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Analyzing Multivariate Dynamics Using Cross-Recurrence Quantification Analysis (CRQA), Diagonal-Cross-Recurrence

Sebastian Wallot1, Giuseppe Leonardi2

  • 1Max Planck Institute for Empirical Aesthetics, Frankfurt am Main, Germany.

Frontiers in Psychology
|December 20, 2018
PubMed
Summary
This summary is machine-generated.

This paper introduces cross-recurrence quantification analysis (CRQA) and related methods for analyzing time-dependent data in R. It offers practical guidance for researchers in cognitive and social sciences using these recurrence-based techniques.

Keywords:
RRQAcross-recurrence quantification analysisdiagonal cross-recurrence profilemultidimensional recurrence quantification analysistutorial

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Area of Science:

  • Cognitive Science
  • Social Science
  • Data Analysis

Background:

  • Behavioral and neurophysiological processes are time-dependent and context-reliant.
  • Recurrence-based methods are suitable for complex, non-stationary time-series data.
  • These methods analyze dynamics and coupling in physiological, movement, and symbolic data.

Purpose of the Study:

  • Provide a practical introduction to cross-recurrence quantification analysis (CRQA), diagonal cross-recurrence profiles (DCRP), and multidimensional recurrence quantification analysis (MdRQA).
  • Demonstrate the application of these methods in the R statistical environment.
  • Offer guidance on current best practices for applying recurrence quantification analysis.

Main Methods:

  • Conceptual introduction to CRQA, DCRP, and MdRQA.
  • Step-by-step R implementation of recurrence-based analyses.
  • Application examples in joint action research and time-series coupling.

Main Results:

  • Demonstrated practical application of CRQA, DCRP, and MdRQA in R.
  • Provided a framework for analyzing time-dependent data in cognitive and social sciences.
  • Highlighted the utility of recurrence methods for various data types.

Conclusions:

  • Recurrence quantification analysis offers powerful tools for studying complex, time-dependent phenomena.
  • R provides a robust platform for implementing these advanced analytical techniques.
  • The paper serves as a valuable resource for researchers seeking to apply recurrence methods.