Nonparametric Predictive Inference Bootstrap with Application to Reproducibility of the Two-Sample Kolmogorov–Smirnov Test

被引：0

作者：

Frank P. A. Coolen

Sulafah Bin Himd

机构：

[1] Durham University,Department of Mathematical Sciences

[2] King Abdulaziz University,Department of Statistics

来源：

Journal of Statistical Theory and Practice | 2020年 / 14卷

关键词：

Bootstrap; Kolmogorov–Smirnov test; Nonparametric predictive inference; Reproducibility of tests;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

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.

引用

共 50 条

[1] Nonparametric Predictive Inference Bootstrap with Application to Reproducibility of the Two-Sample Kolmogorov-Smirnov Test
Coolen, Frank P. A.
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[J]. JOURNAL OF STATISTICAL THEORY AND PRACTICE, 2020, 14 (02)
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