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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

Research output: Contribution to journalJournal article

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An Updated Literature Review of Distance Correlation and Its Applications to Time Series. / Edelmann, Dominic; Fokianos, Konstantinos; Pitsillou, Maria.

In: International Statistical Review, Vol. 87, No. 2, 01.08.2019, p. 237-262.

Research output: Contribution to journalJournal article

Harvard

Edelmann, D, Fokianos, K & Pitsillou, M 2019, 'An Updated Literature Review of Distance Correlation and Its Applications to Time Series', International Statistical Review, vol. 87, no. 2, pp. 237-262. https://doi.org/10.1111/insr.12294

APA

Vancouver

Author

Edelmann, Dominic ; Fokianos, Konstantinos ; Pitsillou, Maria. / An Updated Literature Review of Distance Correlation and Its Applications to Time Series. In: International Statistical Review. 2019 ; Vol. 87, No. 2. pp. 237-262.

Bibtex

@article{9897642a5daf403d8dcf7cb6d3ec53ab,
title = "An Updated Literature Review of Distance Correlation and Its Applications to Time Series",
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.",
keywords = "characteristic function, distance covariance, non‐linear time series, Portmanteau test statistics , spectral density",
author = "Dominic Edelmann and Konstantinos Fokianos and Maria Pitsillou",
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.",
year = "2019",
month = "8",
day = "1",
doi = "10.1111/insr.12294",
language = "English",
volume = "87",
pages = "237--262",
journal = "International Statistical Review",
issn = "0306-7734",
publisher = "International Statistical Institute",
number = "2",

}

RIS

TY - JOUR

T1 - An Updated Literature Review of Distance Correlation and Its Applications to Time Series

AU - Edelmann, Dominic

AU - Fokianos, Konstantinos

AU - Pitsillou, Maria

N1 - 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.

PY - 2019/8/1

Y1 - 2019/8/1

N2 - 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.

AB - 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.

KW - characteristic function

KW - distance covariance

KW - non‐linear time series

KW - Portmanteau test statistics

KW - spectral density

U2 - 10.1111/insr.12294

DO - 10.1111/insr.12294

M3 - Journal article

VL - 87

SP - 237

EP - 262

JO - International Statistical Review

JF - International Statistical Review

SN - 0306-7734

IS - 2

ER -