Consistency of the jackknife-after-bootstrap variance estimator for the bootstrap quantiles of a studentized statistic

dc.creatorLahiri, S. N.
dc.date2006-02-15
dc.date.accessioned2026-07-07T08:07:34Z
dc.date.available2026-07-07T08:07:34Z
dc.descriptionEfron [J. Roy. Statist. Soc. Ser. B 54 (1992) 83--111] proposed a computationally efficient method, called the jackknife-after-bootstrap, for estimating the variance of a bootstrap estimator for independent data. For dependent data, a version of the jackknife-after-bootstrap method has been recently proposed by Lahiri [Econometric Theory 18 (2002) 79--98]. In this paper it is shown that the jackknife-after-bootstrap estimators of the variance of a bootstrap quantile are consistent for both dependent and independent data. Results from a simulation study are also presented.
dc.descriptionPublished at http://dx.doi.org/10.1214/009053605000000507 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/math/0602328
dc.identifierhttp://arxiv.org/abs/math/0602328
dc.identifierAnnals of Statistics 2005, Vol. 33, No. 5, 2475-2506
dc.identifierdoi:10.1214/009053605000000507
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/130976
dc.subjectStatistics Theory
dc.subject62G05 (Primary) 62G25 (Secondary)
dc.titleConsistency of the jackknife-after-bootstrap variance estimator for the bootstrap quantiles of a studentized statistic
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