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Analyzing Multivariate Dynamics Using Cross-Recurrence Quantification Analysis (CRQA) Diagonal-Cross-Recurrence Profiles (DCRP) and Multidimensional Recurrence Quantification Analysis (MdRQA) – A Tutorial in R

机译:使用交叉递归量化分析(CRQA)对角交叉递归分布图(DCRP)和多维递归量化分析(MdRQA)分析多元动力学– R中的教程

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摘要

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.
机译:本文为R中的交叉递归量化分析(CRQA),对角交叉递归分布图(DCRP)和多维递归量化分析(MdRQA)提供了实用的动手实践。这些方法在认知和认知方面越来越受欢迎。自从认识到许多行为和神经生理过程本质上是时间依赖并且依赖于环境和社会环境以来,社会科学就出现了。基于递归的方法特别适用于非平稳或具有复杂动力学的时间序列,例如更长的连续生理或运动数据记录,但对于符号数据的时间序列也很有用,例如文字/语言转录或分类编码行为的情况。过去,它们已用于评估生理和行为指标之间的动态变化或耦合,例如在联合行动研究中确定二元组或二元组中个体之间行为的共同演化,或用于评估两个或多个时间序列之间的耦合/相关强度。在本文中,我们为读者提供了概念上的介绍,然后逐步解释了如何在R中执行分析,并总结了其应用程序的当前最佳实践。

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