Distance covariance for stochastic processes
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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 analogs 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.
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Sponsorship
Muneya Matsui's research is partly supported
by JSPS Grant-in-Aid
for Young Scientists B (16K16023) and Nanzan University
Pache Research Subsidy I-A-2 for the 2016 academic year.
Thomas Mikosch's research is partly supported
by the Danish Research Council Grant DFF-4002-00435.
Gennady Samorodnitsky's research is partly supported by the ARO MURI
grant W911NF-12-1-0385.
Date Issued
2016-12-13
Publisher
Keywords
emnpirical characteristic function, distance covariance, stochastic process, test of independence