Speaker
Dr
Maria Pitsillou
(Department of Mathematics & Statistics, Cyprus)
Description
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)
Co-author
Prof.
Konstantinos Fokianos
(Department of Mathematics & Statistics, University of Cyprus)
