Smoothed bootstrap methods for bivariate data

Al Luhayb, A.S.M.; Coolen-Maturi, T.; Coolen, F.P.A.

Abstract

A smoothed bootstrap method is introduced for right-censored data based on the rightcensoring-A(n) assumption introduced by Coolen and Yan (2004), which is a generalization of Hill’s A(n) assumption (Hill, 1968) for right-censored data. The smoothed bootstrap method is compared to Efron’s method for right-censored data (Efron, 1981) through simulations. The comparison is conducted in terms of the coverage of percentile confidence intervals for the quartiles. From the study, it is found that the smoothed bootstrap method mostly performs better than Efron’s method, in particular for small data sets. We also illustrate the use of the method for survival function inference and compare it to a smoothed Kaplan-Meier bootstrap method through simulations.

Citation

Al Luhayb, A., Coolen-Maturi, T., & Coolen, F. (2023). Smoothed bootstrap methods for bivariate data. Journal of statistical theory and practice, 17(3), Article 37. https://doi.org/10.1007/s42519-023-00334-7

• Journal Article Type: Article
• Acceptance Date: May 15, 2023
• Online Publication Date: Jun 13, 2023
• Publication Date: 2023-09
• Deposit Date: May 17, 2023
• Publicly Available Date: Jun 14, 2024
• Journal: Journal of Statistical Theory and Practice
• Electronic ISSN: 1559-8616
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 17
• Issue: 3
• Article Number: 37
• DOI: https://doi.org/10.1007/s42519-023-00334-7
• Public URL: https://durham-repository.worktribe.com/output/1174821
• Publisher URL: https://www.springer.com/journal/42519