Distance correlation for stochastic processes

Research output: Contribution to journal › Journal article › Research › peer-review

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Distance correlation for stochastic processes. / Matsui, Muneya; Mikosch, Thomas Valentin; Samorodnitsky, Gennady.

In: Probability and Mathematical Statistics, Vol. 37, No. 2, 2017, p. 355-372.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Matsui, M, Mikosch, TV & Samorodnitsky, G 2017, 'Distance correlation for stochastic processes', Probability and Mathematical Statistics, vol. 37, no. 2, pp. 355-372. https://doi.org/10.19195/0208-4147.37.2.9

APA

Matsui, M., Mikosch, T. V., & Samorodnitsky, G. (2017). Distance correlation for stochastic processes. Probability and Mathematical Statistics, 37(2), 355-372. https://doi.org/10.19195/0208-4147.37.2.9

Vancouver

Matsui M, Mikosch TV, Samorodnitsky G. Distance correlation for stochastic processes. Probability and Mathematical Statistics. 2017;37(2):355-372. https://doi.org/10.19195/0208-4147.37.2.9

Author

Matsui, Muneya ; Mikosch, Thomas Valentin ; Samorodnitsky, Gennady. / Distance correlation for stochastic processes. In: Probability and Mathematical Statistics. 2017 ; Vol. 37, No. 2. pp. 355-372.

Bibtex

@article{41b06b72b59744b587040df1706c77c3,
title = "Distance correlation for stochastic processes",
abstract = "The distance covariance of two random vectors is a measure of their dependence. The empirical distance covariance and correlation can be used as statistical tools for testing whether two random vectors are independent. We propose an analog of the distance covariance for two stochastic processes defined on some interval. Their empirical analogs can be used to test the independence of two processes.",
keywords = "Distance covariance, Empirical characteristic function, Stochastic process, Test of independence",
author = "Muneya Matsui and Mikosch, {Thomas Valentin} and Gennady Samorodnitsky",
year = "2017",
doi = "10.19195/0208-4147.37.2.9",
language = "English",
volume = "37",
pages = "355--372",
journal = "Probability and Mathematical Statistics",
issn = "0208-4147",
publisher = "PWN-Polish Scientific Publishers",
number = "2",

}

RIS

TY - JOUR

T1 - Distance correlation for stochastic processes

AU - Matsui, Muneya

AU - Mikosch, Thomas Valentin

AU - Samorodnitsky, Gennady

PY - 2017

Y1 - 2017

N2 - The distance covariance of two random vectors is a measure of their dependence. The empirical distance covariance and correlation can be used as statistical tools for testing whether two random vectors are independent. We propose an analog of the distance covariance for two stochastic processes defined on some interval. Their empirical analogs can be used to test the independence of two processes.

AB - The distance covariance of two random vectors is a measure of their dependence. The empirical distance covariance and correlation can be used as statistical tools for testing whether two random vectors are independent. We propose an analog of the distance covariance for two stochastic processes defined on some interval. Their empirical analogs can be used to test the independence of two processes.

KW - Distance covariance

KW - Empirical characteristic function

KW - Stochastic process

KW - Test of independence

U2 - 10.19195/0208-4147.37.2.9

DO - 10.19195/0208-4147.37.2.9

M3 - Journal article

AN - SCOPUS:85039786736

VL - 37

SP - 355

EP - 372

JO - Probability and Mathematical Statistics

JF - Probability and Mathematical Statistics

SN - 0208-4147

IS - 2

ER -

ID: 194806653