Averaged Singular Integral Estimation as a Bias Reduction Technique

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dc.contributor.author Delgado, Miguel A.
dc.contributor.author Vidal-Sanz, Jose M.
dc.date.accessioned 2009-05-29T11:55:57Z
dc.date.available 2009-05-29T11:55:57Z
dc.date.issued 2002
dc.identifier.bibliographicCitation Journal of Multivariate Analysis. 2002, vol. 80, nº 1, p. 127-137
dc.identifier.issn 0047-259X
dc.identifier.uri http://hdl.handle.net/10016/2453
dc.description.abstract This paper proposes an averaged version of singular integral estimators, whose bias achieves higher rates of convergence under smoothing assumptions. We derive exact bias bounds, without imposing smoothing assumptions, which are a basis for deriving the rates of convergence under differentiability assumptions.
dc.format.mimetype text/plain
dc.format.mimetype application/pdf
dc.language.iso eng
dc.language.iso eng
dc.publisher Elsevier
dc.rights © Elsevier
dc.subject.other global rates of convergence for the bias
dc.subject.other singular integral estimators
dc.subject.other generalized jackknife
dc.subject.other bias reduction techniques
dc.title Averaged Singular Integral Estimation as a Bias Reduction Technique
dc.type article
dc.type.review PeerReviewed
dc.description.status Publicado
dc.relation.publisherversion http://dx.doi.org/10.1006/jmva.2000.1978
dc.subject.eciencia Economía
dc.identifier.doi 10.1006/jmva.2000.1978
dc.rights.accessRights openAccess
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