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Bivariate surrogate techniques: necessity, strengths, and caveats

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dc.contributor.author Andrzejak, Ralph Gregor
dc.contributor.author Kraskov, Alexander
dc.contributor.author Stögbauer, Harald
dc.contributor.author Mormann, Florian
dc.contributor.author Kreuz, Thomas
dc.date.accessioned 2020-02-18T13:54:32Z
dc.date.available 2020-02-18T13:54:32Z
dc.date.issued 2003
dc.identifier.citation Andrzejak RG, Kraskov A, Stogbauer H, Mormann F, Kreuz T. Bivariate surrogate techniques: necessity, strengths, and caveats. Phys Rev E. 2003;68:066202. DOI: 10.1103/PhysRevE.68.066202
dc.identifier.issn 2470-0045
dc.identifier.uri http://hdl.handle.net/10230/43634
dc.description.abstract The concept of surrogates allows testing results from time series analysis against specified null hypotheses. In application to bivariate model dynamics we here compare different types of surrogates, each designed to test against a different null hypothesis, e.g., an underlying bivariate linear stochastic process. Two measures that aim at a characterization of interdependence between nonlinear deterministic dynamics were used as discriminating statistics. We analyze eight different stochastic and deterministic models not only to demonstrate the power of the surrogates, but also to reveal some pitfalls and limitations.
dc.description.sponsorship T.K. and F.M. acknowledge support from the Deutsche Forschungsgemeinschaft.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher American Physical Society
dc.relation.ispartof Physical Review E. 2003;68:066202
dc.title Bivariate surrogate techniques: necessity, strengths, and caveats
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1103/PhysRevE.68.066202
dc.subject.keyword Nonlinear signal analysis
dc.subject.keyword Synchronization
dc.subject.keyword Surrogates
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion


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