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Reducing bias without prejudicing sign

Hall, Peter; Presnell, B; Turlach, B


Jackknife and bootstrap bias corrections are based on a differencing argument which does not necessarily respect the sign of the true parameter value. Depending on sampling variability they can over-correct, producing a final estimator that is negative when one knows on physical grounds that it should be positive. To overcome this problem we suggest a simple, alternative bootstrap approach, based on biased-bootstrap methods. Our technique has similar properties to the standard uniform-bootstrap...[Show more]

CollectionsANU Research Publications
Date published: 2000
Type: Journal article
Source: Annals of the Institute of Statistical Mathematics


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