High-dimensional multivariate analysis of variance via geometric median and bootstrapping.

ABSTRACT: The geometric median, which is applicable to high-dimensional data, can be viewed as a generalization of the univariate median used in 1-dimensional data. It can be used as a robust estimator for identifying the location of multi-dimensional data and has a wide range of applications in real-world scenarios. This paper explores the problem of high-dimensional multivariate analysis of variance (MANOVA) using the geometric median. A maximum-type statistic that relies on the differences between the geometric medians among various groups is introduced. The distribution of the new test statistic is derived under the null hypothesis using Gaussian approximations, and its consistency under the alternative hypothesis is established. To approximate the distribution of the new statistic in high dimen

SUBMITTER: Cheng G 

PROVIDER: S-EPMC11381952 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature