On extracting probability distribution information from time series

Autores
Kowalski, Andres Mauricio; Martín, María Teresa; Plastino, Angelo; Judge, George
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Time-series (TS) are employed in a variety of academic disciplines. In this paper we focus on extracting probability density functions (PDFs) from TS to gain an insight into the underlying dynamic processes. On discussing this "extraction" problem, we consider two popular approaches that we identify as histograms and Bandt-Pompe. We use an information-theoretic method to objectively compare the information content of the concomitant PDFs. © 2012 by the authors.
Fil: Kowalski, Andres Mauricio. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. 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: Martín, María Teresa. Instituto de Física la Plata (conicet- Universidad Nacional de la Plata); Argentina
Fil: Plastino, Angelo. Universitat de Les Illes Balears; . 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: Judge, George. University of California at Berkeley; Estados Unidos
Materia
BANDT-POMPE
HISTOGRAMS
TIME-SERIES
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:11336/74567
Acceder
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network_acronym_str CONICETDig
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network_name_str CONICET Digital (CONICET)
spelling On extracting probability distribution information from time seriesKowalski, Andres MauricioMartín, María TeresaPlastino, AngeloJudge, GeorgeBANDT-POMPEHISTOGRAMSTIME-SERIEShttps://purl.org/becyt/ford/1.1https://purl.org/becyt/ford/1Time-series (TS) are employed in a variety of academic disciplines. In this paper we focus on extracting probability density functions (PDFs) from TS to gain an insight into the underlying dynamic processes. On discussing this "extraction" problem, we consider two popular approaches that we identify as histograms and Bandt-Pompe. We use an information-theoretic method to objectively compare the information content of the concomitant PDFs. © 2012 by the authors.Fil: Kowalski, Andres Mauricio. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. 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: Martín, María Teresa. Instituto de Física la Plata (conicet- Universidad Nacional de la Plata); ArgentinaFil: Plastino, Angelo. Universitat de Les Illes Balears; . 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: Judge, George. University of California at Berkeley; Estados UnidosMolecular Diversity Preservation International2012-09info: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/11336/74567Kowalski, Andres Mauricio; Martín, María Teresa; Plastino, Angelo; Judge, George; On extracting probability distribution information from time series; Molecular Diversity Preservation International; Entropy; 14; 10; 9-2012; 1829-18411099-4300CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.3390/e14101829info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/1099-4300/14/10/1829info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:07:16Zoai:ri.conicet.gov.ar:11336/74567instacron: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 10:07:16.509CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv On extracting probability distribution information from time series
title On extracting probability distribution information from time series
spellingShingle On extracting probability distribution information from time series
Kowalski, Andres Mauricio
BANDT-POMPE
HISTOGRAMS
TIME-SERIES
title_short On extracting probability distribution information from time series
title_full On extracting probability distribution information from time series
title_fullStr On extracting probability distribution information from time series
title_full_unstemmed On extracting probability distribution information from time series
title_sort On extracting probability distribution information from time series
dc.creator.none.fl_str_mv Kowalski, Andres Mauricio
Martín, María Teresa
Plastino, Angelo
Judge, George
author Kowalski, Andres Mauricio
author_facet Kowalski, Andres Mauricio
Martín, María Teresa
Plastino, Angelo
Judge, George
author_role author
author2 Martín, María Teresa
Plastino, Angelo
Judge, George
author2_role author
author
author
dc.subject.none.fl_str_mv BANDT-POMPE
HISTOGRAMS
TIME-SERIES
topic BANDT-POMPE
HISTOGRAMS
TIME-SERIES
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.1
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Time-series (TS) are employed in a variety of academic disciplines. In this paper we focus on extracting probability density functions (PDFs) from TS to gain an insight into the underlying dynamic processes. On discussing this "extraction" problem, we consider two popular approaches that we identify as histograms and Bandt-Pompe. We use an information-theoretic method to objectively compare the information content of the concomitant PDFs. © 2012 by the authors.
Fil: Kowalski, Andres Mauricio. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. 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: Martín, María Teresa. Instituto de Física la Plata (conicet- Universidad Nacional de la Plata); Argentina
Fil: Plastino, Angelo. Universitat de Les Illes Balears; . 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: Judge, George. University of California at Berkeley; Estados Unidos
description Time-series (TS) are employed in a variety of academic disciplines. In this paper we focus on extracting probability density functions (PDFs) from TS to gain an insight into the underlying dynamic processes. On discussing this "extraction" problem, we consider two popular approaches that we identify as histograms and Bandt-Pompe. We use an information-theoretic method to objectively compare the information content of the concomitant PDFs. © 2012 by the authors.
publishDate 2012
dc.date.none.fl_str_mv 2012-09
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/11336/74567
Kowalski, Andres Mauricio; Martín, María Teresa; Plastino, Angelo; Judge, George; On extracting probability distribution information from time series; Molecular Diversity Preservation International; Entropy; 14; 10; 9-2012; 1829-1841
1099-4300
CONICET Digital
CONICET
url http://hdl.handle.net/11336/74567
identifier_str_mv Kowalski, Andres Mauricio; Martín, María Teresa; Plastino, Angelo; Judge, George; On extracting probability distribution information from time series; Molecular Diversity Preservation International; Entropy; 14; 10; 9-2012; 1829-1841
1099-4300
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.3390/e14101829
info:eu-repo/semantics/altIdentifier/url/https://www.mdpi.com/1099-4300/14/10/1829
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 Molecular Diversity Preservation International
publisher.none.fl_str_mv Molecular Diversity Preservation International
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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score 13.070432

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