Please use this identifier to cite or link to this item: https://hdl.handle.net/11000/35204
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dc.contributor.authorGARCIA AROCA, CARLOS-
dc.contributor.authorMartínez Mayoral, Mª Asunción-
dc.contributor.authorMorales-Socuéllamos, Javier-
dc.contributor.otherDepartamentos de la UMH::Estadística, Matemáticas e Informáticaes_ES
dc.date.accessioned2025-01-23T20:35:47Z-
dc.date.available2025-01-23T20:35:47Z-
dc.date.created2024-04-
dc.identifier.citationSoftware Impacts 20 (2024) 100644es_ES
dc.identifier.issn2665-9638-
dc.identifier.urihttps://hdl.handle.net/11000/35204-
dc.description.abstractalPCA is a software coded in R and designed to automatically combine predictions from a collection of individual forecasting methods that integrate it. It employs three categories of weights derived from the PCA scores, and decision rules to determine the optimal combination of these methods. alPCA serves as an automated component within the artificial intelligence toolkit for monthly time series processing with the objective of obtaining the best forecast.es_ES
dc.formatapplication/pdfes_ES
dc.format.extent3es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectForecastinges_ES
dc.subjectTime serieses_ES
dc.subjectForecasting combinationes_ES
dc.subjectPrincipal component analysises_ES
dc.subject.otherCDU::5 - Ciencias puras y naturales::50 - Generalidades sobre las ciencias purases_ES
dc.titlealPCA:Anautomaticsoftwarefortheselectionandcombinationofforecasts in monthlyserieses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherversionhttps://doi.org/10.1016/j.simpa.2024.100644es_ES
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Artículos Estadística, Matemáticas e Informática


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