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Two-Sample High Dimensional Mean Test Based On Prepivots | | Santu Ghosh
; Deepak Nag Ayyala
; Rafael Hellebuyck
; | | Date: |
13 Mar 2020 | | Abstract: | Testing equality of mean vectors is a very commonly used criterion when
comparing two multivariate random variables. Traditional tests such as
Hotelling’s T-squared become either unusable or output small power when the
number of variables is greater than the combined sample size. In this paper,
w}e propose a test using both prepivoting and Edgeworth expansion for testing
the equality of two population mean vectors in the "large p, small n" setting.
The asymptotic null distribution of the test statistic is derived and it is
shown that the power of suggested test converges to one under certain
alternatives when both n and p increase to infinity against sparse
alternatives. Finite sample performance of the proposed test statistic is
compared with other recently developed tests designed to also handle the "large
p, small n" situation through simulations. The proposed test achieves
competitive rates for both type I error rate and power. The usefulness of our
test is illustrated by applications to two microarray gene expression data sets | | Source: | arXiv, 2003.6455 | | Services: | Forum | Review | PDF | Favorites | |
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