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.
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
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