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  • 1710.01146

    Rights statement: This is the peer reviewed version of the following article: Edelmann, D., Fokianos, K., and Pitsillou, M. ( 2019) An Updated Literature Review of Distance Correlation and Its Applications to Time Series. International Statistical Review, 87: 237– 262. https://doi.org/10.1111/insr.12294 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/insr.12294/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

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An Updated Literature Review of Distance Correlation and Its Applications to Time Series

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<mark>Journal publication date</mark>1/08/2019
<mark>Journal</mark>International Statistical Review
Issue number2
Volume87
Number of pages26
Pages (from-to)237-262
Publication statusPublished
Early online date27/09/18
Original languageEnglish

Abstract

The concept of distance covariance/correlation was introduced recently to characterise dependence among vectors of random variables. We review some statistical aspects of distance covariance/correlation function, and we demonstrate its applicability to time series analysis. We will see that the auto‐distance covariance/correlation function is able to identify non‐linear relationships and can be employed for testing the i.i.d. hypothesis. Comparisons with other measures of dependence are included.

Bibliographic note

This is the peer reviewed version of the following article: Edelmann, D., Fokianos, K., and Pitsillou, M. ( 2019) An Updated Literature Review of Distance Correlation and Its Applications to Time Series. International Statistical Review, 87: 237– 262. https://doi.org/10.1111/insr.12294 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/insr.12294/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.