UNIVERSITY OF CAMBRIDGE
STATISTICAL LABORATORY
DEPARTMENT OF PURE MATHEMATICS AND MATHEMATICAL STATISTICS
16 MILL LANE, CAMBRIDGE CB2 1SB
Tel: (01223) 337958
Fax: (01223) 337956
SEMINAR
Room S27, Statistical Laboratory
Tuesday, 19 May, 1998
2.00 p.m.
Peter Hall (Australian National University)
INTENTIONALLY BIASED BOOTSTRAP METHODS
A class of weighted bootstrap techniques, called biased bootstrap or
b-bootstrap methods, is proposed. It is motivated by the need to
adjust more conventional empirical methods, such as the `uniform'
bootstrap, in a surgical way so as to alter some of their features
while leaving others unchanged. Depending on the nature of the
adjustment, the b-bootstrap can be used to reduce bias, or reduce
variance, or render some characteristic equal to a predetermined
quantity. Examples of the latter application include a b-bootstrap
approach to hypothesis testing in nonparametric contexts, where the
b-bootstrap enables simulation `under the null hypothesis', even when
the latter is false; and a b-bootstrap competitor to Tibshirani's
variance stabilisation method. An example of the bias-reduction
application is adjustment of Nadaraya-Watson estimators of a
regression mean, to make them competitive with local linear
smoothing. Other applications include density estimation under
constraints, outlier trimming, sensitivity analysis, skewness or
kurtosis reduction and shrinkage.
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ALL INTERESTED ARE WELCOME
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For the full list of Statistical Laboratory seminars being given in the
Easter Term, please see our web page
http://www.statslab.cam.ac.uk/Dept/Seminars
Enquiries to: [log in to unmask]
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