Consistency of the jackknife-after-bootstrap variance estimator for the bootstrap quantiles of a studentized statistic
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.
Keywords
Cite
@article{arxiv.math/0602328,
title = {Consistency of the jackknife-after-bootstrap variance estimator for the bootstrap quantiles of a studentized statistic},
author = {S. N. Lahiri},
journal= {arXiv preprint arXiv:math/0602328},
year = {2007}
}
Comments
Published 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)