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Studying event time series is a powerful approach for analyzing the dynamics of complex dynamical systems in many fields of science. In this paper, we describe the method of event coincidence analysis to provide a framework for quantifying the strength, directionality and time lag of statistical interrelationships between event series. Event coincidence analysis 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 and other higher-order properties. Applying the framework to country-level observational data yields evidence that flood events have acted as triggers of epidemic outbreaks globally since the 1950s. Facing projected future changes in the statistics of climatic extreme events, statistical techniques such as event coincidence analysis will be relevant for investigating the impacts of anthropogenic climate change on human societies and ecosystems worldwide.
Research news | 2017-10-19
The starting point for a rethink on how we produce our food
Research news | 2017-10-18
Beatrice Crona awarded fellowship in new leadership programme on global health
Research news | 2017-10-16
How investments in solar energy go beyond access to electricity to positively affect people’s life expectancy and years of schooling
Research news | 2017-10-12
Stockholm Resilience Centre acts as impact partner for their Global Solutions Program
Research news | 2017-10-11
How pro-environmental interest groups were able to push for reforms of the EU Common Fisheries Policy
Educational news | 2017-10-02
Introducing our new executive programme in resilience thinking