Abstract
Complex systems are characterized by deterministic laws (which often may be hidden) and randomness. A tool to analyse those systems is recurrence quantification analysis (RQA). RQA does not rely on any sort of assumption of stationarity and is not sensitive to singularities and transitions. It could be applied to both numeric and symbolic data, and it has a wide array of applications ranging from economics to biochemistry, physiology and physics. In Sect. 10.2, we introduce the reader to the recurrence plot, and in Sect. 10.3 to the recurrence quantification analysis. In Sect. 10.4, we exhibit specific examples of the application of RQA. This is of great importance because RQA can be adopted to derive an indicator of structural changes in a signal related to chaos.
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Orlando, G., Zimatore, G., Giuliani, A. (2021). Recurrence Quantification Analysis: Theory and Applications. In: Orlando, G., Pisarchik, A.N., Stoop, R. (eds) Nonlinearities in Economics. Dynamic Modeling and Econometrics in Economics and Finance, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-030-70982-2_10
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