Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis with crqa

Article


Coco, M., Mønster, D., Leonardi, G., Dale, R. and Wallot, S. 2021. Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis with crqa. The R Journal. 13 (1), pp. 145-163. https://doi.org/10.32614/RJ-2021-062
AuthorsCoco, M., Mønster, D., Leonardi, G., Dale, R. and Wallot, S.
Abstract

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 recurrence based 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 auto recurrence 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 recurrence based 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.

JournalThe R Journal
Journal citation13 (1), pp. 145-163
ISSN2073-4859
Year2021
PublisherThe R Foundation
Publisher's version
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File Access Level
Anyone
Digital Object Identifier (DOI)https://doi.org/10.32614/RJ-2021-062
Publication dates
Online21 Jun 2021
Publication process dates
Deposited14 Sep 2021
FunderDeutsche Forschungsgemeinschaft
Fundação para a Ciência e Tecnologia
Copyright holder© 2021 The R Foundation
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