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https://hdl.handle.net/11000/35204
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Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | GARCIA AROCA, CARLOS | - |
dc.contributor.author | Martínez Mayoral, Mª Asunción | - |
dc.contributor.author | Morales-Socuéllamos, Javier | - |
dc.contributor.other | Departamentos de la UMH::Estadística, Matemáticas e Informática | es_ES |
dc.date.accessioned | 2025-01-23T20:35:47Z | - |
dc.date.available | 2025-01-23T20:35:47Z | - |
dc.date.created | 2024-04 | - |
dc.identifier.citation | Software Impacts 20 (2024) 100644 | es_ES |
dc.identifier.issn | 2665-9638 | - |
dc.identifier.uri | https://hdl.handle.net/11000/35204 | - |
dc.description.abstract | alPCA 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.format | application/pdf | es_ES |
dc.format.extent | 3 | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Elsevier | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Forecasting | es_ES |
dc.subject | Time series | es_ES |
dc.subject | Forecasting combination | es_ES |
dc.subject | Principal component analysis | es_ES |
dc.subject.other | CDU::5 - Ciencias puras y naturales::50 - Generalidades sobre las ciencias puras | es_ES |
dc.title | alPCA:Anautomaticsoftwarefortheselectionandcombinationofforecasts in monthlyseries | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.simpa.2024.100644 | es_ES |
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