Nonlinear analysis of bivariate data with cross recurrence plots

Abstract

We use the extension of the method of recurrence plots to cross recurrence plots (CRP) which enables a nonlinear analysis of bivariate data. To quantify CRPs, we develop further three measures of complexity mainly basing on diagonal structures in CRPs. The CRP analysis of prototypical model systems with nonlinear interactions demonstrates that this technique enables to find these nonlinear interrelations from bivariate time series, whereas linear correlation tests do not. Applying the CRP analysis to climatological data, we find a complex relationship between rainfall and El Nino data.

References in corpus (3)

• Measuring Information Transfer
• Recurrence Plot Based Measures of Complexity and its Application to Heart Rate Variability Data
• Cross Recurrence Plot Based Synchronization of Time Series

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