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dc.contributor.authorRoueff, F.en_US
dc.contributor.authorTaqqu, Murad S.en_US
dc.date.accessioned2019-08-28T13:31:18Z
dc.date.available2019-08-28T13:31:18Z
dc.date.issued2009-09-01
dc.identifierhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000269189200004&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=6e74115fe3da270499c3d65c9b17d654
dc.identifier.citationF. Roueff, M.S. Taqqu. 2009. "Asymptotic normality of wavelet estimators of the memory parameter for linear processes." JOURNAL OF TIME SERIES ANALYSIS, Volume 30, Issue 5, pp. 534 - 558 (25). https://doi.org/10.1111/j.1467-9892.2009.00627.x
dc.identifier.issn0143-9782
dc.identifier.urihttps://hdl.handle.net/2144/37421
dc.description.abstractWe consider linear processes, not necessarily Gaussian, with long, short or negative memory. The memory parameter is estimated semi‐parametrically using wavelets from a sample X1,…, Xn of the process. We treat both the log‐regression wavelet estimator and the wavelet Whittle estimator. We show that these estimators are asymptotically normal as the sample size n → ∞ and we obtain an explicit expression for the limit variance. These results are derived from a general result on the asymptotic normality of the scalogram for linear processes, conveniently centred and normalized. The scalogram is an array of quadratic forms of the observed sample, computed from the wavelet coefficients of this sample. In contrast to quadratic forms computed on the basis of Fourier coefficients such as the periodogram, the scalogram involves correlations which do not vanish as the sample size n → ∞.en_US
dc.description.sponsorshipWe thank the referee for his comments. Murad S. Taqqu thanks Telecom ParisTech for their hospitality. This research was partially supported by the NSF Grants DMS-0505747 and DMS-0706786 at Boston University. (DMS-0505747 - NSF; DMS-0706786 - NSF)en_US
dc.format.extent534 - 558 (25)en_US
dc.languageEnglish
dc.publisherWILEY-BLACKWELL PUBLISHING, INCen_US
dc.relation.ispartofJOURNAL OF TIME SERIES ANALYSIS
dc.subjectMathematics, interdisciplinary applicationsen_US
dc.subjectStatistics & probabilityen_US
dc.subjectMathematicsen_US
dc.subjectSpectral analysisen_US
dc.subjectWavelet analysisen_US
dc.subjectLong-range dependenceen_US
dc.subjectSemiparametric estimationen_US
dc.subjectEconometricsen_US
dc.titleAsymptotic normality of wavelet estimators of the memory parameter for linear processesen_US
dc.typeArticleen_US
dc.description.versionFirst author draften_US
dc.identifier.doi10.1111/j.1467-9892.2009.00627.x
pubs.elements-sourceweb-of-scienceen_US
pubs.notesEmbargo: Not knownen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, College of Arts & Sciencesen_US
pubs.organisational-groupBoston University, College of Arts & Sciences, Department of Mathematics & Statisticsen_US
pubs.publication-statusPublisheden_US
dc.identifier.orcid0000-0002-1145-9082 (Taqqu, MS)
dc.identifier.mycv54248


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