DCovTS: Distance covariance/correlation for time series

10Citations
Citations of this article
680Readers
Mendeley users who have this article in their library.

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.

Cite

CITATION STYLE

APA

Pitsillou, M., & Fokianos, K. (2016). DCovTS: Distance covariance/correlation for time series. R Journal, 8(2), 324–340. https://doi.org/10.32614/rj-2016-049

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free