On the bootstrap and the trimmed mean
We show that the bootstrap approximation to the distribution of the Studentized trimmed mean performs better than the normal approximation, in that it is in error by terms of smaller order than n-1/2, where n denotes sample size. No assumptions are made about symmetry and only mild smoothness conditions are imposed. The method of proof involves differential smoothing of the bootstrap approximant, and is applicable to important related problems such as bootstrap approximation of the distribution of the trimmed variance.
Year of publication: |
1992
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Authors: | Hall, Peter ; Padmanabhan, A. R. |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 41.1992, 1, p. 132-153
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Publisher: |
Elsevier |
Keywords: | Edgeworth expansion quantile smoothing Studentize Winsorize bootstrap trimmed mean |
Saved in:
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