Professor Frank Coolen frank.coolen@durham.ac.uk
Professor
Nonparametric predictive inference bootstrap with application to reproducibility of the two-sample Kolmogorov-Smirnov test
Coolen, F.P.A.; Bin Himd, S.
Authors
S. Bin Himd
Abstract
This paper introduces a new bootstrap method based on the nonparametric predictive inference (NPI) approach to statistics. NPI is a frequentist statistics framework which explicitly focuses on prediction of future observations. The NPI framework enables a bootstrap method (NPI-B) to be introduced which, different to Efron’s classical bootstrap (Ef-B), is aimed at prediction of future observations instead of estimation of population characteristics. A brief initial comparison of NPI-B and Ef-B is presented. The main reason for introducing NPI-B here is for its application to NPI for reproducibility of statistical tests, which is illustrated for the two-sample Kolmogorov–Smirnov test.
Citation
Coolen, F., & Bin Himd, S. (2020). Nonparametric predictive inference bootstrap with application to reproducibility of the two-sample Kolmogorov-Smirnov test. Journal of statistical theory and practice, 14(2), Article 26. https://doi.org/10.1007/s42519-020-00097-5
Journal Article Type | Article |
---|---|
Acceptance Date | Mar 28, 2020 |
Publication Date | Jun 30, 2020 |
Deposit Date | Mar 30, 2020 |
Publicly Available Date | May 7, 2020 |
Journal | Journal of Statistical Theory and Practice |
Electronic ISSN | 1559-8616 |
Publisher | Springer |
Peer Reviewed | Peer Reviewed |
Volume | 14 |
Issue | 2 |
Article Number | 26 |
DOI | https://doi.org/10.1007/s42519-020-00097-5 |
Public URL | https://durham-repository.worktribe.com/output/1305255 |
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Copyright Statement
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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