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dc.contributor.authorBai, Shuyangen_US
dc.contributor.authorTaqqu, Murad S.en_US
dc.date.accessioned2020-01-22T20:01:54Z
dc.date.available2020-01-22T20:01:54Z
dc.date.issued2017-12-01
dc.identifierhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000418371600003&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=6e74115fe3da270499c3d65c9b17d654
dc.identifier.citationShuyang Bai, Murad S Taqqu. 2017. "ON THE VALIDITY OF RESAMPLING METHODS UNDER LONG MEMORY." ANNALS OF STATISTICS, Volume 45, Issue 6, pp. 2365 - 2399 (35). https://doi.org/10.1214/16-AOS1524
dc.identifier.issn0090-5364
dc.identifier.urihttps://hdl.handle.net/2144/39138
dc.description.abstractFor long-memory time series, inference based on resampling is of crucial importance, since the asymptotic distribution can often be non-Gaussian and is difficult to determine statistically. However, due to the strong dependence, establishing the asymptotic validity of resampling methods is nontrivial. In this paper, we derive an efficient bound for the canonical correlation between two finite blocks of a long-memory time series. We show how this bound can be applied to establish the asymptotic consistency of subsampling procedures for general statistics under long memory. It allows the subsample size b to be o(n), where n is the sample size, irrespective of the strength of the memory. We are then able to improve many results found in the literature. We also consider applications of subsampling procedures under long memory to the sample covariance, M-estimation and empirical processes.en_US
dc.description.sponsorshipSupported in part by the NSF Grant DMS-13-09009 at Boston University. (DMS-13-09009 - NSF at Boston University)en_US
dc.format.extentp. 2365 - 2399en_US
dc.languageEnglish
dc.language.isoen_US
dc.publisherINST MATHEMATICAL STATISTICSen_US
dc.relation.ispartofANNALS OF STATISTICS
dc.subjectScience & technologyen_US
dc.subjectPhysical sciencesen_US
dc.subjectStatistics & probabilityen_US
dc.subjectMathematicsen_US
dc.subjectLong memoryen_US
dc.subjectLong-range dependenceen_US
dc.subjectResamplingen_US
dc.subjectSubsamplingen_US
dc.subjectBlock samplingen_US
dc.subjectNoncentral limit theoremsen_US
dc.subjectCanonical correlationen_US
dc.subjectCentral limit-theoremsen_US
dc.subjectSampling window methoden_US
dc.subjectTime-seriesen_US
dc.subjectSubsampling inferenceen_US
dc.subjectNonlinear functionalsen_US
dc.subjectRang dependenceen_US
dc.subjectGaussian fieldsen_US
dc.subjectBlock bootstrapen_US
dc.subjectAutocorrelationsen_US
dc.subjectAutocovariancesen_US
dc.subjectStatisticsen_US
dc.subjectEconometricsen_US
dc.subjectStatistics & probabilityen_US
dc.titleOn the validity of resampling methods under long memoryen_US
dc.typeArticleen_US
dc.description.versionAccepted manuscripten_US
dc.identifier.doi10.1214/16-AOS1524
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, Murad S)
dc.identifier.mycv54265


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