Causality and the Entropy Complexity Plane: Robustness and Missing Ordinal Patterns

Autores
Rosso, Osvaldo Aníbal; Carpi, Laura; Saco, Patricia; Gomez Ravetti, Martín; Plastino, Angelo; Larrondo, Hilda Angela
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
We deal here with the issue of determinism versus randomness in time series. One wishes to identify their relative weights in a given time series. Two different tools have been advanced in the literature to such effect, namely, (i) the “causal” entropy–complexity plane [O.A. Rosso, H.A. Larrondo, M.T. Martín, A. Plastino, M.A. Fuentes, Distinguishing noise from chaos, Phys. Rev. Lett. 99 (2007) 154102] and (ii) the estimation of the decay rate of missing ordinal patterns [J.M. Amigó, S. Zambrano, M.A.F. Sanjuán, True and false forbidden patterns in deterministic and random dynamics, Europhys. Lett. 79 (2007) 50001; L.C. Carpi, P.M. Saco, O.A. Rosso, Missing ordinal patterns in correlated noises. Physica A 389 (2010) 2020–2029]. In this work we extend the use of these techniques to address the analysis of deterministic finite time series contaminated with additive noises of different degree of correlation. The chaotic series studied here was via the logistic map (r = 4) to which we added correlated noise (colored noise with f -k Power Spectrum, 0 <- k <2) of varying amplitudes. In such a fashion important insights pertaining to the deterministic component of the original time series can be gained. We find that in the entropy–complexity plane this goal can be achieved without additional computations.
Fil: Rosso, Osvaldo Aníbal. University of Newcastle; Reino Unido. Universidade Federal de Minas Gerais; Brasil. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Formación e Investigación en Enseñanza de las Ciencias; Argentina
Fil: Carpi, Laura. Universidade Federal de Minas Gerais; Brasil. University of Newcastle; Reino Unido
Fil: Saco, Patricia. University of Newcastle; Reino Unido
Fil: Gomez Ravetti, Martín. Universidade Federal de Minas Gerais; Brasil
Fil: Plastino, Angelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; Argentina
Fil: Larrondo, Hilda Angela. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata; Argentina
Materia
Time Series Analysis
Chaos
Entropy complexity
Missing Ordinal Patterns
Noise
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/105235

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network_name_str CONICET Digital (CONICET)
spelling Causality and the Entropy Complexity Plane: Robustness and Missing Ordinal PatternsRosso, Osvaldo AníbalCarpi, LauraSaco, PatriciaGomez Ravetti, MartínPlastino, AngeloLarrondo, Hilda AngelaTime Series AnalysisChaosEntropy complexityMissing Ordinal PatternsNoisehttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1We deal here with the issue of determinism versus randomness in time series. One wishes to identify their relative weights in a given time series. Two different tools have been advanced in the literature to such effect, namely, (i) the “causal” entropy–complexity plane [O.A. Rosso, H.A. Larrondo, M.T. Martín, A. Plastino, M.A. Fuentes, Distinguishing noise from chaos, Phys. Rev. Lett. 99 (2007) 154102] and (ii) the estimation of the decay rate of missing ordinal patterns [J.M. Amigó, S. Zambrano, M.A.F. Sanjuán, True and false forbidden patterns in deterministic and random dynamics, Europhys. Lett. 79 (2007) 50001; L.C. Carpi, P.M. Saco, O.A. Rosso, Missing ordinal patterns in correlated noises. Physica A 389 (2010) 2020–2029]. In this work we extend the use of these techniques to address the analysis of deterministic finite time series contaminated with additive noises of different degree of correlation. The chaotic series studied here was via the logistic map (r = 4) to which we added correlated noise (colored noise with f -k Power Spectrum, 0 <- k <2) of varying amplitudes. In such a fashion important insights pertaining to the deterministic component of the original time series can be gained. We find that in the entropy–complexity plane this goal can be achieved without additional computations.Fil: Rosso, Osvaldo Aníbal. University of Newcastle; Reino Unido. Universidade Federal de Minas Gerais; Brasil. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Formación e Investigación en Enseñanza de las Ciencias; ArgentinaFil: Carpi, Laura. Universidade Federal de Minas Gerais; Brasil. University of Newcastle; Reino UnidoFil: Saco, Patricia. University of Newcastle; Reino UnidoFil: Gomez Ravetti, Martín. Universidade Federal de Minas Gerais; BrasilFil: Plastino, Angelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; ArgentinaFil: Larrondo, Hilda Angela. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata; ArgentinaElsevier Science2012-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/105235Rosso, Osvaldo Aníbal; Carpi, Laura; Saco, Patricia; Gomez Ravetti, Martín; Plastino, Angelo; et al.; Causality and the Entropy Complexity Plane: Robustness and Missing Ordinal Patterns; Elsevier Science; Physica A: Statistical Mechanics and its Applications; 391; 10-2012; 42-550378-4371CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0378437111005772info:eu-repo/semantics/altIdentifier/doi/10.1016/j.physa.2011.07.030info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:58:17Zoai:ri.conicet.gov.ar:11336/105235instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:58:18.033CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Causality and the Entropy Complexity Plane: Robustness and Missing Ordinal Patterns
title Causality and the Entropy Complexity Plane: Robustness and Missing Ordinal Patterns
