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dc.rights.licenseopenen_US
dc.contributor.authorPOLANCO-MARTINEZ, Josue,M
dc.contributor.authorMEDINA-ELIZALDE, Martin,A
hal.structure.identifierEnvironnements et Paléoenvironnements OCéaniques [EPOC]
dc.contributor.authorSANCHEZ GONI, Maria
IDREF: 057015627
dc.contributor.authorMUDELSEE, Manfred
dc.date.accessioned2024-06-07T08:14:03Z
dc.date.available2024-06-07T08:14:03Z
dc.date.issued2019-01-01
dc.identifier.issn2073-4859en_US
dc.identifier.urioai:crossref.org:10.32614/rj-2019-035
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/200334
dc.description.abstractEnThis paper presents a computational program named BINCOR (BINned CORrelation) for estimating the correlation between two unevenly spaced time series. This program is also applicable to the situation of two evenly spaced time series not on the same time grid. BINCOR is based on a novel estimation approach proposed by Mudelsee (2010) for estimating the correlation between two climate time series with different timescales. The idea is that autocorrelation (e.g. an AR1 process) means that memory enables values obtained on different time points to be correlated. Binned correlation is performed by resampling the time series under study into time bins on a regular grid, assigning the mean values of the variable under scrutiny within those bins. We present two examples of our BINCOR package with real data: instrumental and paleoclimatic time series. In both applications BINCOR works properly in detecting well-established relationships between the climate records compared.
dc.language.isoENen_US
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.sourcecrossref
dc.title.enBINCOR: An R package for Estimating the Correlation between Two Unevenly Spaced Time Series
dc.title.alternativeR. J.en_US
dc.typeArticle de revueen_US
dc.identifier.doi10.32614/rj-2019-035en_US
dc.subject.halSciences de l'environnementen_US
dc.description.sponsorshipEuropeMarie Curie Initial Training Networken_US
bordeaux.journalThe R Journalen_US
bordeaux.page170-184en_US
bordeaux.volume11en_US
bordeaux.hal.laboratoriesEPOC : Environnements et Paléoenvironnements Océaniques et Continentaux - UMR 5805en_US
bordeaux.issue1en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionCNRSen_US
bordeaux.teamPALEOen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
bordeaux.import.sourcedissemin
hal.identifierhal-04604478
hal.version1
hal.date.transferred2024-06-07T08:14:05Z
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exporttrue
workflow.import.sourcedissemin
dc.rights.ccPas de Licence CCen_US
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