Bootstrap variance estimators with truncation

Jun Shao

Statistics & Probability Letters, 1992, vol. 15, issue 2, 95-101

Abstract: The bootstrap estimator of the asymptotic covariance matrix of a function of sample means or sample quantiles is inconsistent in some situations. Using the idea of truncation, we propose a modified bootstrap estimator and show its consistency under weak conditions. A simulation study shows that in terms of finite-sample performance, the gain in using truncation is substantial. The computation of our modified bootstrap estimator is much easier and cheaper than that of the estimator based on the quantiles of the bootstrap distribution. We show by simulation that with the same number of bootstrap replicates (in bootstrap Monte Carlo approximation), the modified bootstrap estimator is more accurate than the estimator based on the interquartile range of the bootstrap distribution.

Keywords: Asymptotic; variance; consistency; sample; mean; sample; quantile; truncation (search for similar items in EconPapers)
Date: 1992
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Citations: View citations in EconPapers (7)

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