system under study (the opposite may also be true). This is particularly relevant for networks constructed from multivariate data using the tools of time series analysis. Given this uncertainty, it is very important to evaluate the significance of measured network properties such as clustering coefficient, average path length, degree distribution or various vertex centrality sequences with respect to a given null hypothesis. Here we present different types of surrogates for spatially embedded networks, i.e., random networks with prescribed spatial constraints such as fixed edge distance distribution or a fixed average edge distance sequence, and show how to use them for testing the associated null hypotheses. The method is illustrated using diverse example networks, e.g., the european power grid or a climate network representing correlation structure of the surface air temperature field.