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dc.contributor.authorOrbe Mandaluniz, Susan
dc.contributor.authorFerreira García, Eva
dc.contributor.authorRodríguez Poo, Juan Manuel
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2014-05-16T12:16:58Z
dc.date.available2014-05-16T12:16:58Z
dc.date.issued2001
dc.identifier.issn1134-8984
dc.identifier.urihttp://hdl.handle.net/10902/4640
dc.description.abstractIn this paper we propose a new method to estimate nonparametrically a time varying parameter model when some qualitative information from outside data (e.g. seasonality) is available. In this framework we make two main contributions. First, the resulting estimator is shown to belong to the class of generalized ridge estimators and under some conditions its rate of convergence is optimal within its smoothness class. Furthermore, if the outside data information is fullfilled by the underlying model, the estimator shows efficiency gains in small sample sizes. Second, for the implementation process, since the estimation procedure envolves the computation of the inverse of a high order matrix we provide an algorithm that avoids this computation and, also, a data-driven method is derived to select the control parameters. The practical performance of the method is demonstrated in a simulation study and in an application to the demand of soft drinks in Canada.es_ES
dc.format.extent23 p.es_ES
dc.language.isoenges_ES
dc.publisherUniversidad del País Vascoes_ES
dc.rights© Susan Orbe Mandaluniz © Eva Ferreira García © Juan Manuel Rodríguez Pooes_ES
dc.sourceDocumentos de Trabajo BILTOKI, ISSN-e 1134-8984, Nº. 2, 2001es_ES
dc.subject.otherNonparametric regressiones_ES
dc.subject.otherKernel estimatorses_ES
dc.subject.otherTime varying coefficientses_ES
dc.subject.otherBandwidth selectiones_ES
dc.subject.otherEstimation algorithmes_ES
dc.subject.otherSeasonalityes_ES
dc.titleNonparametric estimation of time varying parameters under shape restrictionses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsopenAccesses_ES
dc.type.versionpublishedVersiones_ES


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