Sample size determination of a nonparametric test based on weighted -Wasserstein distance

详细信息    查看全文

• 作者：Jim X. Xiang ^{jxiang@its.jnj.com}
• 关键词：primary ; 62G10 ; secondary ; 62G20
• 刊名：Statistics & Probability Letters
• 出版年：2017
• 出版时间：April 2017
• 年：2017
• 卷：123
• 期：Complete
• 页码：160-164
• 全文大小：373 K
• 卷排序：123

文摘

In this paper we derive a formula for the sample size of a nonparametric test based on weighted L2L2-Wasserstein distance with a known alternative. As an example we apply the formula to determine the sample size for a hypothesis testing from the Tukey’s contaminated distribution model. The reliability of the sample size formula is evaluated in terms of type I errors and the powers of the test. The Monte Carlo simulation results show that the test based on the weighted L2L2-Wasserstein distance performs equally well as the Anderson–Darling test and is superior to the Kolmogorov–Smirnov and the Cramer–von Mises tests.