Use Single SignOn (SSO) to login with your home institute's account and login service.
14-18 August 2017
Uppsala University
Europe/Stockholm timezone

Testing independence for multivariate time series by the auto-distance correlation matrix

15 Aug 2017, 11:30
Ångströmslaboratoriet (Uppsala University)


Uppsala University



Dr Maria Pitsillou (Department of Mathematics & Statistics, Cyprus)


We introduce the notions of multivariate auto-distance covariance and correlation functions for time series analysis. These concepts have been recently discussed in the context of both independent and dependent data but we extend them in a different direction by putting forward their matrix version. Their matrix version allows us to identify possible interrelationships among the components of a multivariate time series. Interpretation and consistent estimators of these new concepts are discussed. Additionally, we develop a test for testing the i.i.d. hypothesis for multivariate time series data. The resulting test statistic performs better than the standard multivariate Ljung-Box test statistic. All the above methodology is included in the R package dCovTS which is briefly introduced in this talk.

Primary author

Dr Maria Pitsillou (Department of Mathematics & Statistics, Cyprus)


Prof. Konstantinos Fokianos (Department of Mathematics & Statistics, University of Cyprus)

Presentation Materials

Your browser is out of date!

Update your browser to view this website correctly. Update my browser now