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.
@article{1132936569,
author = {Lahiri, S. N.},
title = {Consistency of the jackknife-after-bootstrap variance estimator for the bootstrap quantiles of a Studentized statistic},
journal = {Ann. Statist.},
volume = {33},
number = {1},
year = {2005},
pages = { 2475-2506},
language = {en},
url = {http://dml.mathdoc.fr/item/1132936569}
}
Lahiri, S. N. Consistency of the jackknife-after-bootstrap variance estimator for the bootstrap quantiles of a Studentized statistic. Ann. Statist., Tome 33 (2005) no. 1, pp. 2475-2506. http://gdmltest.u-ga.fr/item/1132936569/