Bootstrap quantile estimation via importance resampling

Jiaqiao Hu and Zheng Su

Computational Statistics & Data Analysis, 2008, vol. 52, issue 12, 5136-5142

Abstract: We propose an adaptive importance resampling algorithm for estimating bootstrap quantiles of general statistics. The algorithm is especially useful in estimating extreme quantiles and can be easily used to construct bootstrap confidence intervals. Empirical results on real and simulated data sets show that the proposed algorithm is not only superior to the uniform resampling approach, but may also provide more than an order of magnitude of computational efficiency gains.

Date: 2008
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