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

Fokianos, K. and Pitsillou, M. (2018) Testing independence for multivariate time series via the auto-distance correlation matrix. Biometrika, 105 (2). pp. 337-352. ISSN 0006-3444

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Abstract

We introduce the matrix multivariate auto-distance covariance and correlation functions for time series, discuss their interpretation and develop consistent estimators for practical implementation. We also develop a test of the independent and identically distributed hypothesis for multivariate time series data and show that it performs better than the multivariate Ljung–Box test. We discuss computational aspects and present a data example to illustrate the method.

Item Type:
Journal Article
Journal or Publication Title:
Biometrika
Additional Information:
This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Biometrika following peer review. The definitive publisher-authenticated version K Fokianos, M Pitsillou; Testing independence for multivariate time series via the auto-distance correlation matrix, Biometrika, Volume 105, Issue 2, 1 June 2018, Pages 337–352, https://doi.org/10.1093/biomet/asx082
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1100/1101
Subjects:
ID Code:
127720
Deposited By:
Deposited On:
01 Oct 2018 09:04
Refereed?:
Yes
Published?:
Published
Last Modified:
05 Apr 2020 05:14