Smoothed Bootstrap Methods for Hypothesis Testing

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

Abstract

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.

Citation

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. https://doi.org/10.1007/s42519-024-00370-x

• 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
• Electronic ISSN: 1559-8616
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 18
• Issue: 1
• Article Number: 16
• DOI: https://doi.org/10.1007/s42519-024-00370-x
• Keywords: Smoothed bootstrap, Banks’ bootstrap, Bootstrap confidence interval, Achieved significance level, Efron’s bootstrap
• Public URL: https://durham-repository.worktribe.com/output/2313730