Reducing bias without prejudicing sign
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]
|Collections||ANU Research Publications|
|Source:||Annals of the Institute of Statistical Mathematics|
|01_Hall_Reducing_bias_without_2000.pdf||760.42 kB||Adobe PDF||Request a copy|
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