A High-Dimensional Nonparametric Multivariate Test for Mean Vector.

ABSTRACT: This work is concerned with testing the population mean vector of nonnormal high-dimensional multivariate data. Several tests for high-dimensional mean vector, based on modifying the classical Hotelling T² test, have been proposed in the literature. Despite their usefulness, they tend to have unsatisfactory power performance for heavy-tailed multivariate data, which frequently arise in genomics and quantitative finance. This paper proposes a novel high-dimensional nonparametric test for the population mean vector for a general class of multivariate distributions. With the aid of new tools in modern probability theory, we proved that the limiting null distribution of the proposed test is normal under mild conditions when p is substantially larger than n. We f

SUBMITTER: Wang L 

PROVIDER: S-EPMC4734767 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature