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Smoothed bootstrap methods for bivariate data

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

Authors

A.S.M. Al Luhayb



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

Files

This file is under embargo until Jun 14, 2024 due to copyright restrictions.




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