An Extension of the Classical Distance Correlation Coefficient for Multivariate Functional Data with Applications

Górecki Tomasz (), Krzyśko Mirosław (), Ratajczak Waldemar () and Wołyński Waldemar ()
Additional contact information
Górecki Tomasz: Faculty of Mathematics and Computer Science, Colorado State University, Colorado, ; United States
Krzyśko Mirosław: Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Poznan, ; Poland
Ratajczak Waldemar: Faculty of Geographical and Geological Sciences, Adam Mickiewicz University, Poznan, ; Poland
Wołyński Waldemar: Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Poznan, ; Poland

Statistics in Transition New Series, 2016, vol. 17, issue 3, 449-466

Abstract: The relationship between two sets of real variables defined for the same individuals can be evaluated by a few different correlation coefficients. For the functional data we have one important tool: canonical correlations. It is not immediately straightforward to extend other similar measures to the context of functional data analysis. In this work we show how to use the distance correlation coefficient for a multivariate functional case.

Keywords: multivariate functional data; functional data analysis; correlation analysis (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.21307/stattrans-2016-032 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:stintr:v:17:y:2016:i:3:p:449-466:n:14

DOI: 10.21307/stattrans-2016-032

Access Statistics for this article

Statistics in Transition New Series is currently edited by Włodzimierz Okrasa

More articles in Statistics in Transition New Series from Statistics Poland
Bibliographic data for series maintained by Peter Golla ().