Regensburg 2016 – wissenschaftliches Programm
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DY: Fachverband Dynamik und Statistische Physik
DY 52: Extreme events
DY 52.3: Vortrag
Donnerstag, 10. März 2016, 12:00–12:15, H47
Event coincidence analysis for quantifying statistical interrelationships between event time series — Jonathan F. Donges1,2, Carl-Friedrich Schleussner1,3, Jonatan F. Siegmund1,4, and •Reik V. Donner1 — 1Potsdam Institute for Climate Impact Research, Potsdam, Germany — 2Stockholm Resilience Centre, Stockholm, Sweden — 3Climate Analytics, Berlin, Germany — 4University of Potsdam, Germany
Despite its relevance and wide applicability for interdisciplinary research, the statistical analysis of interrelations between event time series has received relatively little attention in the literature so far. Here, we introduce the concept of event coincidence analysis (ECA) as a novel framework for quantifying the strength, directionality and time lag of statistical interrelationships between event series. ECA allows to formulate and test null hypotheses on the origin of the observed interrelationships including tests based on Poisson processes or, more generally, stochastic point processes with a prescribed inter-event time distribution. As an illustrative example, we apply ECA to country-level observational data on flood events and epidemic outbreaks, providing robust statistical evidence for corresponding relationships since the 1950s.