Wavelets Analysis for Time Series

Autores
Christen, Alejandra
Año de publicación
2019
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Wavelet analysis has been widely used to analyze time series and has countless applications in astronomy. Because of its characteristics it is a method that is well suited to approximate functions, eliminate noise, detect points of change, discontinuities and periodicities. In this article an introduction to the wavelet theory and its use in time series is presented. Numerical simulations and some real examples are developed in the software R.
Facultad de Ciencias Astronómicas y Geofísicas
Materia
Ciencias Astronómicas
Methods: statistical
Methods: analytical
wavelets
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/167767
Acceder
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network_name_str SEDICI (UNLP)
spelling Wavelets Analysis for Time SeriesChristen, AlejandraCiencias AstronómicasMethods: statisticalMethods: analyticalwaveletsWavelet analysis has been widely used to analyze time series and has countless applications in astronomy. Because of its characteristics it is a method that is well suited to approximate functions, eliminate noise, detect points of change, discontinuities and periodicities. In this article an introduction to the wavelet theory and its use in time series is presented. Numerical simulations and some real examples are developed in the software R.Facultad de Ciencias Astronómicas y Geofísicas2019-11info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf127-158http://sedici.unlp.edu.ar/handle/10915/167767enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-24948-7-2info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:44:41Zoai:sedici.unlp.edu.ar:10915/167767Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:44:41.932SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Wavelets Analysis for Time Series
title Wavelets Analysis for Time Series
spellingShingle Wavelets Analysis for Time Series
Christen, Alejandra
Ciencias Astronómicas
Methods: statistical
Methods: analytical
wavelets
title_short Wavelets Analysis for Time Series
title_full Wavelets Analysis for Time Series
title_fullStr Wavelets Analysis for Time Series
title_full_unstemmed Wavelets Analysis for Time Series
title_sort Wavelets Analysis for Time Series
dc.creator.none.fl_str_mv Christen, Alejandra
author Christen, Alejandra
author_facet Christen, Alejandra
author_role author
dc.subject.none.fl_str_mv Ciencias Astronómicas
Methods: statistical
Methods: analytical
wavelets
topic Ciencias Astronómicas
Methods: statistical
Methods: analytical
wavelets
dc.description.none.fl_txt_mv Wavelet analysis has been widely used to analyze time series and has countless applications in astronomy. Because of its characteristics it is a method that is well suited to approximate functions, eliminate noise, detect points of change, discontinuities and periodicities. In this article an introduction to the wavelet theory and its use in time series is presented. Numerical simulations and some real examples are developed in the software R.
Facultad de Ciencias Astronómicas y Geofísicas
description Wavelet analysis has been widely used to analyze time series and has countless applications in astronomy. Because of its characteristics it is a method that is well suited to approximate functions, eliminate noise, detect points of change, discontinuities and periodicities. In this article an introduction to the wavelet theory and its use in time series is presented. Numerical simulations and some real examples are developed in the software R.
publishDate 2019
dc.date.none.fl_str_mv 2019-11
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/167767
url http://sedici.unlp.edu.ar/handle/10915/167767
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-987-24948-7-2
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
127-158
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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score 13.070432

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