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ON THE JACKKNIFE-AFTER-BOOTSTRAP METHOD FOR DEPENDENT DATA AND ITS CONSISTENCY PROPERTIES

Published online by Cambridge University Press:  06 March 2002

S.N. Lahiri
S.N. Lahiri
Affiliation:
Iowa State University
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Abstract

Motivated by Efron (1992, Journal of the Royal Statistical Society, Series B 54, 83–111), this paper proposes a version of the moving block jackknife as a method of estimating standard errors of block-bootstrap estimators under dependence. As in the case of independent and identically distributed (i.i.d.) observations, the proposed method merely regroups the values of a statistic from different bootstrap replicates to produce an estimate of its standard error. Consistency of the resulting jackknife standard error estimator is proved for block-bootstrap estimators of the bias and the variance of a large class of statistics. Consistency of Efron's method is also established in similar problems for i.i.d. data.

Type
Research Article
Information
Econometric Theory , Volume 18 , Issue 1 , February 2002 , pp. 79 - 98
Copyright
© 2002 Cambridge University Press

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