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

被引：7
|
作者：
Coolen, Frank P. A. [1 ]
Bin Himd, Sulafah [2 ]
机构：
[1] Univ Durham, Dept Math Sci, Durham, England
[2] King Abdulaziz Univ, Dept Stat, Jeddah, Saudi Arabia
来源：
JOURNAL OF STATISTICAL THEORY AND PRACTICE | 2020年 / 14卷 / 02期
关键词：
Bootstrap; Kolmogorov-Smirnov test; Nonparametric predictive inference; Reproducibility of tests; P-VALUES; REPLICATION;
D O I：
10.1007/s42519-020-00097-5
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
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.
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页数：13
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