Mostra i principali dati dell'item

dcterms.contributor.authorGiordano, Francesco
dcterms.contributor.authorParrella, Maria Lucia
dc.date.accessioned2019-11-08T13:51:51Z
dc.date.available2019-11-08T13:51:51Z
dcterms.date.issued2009
dcterms.identifier.citationGiordano, F. and Parrella, M. L. (2009). “A locally adaptive bandwidth selector for kernel based regression”. DISES Working Paper 3.209, Università degli Studi di Salerno, Dipartimento di Scienze Economiche e Statistiche.it_IT
dcterms.identifier.issn1971-3029it_IT
dcterms.identifier.urihttp://elea.unisa.it:8080/xmlui/handle/10556/3809
dcterms.identifier.urihttp://dx.doi.org/10.14273/unisa-2031
dc.description.abstractThe selection of the smoothing parameter represents a crucial step in the local polynomial regression, because of the implications on the consistency of the nonparametric regression estimator and because of the difficulties in the implementation of the selection procedure. Moreover, to capture the complexity of the unknown regression curve, a local variable bandwidth is needed, which determines an increase in the efficiency and computa- tional costs of such algorithms. This paper focuses on the problem of the automatic selection of a local bandwidth. We propose a slightly different approach with respect to the traditional ones, which does not require ad- ditional computational effort. The empirical performance of the method is shown in the paper through a simulation study.it_IT
dcterms.format.extent38 p.it_IT
dc.language.isoenit_IT
dc.relation.ispartofWorking Papers ; 3.209it_IT
dcterms.sourceUniSa. Sistema Bibliotecario di Ateneoit_IT
dcterms.subjectNonparametric regressionit_IT
dcterms.subjectVariable bandwidth selectionit_IT
dcterms.subjectDerivative estimationit_IT
dcterms.subjectNeural networksit_IT
dcterms.subjectLocal polynomialsit_IT
dcterms.subjectDependent datait_IT
dcterms.titleA locally adaptive bandwidth selector for kernel based regressionit_IT
dcterms.typeWorking Paperit_IT
 Find Full text

Files in questo item

FilesDimensioneFormatoMostra

Nessun files in questo item.

Questo item appare nelle seguenti collezioni

Mostra i principali dati dell'item