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

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Abstract

Efron [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. © Institute of Mathematical Statistics, 2005.

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Lahiri, S. N. (2005). Consistency of the jackknife-after-bootstrap variance estimator for the bootstrap quantiles of a studentized statistic. Annals of Statistics, 33(5), 2475–2506. https://doi.org/10.1214/009053605000000507

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