The R Journal: article published in 2016, volume 8:2

dCovTS: Distance Covariance/Correlation for Time Series
Maria Pitsillou and Konstantinos Fokianos , The R Journal (2016) 8:2, pages 324-340.

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.

Received: 2016-04-18; online 2016-10-21
CRAN packages: energy, doParallel, portes, MTS , CRAN Task Views implied by cited CRAN packages: TimeSeries, Multivariate


CC BY 4.0
This article is licensed under a Creative Commons Attribution 3.0 Unported license .

@article{RJ-2016-049,
  author = {Maria Pitsillou and Konstantinos Fokianos},
  title = {{dCovTS: Distance Covariance/Correlation for Time Series}},
  year = {2016},
  journal = {{The R Journal}},
  url = {https://journal.r-project.org/archive/2016/RJ-2016-049/index.html},
  pages = {324--340},
  volume = {8},
  number = {2}
}