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Biometrika 1989 76(3):435-446; doi:10.1093/biomet/76.3.435
© 1989 by Biometrika Trust
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Importance sampling and the nested bootstrap

D. V. HINKLEY and S. SHI

Center for Statistical Sciences, The University of Texas at Austin Austin, Texas 78712, U.S.A.

The nested bootstrap is a computer-intensive technique for reducing the statistical error in the ordinary bootstrap. We show how the Monte Carlo technique of importance sampling can be used to substantially reduce the amount of computation needed in a simple double bootstrap confidence limit method.

Key Words: Choice of sample size • Confidence limit • Exponential tilting • Monte Carlo simulation


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