Functional limit theorems for inverse bootstrap processes of sample quantiles

It is shown that the accuracy of the bootstrap estimate of the quantile function pertaining to the distribution of the sample q-quantile based on n independent and identically distributed observations is exactly Op(l/n), q [epsilon] (0, 1) fixed. Thi improved considerably by applying smoothed bootstrap estimates. Our results are formulated in terms of functional central limit theorems for the corresponding inverse bootstrap processes.

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Year of publication:	1991
Authors:	Falk, Michael
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 11.1991, 6, p. 529-536
Publisher:	Elsevier
Keywords:	Bootstrap estimate quantile function sample quantile smoothed bootstrap kernel estimate confidence interval functional central limit theorem Brownian motion

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005138044