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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/105235
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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 |
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reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
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CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
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dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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