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Multidimensional Cross-Recurrence Quantification Analysis (MdCRQA)–A Method for Quantifying Correlation between Multivariate Time-Series

Research output: Journal contributions › Journal articles › Research › peer-review

Standard

Multidimensional Cross-Recurrence Quantification Analysis (MdCRQA)–A Method for Quantifying Correlation between Multivariate Time-Series. / Wallot, Sebastian.
In: Multivariate Behavioral Research, Vol. 54, No. 2, 04.03.2019, p. 173-191.

Research output: Journal contributions › Journal articles › Research › peer-review

Harvard

Wallot, S 2019, 'Multidimensional Cross-Recurrence Quantification Analysis (MdCRQA)–A Method for Quantifying Correlation between Multivariate Time-Series', Multivariate Behavioral Research, vol. 54, no. 2, pp. 173-191. https://doi.org/10.1080/00273171.2018.1512846

APA

Wallot, S. (2019). Multidimensional Cross-Recurrence Quantification Analysis (MdCRQA)–A Method for Quantifying Correlation between Multivariate Time-Series. Multivariate Behavioral Research, 54(2), 173-191. https://doi.org/10.1080/00273171.2018.1512846

Vancouver

Wallot S. Multidimensional Cross-Recurrence Quantification Analysis (MdCRQA)–A Method for Quantifying Correlation between Multivariate Time-Series. Multivariate Behavioral Research. 2019 Mar 4;54(2):173-191. doi: 10.1080/00273171.2018.1512846

Bibtex

@article{1032b950584142a38b978c728898f9a8,
title = "Multidimensional Cross-Recurrence Quantification Analysis (MdCRQA)–A Method for Quantifying Correlation between Multivariate Time-Series",
abstract = "In this paper, Multidimensional Cross-Recurrence Quantification Analysis (MdCRQA) is introduced. It is an extension of Multidimensional Recurrence Quantification Analysis (MdRQA), which allows to quantify the (auto-)recurrence properties of a single multidimensional time-series. MdCRQA extends MdRQA to bi-variate cases to allow for the quantification of the co-evolution of two multidimensional time-series. Moreover, it is shown how a Diagonal Cross-Recurrence Profile (DCRP) can be computed from the MdCRQA output that allows to capture time-lagged coupling between two multidimensional time-series. The core concepts of these analyses are described, as well as practical aspects of their application. In the supplementary materials to this paper, implementations of MdCRQA and the DCRP as MatLab- and R-functions are provided.",
keywords = "Psychology, DCRP, MatLab, MdCRQA, Multidimensional Cross-Recurrence Quantification Analysis, multivariate time-series, R",
author = "Sebastian Wallot",
year = "2019",
month = mar,
day = "4",
doi = "10.1080/00273171.2018.1512846",
language = "English",
volume = "54",
pages = "173--191",
journal = "Multivariate Behavioral Research",
issn = "0027-3171",
publisher = "Psychology Press Ltd",
number = "2",

}

RIS

TY - JOUR

T1 - Multidimensional Cross-Recurrence Quantification Analysis (MdCRQA)–A Method for Quantifying Correlation between Multivariate Time-Series

AU - Wallot, Sebastian

PY - 2019/3/4

Y1 - 2019/3/4

N2 - In this paper, Multidimensional Cross-Recurrence Quantification Analysis (MdCRQA) is introduced. It is an extension of Multidimensional Recurrence Quantification Analysis (MdRQA), which allows to quantify the (auto-)recurrence properties of a single multidimensional time-series. MdCRQA extends MdRQA to bi-variate cases to allow for the quantification of the co-evolution of two multidimensional time-series. Moreover, it is shown how a Diagonal Cross-Recurrence Profile (DCRP) can be computed from the MdCRQA output that allows to capture time-lagged coupling between two multidimensional time-series. The core concepts of these analyses are described, as well as practical aspects of their application. In the supplementary materials to this paper, implementations of MdCRQA and the DCRP as MatLab- and R-functions are provided.

AB - In this paper, Multidimensional Cross-Recurrence Quantification Analysis (MdCRQA) is introduced. It is an extension of Multidimensional Recurrence Quantification Analysis (MdRQA), which allows to quantify the (auto-)recurrence properties of a single multidimensional time-series. MdCRQA extends MdRQA to bi-variate cases to allow for the quantification of the co-evolution of two multidimensional time-series. Moreover, it is shown how a Diagonal Cross-Recurrence Profile (DCRP) can be computed from the MdCRQA output that allows to capture time-lagged coupling between two multidimensional time-series. The core concepts of these analyses are described, as well as practical aspects of their application. In the supplementary materials to this paper, implementations of MdCRQA and the DCRP as MatLab- and R-functions are provided.

KW - Psychology

KW - DCRP

KW - MatLab

KW - MdCRQA

KW - Multidimensional Cross-Recurrence Quantification Analysis

KW - multivariate time-series

KW - R

UR - http://www.scopus.com/inward/record.url?scp=85053136980&partnerID=8YFLogxK

U2 - 10.1080/00273171.2018.1512846

DO - 10.1080/00273171.2018.1512846

M3 - Journal articles

C2 - 30569740

AN - SCOPUS:85053136980

VL - 54

SP - 173

EP - 191

JO - Multivariate Behavioral Research

JF - Multivariate Behavioral Research

SN - 0027-3171

IS - 2

ER -

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