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DCovTS: Distance covariance/correlation for time series

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>23/09/2016
<mark>Journal</mark>The R Journal
Issue number2
Volume8
Number of pages17
Pages (from-to)324-340
Publication statusPublished
Original languageEnglish

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.