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dc.contributor.authorMatsui, Muneya
dc.contributor.authorMikosch, Thomas
dc.contributor.authorSamorodnitsky, Gennady
dc.date.accessioned2016-12-13T15:47:14Z
dc.date.available2016-12-13T15:47:14Z
dc.date.issued2016-12-13
dc.identifier.urihttps://hdl.handle.net/1813/45412
dc.description.abstractThe 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.en_US
dc.description.sponsorshipMuneya 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.en_US
dc.language.isoen_USen_US
dc.subjectemnpirical characteristic function, distance covariance, stochastic process, test of independenceen_US
dc.titleDistance covariance for stochastic processesen_US


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