Analyzing multivariate dynamics using cross-recurrence quantification analysis (CRQA), diagonal-cross-recurrence profiles (DCRP), and multidimensional recurrence quantification analysis (MdRQA) - A tutorial in R

Research output: Journal contributionsJournal articlesResearchpeer-review

Standard

Harvard

APA

Vancouver

Bibtex

@article{49d852bf6ee54efa85b0742347196b80,
title = "Analyzing multivariate dynamics using cross-recurrence quantification analysis (CRQA), diagonal-cross-recurrence profiles (DCRP), and multidimensional recurrence quantification analysis (MdRQA) - A tutorial in R",
abstract = "This paper provides a practical, hands-on introduction to cross-recurrence quantification analysis (CRQA), diagonal cross-recurrence profiles (DCRP), and multidimensional recurrence quantification analysis (MdRQA) in R. These methods have enjoyed increasing popularity in the cognitive and social sciences since a recognition that many behavioral and neurophysiological processes are intrinsically time dependent and reliant on environmental and social context has emerged. Recurrence-based methods are particularly suited for time-series that are non-stationary or have complicated dynamics, such as longer recordings of continuous physiological or movement data, but are also useful in the case of time-series of symbolic data, as in the case of text/verbal transcriptions or categorically coded behaviors. In the past, they have been used to assess changes in the dynamics of, or coupling between physiological and behavioral measures, for example in joint action research to determine the co-evolution of the behavior between individuals in dyads or groups, or for assessing the strength of coupling/correlation between two or more time-series. In this paper, we provide readers with a conceptual introduction, followed by a step-by-step explanation on how the analyses are performed in R with a summary of the current best practices of their application.",
keywords = "Psychology, Cross-recurrence quantification analysis, Diagonal cross-recurrence profile, Multidimensional recurrence quantification analysis, R, RQA, Tutorial",
author = "Sebastian Wallot and Giuseppe Leonardi",
year = "2018",
month = dec,
day = "4",
doi = "10.3389/fpsyg.2018.02232",
language = "English",
volume = "9",
journal = "Frontiers in Psychology",
issn = "1664-1078",
publisher = "Frontiers Media SA",
number = "DEC",

}

RIS

TY - JOUR

T1 - Analyzing multivariate dynamics using cross-recurrence quantification analysis (CRQA), diagonal-cross-recurrence profiles (DCRP), and multidimensional recurrence quantification analysis (MdRQA) - A tutorial in R

AU - Wallot, Sebastian

AU - Leonardi, Giuseppe

PY - 2018/12/4

Y1 - 2018/12/4

N2 - This paper provides a practical, hands-on introduction to cross-recurrence quantification analysis (CRQA), diagonal cross-recurrence profiles (DCRP), and multidimensional recurrence quantification analysis (MdRQA) in R. These methods have enjoyed increasing popularity in the cognitive and social sciences since a recognition that many behavioral and neurophysiological processes are intrinsically time dependent and reliant on environmental and social context has emerged. Recurrence-based methods are particularly suited for time-series that are non-stationary or have complicated dynamics, such as longer recordings of continuous physiological or movement data, but are also useful in the case of time-series of symbolic data, as in the case of text/verbal transcriptions or categorically coded behaviors. In the past, they have been used to assess changes in the dynamics of, or coupling between physiological and behavioral measures, for example in joint action research to determine the co-evolution of the behavior between individuals in dyads or groups, or for assessing the strength of coupling/correlation between two or more time-series. In this paper, we provide readers with a conceptual introduction, followed by a step-by-step explanation on how the analyses are performed in R with a summary of the current best practices of their application.

AB - This paper provides a practical, hands-on introduction to cross-recurrence quantification analysis (CRQA), diagonal cross-recurrence profiles (DCRP), and multidimensional recurrence quantification analysis (MdRQA) in R. These methods have enjoyed increasing popularity in the cognitive and social sciences since a recognition that many behavioral and neurophysiological processes are intrinsically time dependent and reliant on environmental and social context has emerged. Recurrence-based methods are particularly suited for time-series that are non-stationary or have complicated dynamics, such as longer recordings of continuous physiological or movement data, but are also useful in the case of time-series of symbolic data, as in the case of text/verbal transcriptions or categorically coded behaviors. In the past, they have been used to assess changes in the dynamics of, or coupling between physiological and behavioral measures, for example in joint action research to determine the co-evolution of the behavior between individuals in dyads or groups, or for assessing the strength of coupling/correlation between two or more time-series. In this paper, we provide readers with a conceptual introduction, followed by a step-by-step explanation on how the analyses are performed in R with a summary of the current best practices of their application.

