Performance of balanced bootstrap resampling in distribution function and quantile problems
type: Item
instance of: scholarly article
title: Performance of balanced bootstrap resampling in distribution function and quantile problems
zbMATH Open document ID: 0668.60021
DOI: 10.1007/BF01277983
publication date: 1990-01-01T00:00:00Z
review text: It is shown that balanced resampling improves on ordinary uniform resampling when employed to estimate distribution functions or quantiles, but that the improvement is not by an order of magnitude as happens in problems such as bias estimation. Maximum improvement occurs at the centre of the distribution, where performance increases by 175 \%. The increase is only 16 \% at the 2.5 \% and 97.5 \% quantiles. In general the improvement is by the factor \(\{1-\phi^ 2/(1-\Phi)\Phi \}^{-1}\), where \(\Phi\) is the standard normal distribution function and \(\phi =\Phi '\).
Mathematics Subject Classification ID: 60E99
Mathematics Subject Classification ID: 62G05
zbMATH DE Number: 4094484
zbMATH Keywords: bootstrap resampling
zbMATH Keywords: balanced resampling
zbMATH Keywords: bias estimation
MaRDI profile type: Publication
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published in: Zeitschrift für Wahrscheinlichkeitstheorie und Verwandte Gebiete
author: Peter Hall
description: scientific article; zbMATH DE number 4094484