Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis with crqa

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Authors

Recurrence quantification analysis is a widely used method for characterizing patterns in time series. This article presents a comprehensive survey for conducting a wide range of recurrencebased analyses to quantify the dynamical structure of single and multivariate time series and capture coupling properties underlying leader-follower relationships. The basics of recurrence quantification analysis (RQA) and all its variants are formally introduced step-by-step from the simplest autorecurrence to the most advanced multivariate case. Importantly, we show how such RQA methods can be deployed under a single computational framework in R using a substantially renewed version of our crqa 2.0 package. This package includes implementations of several recent advances in recurrencebased analysis, among them applications to multivariate data and improved entropy calculations for categorical data. We show concrete applications of our package to example data, together with a detailed description of its functions and some guidelines on their usage.

OriginalspracheEnglisch
ZeitschriftR Journal
Jahrgang13
Ausgabenummer1
Seiten (von - bis)145-163
Anzahl der Seiten19
ISSN2073-4859
DOIs
PublikationsstatusErschienen - 06.2021
Extern publiziertJa

Bibliographische Notiz

Funding Information:
SW acknowledges support from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)–WA 3538/4-1. MIC acknowledges support from the Fundaçâo para a Ciência e Tecnologia under grant agreement PTDC/PSI-ESP/30958/2017.

Publisher Copyright:
© 2021. All Rights Reserved.

DOI