KW - Psychology

KW - Cross-recurrence quantification analysis

KW - Diagonal cross-recurrence profile

KW - Multidimensional recurrence quantification analysis

KW - R

KW - RQA

KW - Tutorial

UR - http://www.scopus.com/inward/record.url?scp=85057610977&partnerID=8YFLogxK

U2 - 10.3389/fpsyg.2018.02232

DO - 10.3389/fpsyg.2018.02232

M3 - Journal articles

C2 - 30564161

AN - SCOPUS:85057610977

VL - 9

JO - Frontiers in Psychology

JF - Frontiers in Psychology

SN - 1664-1078

IS - DEC

M1 - 2232

ER -

DOI

Recently viewed

Publications

  1. Advanced Neural Classifier-Based Effective Human Assistance Robots Using Comparable Interactive Input Assessment Technique
  2. A Wavelet Based Algorithm without a Priori Knowledge of Noise Level for Gross Errors Detection
  3. Fostering Circularity: Building a Local Community and Implementing Circular Processes
  4. Calculation of Average Mutual Information (AMI) and false-nearest neighbors (FNN) for the estimation of embedding parameters of multidimensional time series in matlab
  5. Modeling and Performance Analysis of a Node in Fault Tolerant Wireless Sensor Networks
  6. Discourse Analyses in Chat-based CSCL with Learning Protocols
  7. Database Publishing Without Databases
  8. A Lightweight Simulation Model for Soft Robot's Locomotion and its Application to Trajectory Optimization
  9. Transformer with Tree-order Encoding for Neural Program Generation
  10. Closed-loop control of product geometry by using an artificial neural network in incremental sheet forming with active medium
  11. Preventive Emergency Detection Based on the Probabilistic Evaluation of Distributed, Embedded Sensor Networks
  12. A transfer operator based computational study of mixing processes in open flow systems
  13. Automatic enumeration of all connected subgraphs.
  14. Methodologies for Noise and Gross Error Detection using Univariate Signal-Based Approaches in Industrial Application
  15. Enabling Road Condition Monitoring with an on-board Vehicle Sensor Setup
  16. Efficient and accurate ℓ p-norm multiple kernel learning
  17. Neural network-based adaptive fault-tolerant control for strict-feedback nonlinear systems with input dead zone and saturation
  18. Different complex word problems require different combinations of cognitive skills
  19. Semantic Parsing for Knowledge Graph Question Answering with Large Language Models
  20. Control of the inverse pendulum based on sliding mode and model predictive control
  21. Clustering Hydrological Homogeneous Regions and Neural Network Based Index Flood Estimation for Ungauged Catchments
  22. Latent structure perceptron with feature induction for unrestricted coreference resolution
  23. Selecting and Adapting Methods for Analysis and Design in Value-Sensitive Digital Social Innovation Projects: Toward Design Principles
  24. Modeling Effective and Ineffective Knowledge Communication and Learning Discourses in CSCL with Hidden Markov Models
  25. Problem structuring for transitions
  26. Using Decision Trees and Reinforcement Learning for the Dynamic Adjustment of Composite Sequencing Rules in a Flexible Manufacturing System
  27. Spatial mislocalization as a consequence of sequential coding of stimuli
  28. DialogueMaps: Supporting interactive transdisciplinary dialogues with a web-based tool for multi-layer knowledge maps
  29. Real-time RDF extraction from unstructured data streams
  30. A Multivariate Method for Dynamic System Analysis
  31. On the Decoupling and Output Functional Controllability of Robotic Manipulation
  32. Analysis of long-term statistical data of cobalt flows in the EU
  33. Supporting the Development and Implementation of a Digitalization Strategy in SMEs through a Lightweight Architecture-based Method
  34. FFTSMC with Optimal Reference Trajectory Generated by MPC in Robust Robotino Motion Planning with Saturating Inputs
  35. Retest effects in matrix test performance