spellingShingle Causality and the Entropy Complexity Plane: Robustness and Missing Ordinal Patterns
Rosso, Osvaldo Aníbal
Time Series Analysis
Chaos
Entropy complexity
Missing Ordinal Patterns
Noise
title_short Causality and the Entropy Complexity Plane: Robustness and Missing Ordinal Patterns
title_full Causality and the Entropy Complexity Plane: Robustness and Missing Ordinal Patterns
title_fullStr Causality and the Entropy Complexity Plane: Robustness and Missing Ordinal Patterns
title_full_unstemmed Causality and the Entropy Complexity Plane: Robustness and Missing Ordinal Patterns
title_sort Causality and the Entropy Complexity Plane: Robustness and Missing Ordinal Patterns
dc.creator.none.fl_str_mv Rosso, Osvaldo Aníbal
Carpi, Laura
Saco, Patricia
Gomez Ravetti, Martín
Plastino, Angelo
Larrondo, Hilda Angela
author Rosso, Osvaldo Aníbal
author_facet Rosso, Osvaldo Aníbal
Carpi, Laura
Saco, Patricia
Gomez Ravetti, Martín
Plastino, Angelo
Larrondo, Hilda Angela
author_role author
author2 Carpi, Laura
Saco, Patricia
Gomez Ravetti, Martín
Plastino, Angelo
Larrondo, Hilda Angela
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Time Series Analysis
Chaos
Entropy complexity
Missing Ordinal Patterns
Noise
topic Time Series Analysis
Chaos
Entropy complexity
Missing Ordinal Patterns
Noise
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv We deal here with the issue of determinism versus randomness in time series. One wishes to identify their relative weights in a given time series. Two different tools have been advanced in the literature to such effect, namely, (i) the “causal” entropy–complexity plane [O.A. Rosso, H.A. Larrondo, M.T. Martín, A. Plastino, M.A. Fuentes, Distinguishing noise from chaos, Phys. Rev. Lett. 99 (2007) 154102] and (ii) the estimation of the decay rate of missing ordinal patterns [J.M. Amigó, S. Zambrano, M.A.F. Sanjuán, True and false forbidden patterns in deterministic and random dynamics, Europhys. Lett. 79 (2007) 50001; L.C. Carpi, P.M. Saco, O.A. Rosso, Missing ordinal patterns in correlated noises. Physica A 389 (2010) 2020–2029]. In this work we extend the use of these techniques to address the analysis of deterministic finite time series contaminated with additive noises of different degree of correlation. The chaotic series studied here was via the logistic map (r = 4) to which we added correlated noise (colored noise with f -k Power Spectrum, 0 <- k <2) of varying amplitudes. In such a fashion important insights pertaining to the deterministic component of the original time series can be gained. We find that in the entropy–complexity plane this goal can be achieved without additional computations.
Fil: Rosso, Osvaldo Aníbal. University of Newcastle; Reino Unido. Universidade Federal de Minas Gerais; Brasil. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Formación e Investigación en Enseñanza de las Ciencias; Argentina
Fil: Carpi, Laura. Universidade Federal de Minas Gerais; Brasil. University of Newcastle; Reino Unido
Fil: Saco, Patricia. University of Newcastle; Reino Unido
Fil: Gomez Ravetti, Martín. Universidade Federal de Minas Gerais; Brasil
Fil: Plastino, Angelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; Argentina
Fil: Larrondo, Hilda Angela. Universidad Nacional de Mar del Plata. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata; Argentina
description We deal here with the issue of determinism versus randomness in time series. One wishes to identify their relative weights in a given time series. Two different tools have been advanced in the literature to such effect, namely, (i) the “causal” entropy–complexity plane [O.A. Rosso, H.A. Larrondo, M.T. Martín, A. Plastino, M.A. Fuentes, Distinguishing noise from chaos, Phys. Rev. Lett. 99 (2007) 154102] and (ii) the estimation of the decay rate of missing ordinal patterns [J.M. Amigó, S. Zambrano, M.A.F. Sanjuán, True and false forbidden patterns in deterministic and random dynamics, Europhys. Lett. 79 (2007) 50001; L.C. Carpi, P.M. Saco, O.A. Rosso, Missing ordinal patterns in correlated noises. Physica A 389 (2010) 2020–2029]. In this work we extend the use of these techniques to address the analysis of deterministic finite time series contaminated with additive noises of different degree of correlation. The chaotic series studied here was via the logistic map (r = 4) to which we added correlated noise (colored noise with f -k Power Spectrum, 0 <- k <2) of varying amplitudes. In such a fashion important insights pertaining to the deterministic component of the original time series can be gained. We find that in the entropy–complexity plane this goal can be achieved without additional computations.
publishDate 2012
dc.date.none.fl_str_mv 2012-10
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/105235
Rosso, Osvaldo Aníbal; Carpi, Laura; Saco, Patricia; Gomez Ravetti, Martín; Plastino, Angelo; et al.; Causality and the Entropy Complexity Plane: Robustness and Missing Ordinal Patterns; Elsevier Science; Physica A: Statistical Mechanics and its Applications; 391; 10-2012; 42-55
0378-4371
CONICET Digital
CONICET
url http://hdl.handle.net/11336/105235
identifier_str_mv Rosso, Osvaldo Aníbal; Carpi, Laura; Saco, Patricia; Gomez Ravetti, Martín; Plastino, Angelo; et al.; Causality and the Entropy Complexity Plane: Robustness and Missing Ordinal Patterns; Elsevier Science; Physica A: Statistical Mechanics and its Applications; 391; 10-2012; 42-55
0378-4371
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0378437111005772
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.physa.2011.07.030
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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