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Smoothed Bootstrap Methods for Hypothesis Testing

Al Luhayb, Asamh S. M.; Coolen-Maturi, Tahani; Coolen, Frank P. A.

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Asamh S. M. Al Luhayb


This paper demonstrates the application of smoothed bootstrap methods and Efron’s methods for hypothesis testing on real-valued data, right-censored data and bivariate data. The tests include quartile hypothesis tests, two sample medians and Pearson and Kendall correlation tests. Simulation studies indicate that the smoothed bootstrap methods outperform Efron’s methods in most scenarios, particularly for small datasets. The smoothed bootstrap methods provide smaller discrepancies between the actual and nominal error rates, which makes them more reliable for testing hypotheses.


Al Luhayb, A. S. M., Coolen-Maturi, T., & Coolen, F. P. A. (2024). Smoothed Bootstrap Methods for Hypothesis Testing. Journal of statistical theory and practice, 18(1), Article 16.

Journal Article Type Article
Acceptance Date Feb 7, 2024
Online Publication Date Mar 4, 2024
Publication Date Mar 1, 2024
Deposit Date Apr 23, 2024
Publicly Available Date Apr 24, 2024
Journal Journal of Statistical Theory and Practice
Publisher Springer
Peer Reviewed Peer Reviewed
Volume 18
Issue 1
Article Number 16
Keywords Smoothed bootstrap, Banks’ bootstrap, Bootstrap confidence interval, Achieved significance level, Efron’s bootstrap
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