期刊名称：Journal of Modern Applied Statistical Methods
出版年度：2016
卷号：15
期号：2
页码：19
出版社：Wayne State University
摘要：Through Monte Carlo simulations, the performance of six multivariate nonparametric tests for testing the hypothesis of parallelism in profile analysis was studied. In conclusion, the tests based on ranks were as efficient as Hotelling's T2 under multivariate normal distribution. For the heavy tailed distribution, the tests based on signs performed best.
关键词：Monte Carlo simulation; multivariate; nonparametric; profile analysis; heavy tailed
