Bivariate surrogate techniques: necessity, strengths, and caveats

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 stoc...

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Detalles Bibliográficos
Autores: Andrzejak, Ralph Gregor, Kraskov, Alexander, Stögbauer, Harald, Mormann, Florian, Kreuz, Thomas
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2003
País:España
Institución:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/43634
Acceso en línea:http://hdl.handle.net/10230/43634
http://dx.doi.org/10.1103/PhysRevE.68.066202
Access Level:acceso abierto
Palabra clave:Nonlinear signal analysis
Synchronization
Surrogates
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spelling Bivariate surrogate techniques: necessity, strengths, and caveatsAndrzejak, Ralph GregorKraskov, AlexanderStögbauer, HaraldMormann, FlorianKreuz, ThomasNonlinear signal analysisSynchronizationSurrogatesThe 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.T.K. and F.M. acknowledge support from the Deutsche Forschungsgemeinschaft.American Physical Society202020202003info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/43634http://dx.doi.org/10.1103/PhysRevE.68.066202reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésPhysical Review E. 2003;68:066202info:eu-repo/semantics/openAccessoai:recercat.cat:10230/436342026-05-29T05:05:01Z
dc.title.none.fl_str_mv Bivariate surrogate techniques: necessity, strengths, and caveats
title Bivariate surrogate techniques: necessity, strengths, and caveats
spellingShingle Bivariate surrogate techniques: necessity, strengths, and caveats
Andrzejak, Ralph Gregor
Nonlinear signal analysis
Synchronization
Surrogates
title_short Bivariate surrogate techniques: necessity, strengths, and caveats
title_full Bivariate surrogate techniques: necessity, strengths, and caveats
title_fullStr Bivariate surrogate techniques: necessity, strengths, and caveats
title_full_unstemmed Bivariate surrogate techniques: necessity, strengths, and caveats
title_sort Bivariate surrogate techniques: necessity, strengths, and caveats
dc.creator.none.fl_str_mv Andrzejak, Ralph Gregor
Kraskov, Alexander
Stögbauer, Harald
Mormann, Florian
Kreuz, Thomas
author Andrzejak, Ralph Gregor
author_facet Andrzejak, Ralph Gregor
Kraskov, Alexander
Stögbauer, Harald
Mormann, Florian
Kreuz, Thomas
author_role author
author2 Kraskov, Alexander
Stögbauer, Harald
Mormann, Florian
Kreuz, Thomas
author2_role author
author
author
author
dc.subject.none.fl_str_mv Nonlinear signal analysis
Synchronization
Surrogates
topic Nonlinear signal analysis
Synchronization
Surrogates
description 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.
publishDate 2003
dc.date.none.fl_str_mv 2003
2020
2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/43634
http://dx.doi.org/10.1103/PhysRevE.68.066202
url http://hdl.handle.net/10230/43634
http://dx.doi.org/10.1103/PhysRevE.68.066202
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Physical Review E. 2003;68:066202
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv American Physical Society
publisher.none.fl_str_mv American Physical Society
dc.source.none.fl_str_mv reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
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