Bootstrap for the sample mean and for U-Statistics of stationary processes

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dc.contributor.authorShapirov, Olimjon Sh.
dc.contributor.authorWendler, Martin
dc.date.accessioned2009-12-14T10:52:49Z
dc.date.available2009-12-14T10:52:49Z
dc.date.issued2009-12-14T10:52:49Z
dc.description.abstractThe validity of various bootstrapping methods has been proved for the sample mean of strongly mixing data. But in many applications, there appear nonlinear statistics of processes that are not strongly mixing. We investigate the nonoverlapping block bootstrap for functionals of absolutely regular processes, which occur from chaotic dynamical systems. We establish the strong consistency of the bootstrap distribution estimator not only for the sample mean, but also for U-statistics, which include examples as Gini’s mean difference or the x 2-test statistic. AMS subject classification: 62G09, 60G10.en
dc.identifier.urihttp://hdl.handle.net/2003/26549
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-12781
dc.language.isoen
dc.relation.ispartofseriesDiscussion Paper / SFB 823;35/2009
dc.subjectBlock bootstrapen
dc.subjectFunctional of absolutely regular sequenceen
dc.subjectStrongly mixing sequenceen
dc.subjectU-Statisticsen
dc.subject.ddc310
dc.subject.ddc330
dc.subject.ddc620
dc.titleBootstrap for the sample mean and for U-Statistics of stationary processesen
dc.typeText
dc.type.publicationtypereport
dcterms.accessRightsopen access

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