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dc.contributor.authorPolanco Martínez, Josué Moisés
dc.contributor.authorFernández Macho, Francisco Javier ORCID
dc.date.accessioned2024-02-08T11:25:05Z
dc.date.available2024-02-08T11:25:05Z
dc.date.issued2014-11-01
dc.identifier.citationComputing in Science & Engineering 16(6) : 68-78 (2014)
dc.identifier.issn1521-9615
dc.identifier.issn1558-366X
dc.identifier.urihttp://hdl.handle.net/10810/65588
dc.description.abstractThis article describes new graphical tools that help with the interpretation of wavelet correlation and cross-correlation analysis, in both bivariate and multivariate cases. We have created an R package called W2CWM2C with the following main functions: Wavelet (Cross) Correlation and Wavelet Multiple (Cross) Correlation. To illustrate its strengths, we use data from several European Union stock market indices, comparing the new graphical output with the classical plots.es_ES
dc.description.sponsorshipFinancial support from the Econometrics Research Group at the University of the Basque Country (UPV/ EHU), Basque Government grants (IT-334-07 and IT-642-13), and the Seventh Framework Programme (FP7) BASE project (no. 308337) is gratefully acknowl- edged
dc.language.isoenges_ES
dc.publisherIEEEes_ES
dc.relationinfo:eu-repo/grantAgreement/EC/FP7/308337
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectmaximal overlap discrete wavelet transformes_ES
dc.subjectwavelet correlation
dc.subjectwavalet cross-correlation
dc.subjectwavelet multiple correlation
dc.subjectwavelet multiple cross-correlation
dc.titlePackage W2CWM2C: description, features and applicationses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.holder© 2014 IEEE*
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/6894486
dc.identifier.doi/10.1109/MCSE.2014.96
dc.contributor.funderEuropean Commission
dc.departamentoesMétodos Cuantitativoses_ES
dc.departamentoeuEkonomia aplikatua III (ekonometria eta estatistika)es_ES


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