Journal
JOURNAL OF MULTIVARIATE ANALYSIS
Volume 179, Issue -, Pages -Publisher
ELSEVIER INC
DOI: 10.1016/j.jmva.2020.104625
Keywords
MANOVA; Testing hypotheses; High-dimensional data analysis
Categories
Funding
- [20K11712]
- [18K11206]
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In this paper, we discuss a two-way multivariate analysis of variance in high-dimensional settings. With a high-dimensional setting, we propose new approximate tests that work well under the following conditions: 1. The error vectors do not necessarily follow a multivariate normal distribution, 2. The cell sizes are unequal, 3. The cell covariance matrices are unequal, and 4. The dimension p is much larger than the total cell size n. The accuracy of the proposed tests with finite samples is shown through simulations for a variety of high-dimensional scenarios. (C) 2020 Elsevier Inc. All rights reserved.
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