Whittle pseudo-maximum likelihood estimation for nonstationary time series

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 dc.contributor.author Velasco, Carlos dc.contributor.author Robinson, Peter M. dc.date.accessioned 2009-06-16T13:21:40Z dc.date.available 2009-06-16T13:21:40Z dc.date.issued 2000-12 dc.identifier.bibliographicCitation Journal of the American Statistical Association. 2000, vol. 95, nº 452, p. 1229-1243 dc.identifier.issn 0162-1459 dc.identifier.uri http://hdl.handle.net/10016/4434 dc.description.abstract Whittle pseudo-maximum likelihood estimates of parameters for stationary time series have been found to be consistent and asymptotically normal in the presence of long-range dependence. Generalizing the definition of the memory parameter d, we extend these results to include possibly nonstationary (.5 $\leq d <$ 1) or antipersistent (-.5 $< d <$ 0) observations. Using adequate data tapers, we can apply this estimation technique to any degree of nonstationarity d ≥ .5 without a priori knowledge of the memory of the series. We analyze the performance of the estimates on simulated and real data. dc.format.mimetype application/pdf dc.language.iso eng dc.publisher American Statistical Association dc.rights © American Statistical Association dc.subject.other Frequency domain estimation dc.subject.other Long-range dependence dc.subject.other Nonstationary fractional models dc.subject.other Nonstationary long memory time series dc.subject.other Tapering dc.title Whittle pseudo-maximum likelihood estimation for nonstationary time series dc.type article dc.type.review PeerReviewed dc.description.status Publicado dc.relation.publisherversion http://www.jstor.org/stable/2669763 dc.subject.eciencia Economía dc.rights.accessRights openAccess
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