Lagged multidimensional recurrence quantification analysis for determining leader-follower relationships within multidimensional time series.

IF 7.6 1区 心理学 Q1 PSYCHOLOGY, MULTIDISCIPLINARY
Alon Tomashin,Ilanit Gordon,Giuseppe Leonardi,Yair Berson,Nir Milstein,Matthias Ziegler,Ursula Hess,Sebastian Wallot
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引用次数: 0

Abstract

The current article introduces lagged multidimensional recurrence quantification analysis. The method is an extension of multidimensional recurrence quantification analysis and allows to quantify the joint dynamics of multivariate time series and to investigate leader-follower relationships in behavioral and physiological data. Moreover, the method enables the quantification of the joint dynamics of a group, when such leader-follower relationships are taken into account. We first provide a formal presentation of the method, and then apply it to synthetic data, as well as data sets from joint action research, investigating the shared dynamics of facial expression and beats-per-minute recordings within different groups. A wrapper function is included, for applying the method together with the "crqa" package in R. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
用于确定多维时间序列中领导者与追随者关系的滞后多维复现量化分析。
本文介绍了滞后多维复现量化分析。该方法是多维复现量化分析的扩展,可以量化多变量时间序列的联合动态,研究行为和生理数据中的领导者与追随者关系。此外,如果考虑到这种领导者与追随者的关系,该方法还能量化群体的联合动态。我们首先对该方法进行了正式介绍,然后将其应用于合成数据以及来自联合行动研究的数据集,调查不同群体中面部表情和每分钟节拍记录的共享动态。我们还提供了一个封装函数,用于将该方法与 R 中的 "crqa "软件包一起应用(PsycInfo Database Record (c) 2024 APA, all rights reserved)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Psychological methods
Psychological methods PSYCHOLOGY, MULTIDISCIPLINARY-
CiteScore
13.10
自引率
7.10%
发文量
159
期刊介绍: Psychological Methods is devoted to the development and dissemination of methods for collecting, analyzing, understanding, and interpreting psychological data. Its purpose is the dissemination of innovations in research design, measurement, methodology, and quantitative and qualitative analysis to the psychological community; its further purpose is to promote effective communication about related substantive and methodological issues. The audience is expected to be diverse and to include those who develop new procedures, those who are responsible for undergraduate and graduate training in design, measurement, and statistics, as well as those who employ those procedures in research.
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