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dc.creatorOlmedo Fernández, Elenaes
dc.creatorValderas Jaramillo, Juan Manueles
dc.creatorGimeno, Ricardoes
dc.creatorEscot Mangas, Lorenzoes
dc.date.accessioned2024-07-08T11:33:36Z
dc.date.available2024-07-08T11:33:36Z
dc.date.issued2005
dc.identifier.citationOlmedo Fernández, E., Valderas Jaramillo, J.M.,...,Escot Mangas, L. (2005). Nonlinear forecasting in economics: a comparison between comprehension approach versus learning approach. An application to spanish time series. https://hdl.handle.net/11441/161179.
dc.identifier.urihttps://hdl.handle.net/11441/161179
dc.description.abstractIn this paper alternative non-parametric forecasting techniques are analysed, making emphasis in the difference between the reconstruction and the learning approach. The first one is based on Takens Theorem that recovers unknown dynamic properties of the system; it is appropriate in deterministic systems. The second one is a powerful instrument in noisy systems. These techniques are applied to the forecasting of Spanish unemployment and the Industrial Production Index using one-to-one forecasting and comparing the results with the one obtained using nonlinear models, specifically TAR model.es
dc.format.extent20 p.es
dc.language.isoenges
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectForecastinges
dc.subjectReconstructiones
dc.subjectNeural networkses
dc.subjectTakens Theoremes
dc.subjectTAR modeles
dc.titleNonlinear forecasting in economics: a comparison between comprehension approach versus learning approach. An application to spanish time serieses
dc.typeinfo:eu-repo/semantics/reportes
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Economía Aplicada Ies
dc.relation.publisherversionhttps://www.funcas.es/wp-content/uploads/Migracion/Publicaciones/PDF/1132.pdfes

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