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DCovTS: Distance covariance/correlation for time series

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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DCovTS: Distance covariance/correlation for time series. / Pitsillou, M.; Fokianos, K.
In: The R Journal, Vol. 8, No. 2, 23.09.2016, p. 324-340.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Pitsillou, M & Fokianos, K 2016, 'DCovTS: Distance covariance/correlation for time series', The R Journal, vol. 8, no. 2, pp. 324-340. <https://journal.r-project.org/archive/2016/RJ-2016-049/index.html>

APA

Pitsillou, M., & Fokianos, K. (2016). DCovTS: Distance covariance/correlation for time series. The R Journal, 8(2), 324-340. https://journal.r-project.org/archive/2016/RJ-2016-049/index.html

Vancouver

Pitsillou M, Fokianos K. DCovTS: Distance covariance/correlation for time series. The R Journal. 2016 Sept 23;8(2):324-340.

Author

Pitsillou, M. ; Fokianos, K. / DCovTS: Distance covariance/correlation for time series. In: The R Journal. 2016 ; Vol. 8, No. 2. pp. 324-340.

Bibtex

@article{be7d6c76f78e42c8a4ed162053eb46b2,
title = "DCovTS: Distance covariance/correlation for time series",
abstract = "The distance covariance function is a new measure of dependence between random vectors. We drop the assumption of iid data to introduce distance covariance for time series. The R package dCovTS provides functions that compute and plot distance covariance and correlation functions for both univariate and multivariate time series. Additionally it includes functions for testing serial independence based on distance covariance. This paper describes the theoretical background of distance covariance methodology in time series and discusses in detail the implementation of these methods with the R package dCovTS.",
author = "M. Pitsillou and K. Fokianos",
year = "2016",
month = sep,
day = "23",
language = "English",
volume = "8",
pages = "324--340",
journal = "The R Journal",
issn = "2073-4859",
publisher = "R Foundation for Statistical Computing",
number = "2",

}

RIS

TY - JOUR

T1 - DCovTS: Distance covariance/correlation for time series

AU - Pitsillou, M.

AU - Fokianos, K.

PY - 2016/9/23

Y1 - 2016/9/23

N2 - The distance covariance function is a new measure of dependence between random vectors. We drop the assumption of iid data to introduce distance covariance for time series. The R package dCovTS provides functions that compute and plot distance covariance and correlation functions for both univariate and multivariate time series. Additionally it includes functions for testing serial independence based on distance covariance. This paper describes the theoretical background of distance covariance methodology in time series and discusses in detail the implementation of these methods with the R package dCovTS.

AB - The distance covariance function is a new measure of dependence between random vectors. We drop the assumption of iid data to introduce distance covariance for time series. The R package dCovTS provides functions that compute and plot distance covariance and correlation functions for both univariate and multivariate time series. Additionally it includes functions for testing serial independence based on distance covariance. This paper describes the theoretical background of distance covariance methodology in time series and discusses in detail the implementation of these methods with the R package dCovTS.

M3 - Journal article

VL - 8

SP - 324

EP - 340

JO - The R Journal

JF - The R Journal

SN - 2073-4859

IS - 2

ER -