Finding recurrence networks' threshold adaptively for a specific time series
- 1Potsdam Institute for Climate Impact Research, Potsdam, Germany
- 2Department of Physics, Humboldt University of Berlin, Berlin, Germany
- 3Institute of Earth and Environmental Science, Potsdam University, Potsdam, Germany
- 4Institute of Complex Systems and Mathematical Biology, University of Aberdeen, Aberdeen, UK
Abstract. Recurrence-plot-based recurrence networks are an approach used to analyze time series using a complex networks theory. In both approaches – recurrence plots and recurrence networks –, a threshold to identify recurrent states is required. The selection of the threshold is important in order to avoid bias of the recurrence network results. In this paper, we propose a novel method to choose a recurrence threshold adaptively. We show a comparison between the constant threshold and adaptive threshold cases to study period–chaos and even period–period transitions in the dynamics of a prototypical model system. This novel method is then used to identify climate transitions from a lake sediment record.