Subsampling the mean of heavy-tailed dependent observations

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• dc.contributor.author Kokoszka, Piotrca
• dc.contributor.author Wolf, Michaelca
• dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa
• dc.date.accessioned 2017-07-26T10:50:04Z
• dc.date.available 2017-07-26T10:50:04Z
• dc.date.issued 2002-02-01
• dc.date.modified 2017-07-23T02:06:41Z
• dc.description.abstract We establish the validity of subsampling confidence intervals for the mean of a dependent series with heavy-tailed marginal distributions. Using point process theory, we study both linear and nonlinear GARCH-like time series models. We propose a data-dependent method for the optimal block size selection and investigate its performance by means of a simulation study.
• dc.format.mimetype application/pdfca
• dc.identifier https://econ-papers.upf.edu/ca/paper.php?id=600
• dc.identifier.citation Journal of Econometrics, 127, 201-224, 2005
• dc.identifier.uri http://hdl.handle.net/10230/384
• dc.language.iso eng
• dc.relation.ispartofseries Economics and Business Working Papers Series; 600
• dc.rights L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
• dc.subject.keyword heavy tails
• dc.subject.keyword linear time series
• dc.subject.keyword subsampling
• dc.subject.keyword Statistics, Econometrics and Quantitative Methods
• dc.title Subsampling the mean of heavy-tailed dependent observationsca
• dc.type info:eu-repo/semantics/workingPaper