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On bootstrap estimation of the distribution of the studentized mean |
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| Authors: | Peter Hall Raoul LePage |
| Affiliation: | (1) School of Mathematical Sciences, Centre for Mathematics and its Applications, Australian National University, 0200 Canberra, A.C.T., Australia;(2) Department of Statistics and Probability, Michigan State University, 48824 East Lansing, MI, U.S.A. |
| Abstract: | It is shown that bootstrap methods for estimating the distribution of the Studentized mean produce consistent estimators in quite general contexts, demanding not a lot more than existence of finite mean. In particular, neither the sample mean (suitably normalized) nor the Studentized mean need converge in distribution. It is unnecessary to assume that the sampling distribution is in the domain of attraction of any limit law.Now at Michigan State University |
| Keywords: | Bootstrap central limit theorem consistency domain of attraction domain of partial attraction heavy tail percentile-t method self-normalization Stable law Studentization |
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