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2000•RePEc: Research Papers in EconomicsRequires access

On the Number of Bootstrap Repetitions for BC_a Confidence Intervals

Donald W. K. Andrews, Moshe Buchinsky

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Abstract

This paper considers the problem of choosing the number bootstrap repetitions B to use with the BC_{a} bootstrap confidence intervals introduced by Efron (1987). Because the simulated random variables are ancillary, we seek a choice of B that yields a confidence interval that is close to the ideal bootstrap confidence interval for which B = infinity. We specifiy a three-step method of choosing B that ensures that the lower and upper lengths of the confidence interval deviate from those of the ideal bootstrap confidence interval by at most a small percentage with high probability.

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This paper considers the problem of choosing the number bootstrap repetitions B to use with the BC_{a} bootstrap confidence intervals introduced by Efron (1987). Because the simulated random variables are ancillary, we seek a choice of B that yields a confidence interval that is close to the ideal bootstrap confidence interval for which B = infinity. We specifiy a three-step method of choosing B that ensures that the lower and upper lengths of the confidence interval deviate from those of the ideal bootstrap confidence interval by at most a small percentage with high probability.

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Available abstract

This paper considers the problem of choosing the number bootstrap repetitions B to use with the BC_{a} bootstrap confidence intervals introduced by Efron (1987). Because the simulated random variables are ancillary, we seek a choice of B that yields a confidence interval that is close to the ideal bootstrap confidence interval for which B = infinity. We specifiy a three-step method of choosing B that ensures that the lower and upper lengths of the confidence interval deviate from those of the ideal bootstrap confidence interval by at most a small percentage with high probability.

Key concepts: CDF-based nonparametric confidence interval, Confidence interval, Robust confidence intervals, Mathematics, Statistics, Tolerance interval, Coverage probability, Confidence distribution

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