Two-way MANOVA with unequal cell sizes and unequal cell covariance matrices in high-dimensional settings
Two-way MANOVA with unequal cell sizes and unequal cell covariance matrices in high-dimensional settings
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DOI：
10.1016/j.jmva.2020.104625
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发表时间：
2020-05
期刊：
影响因子：
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通讯作者：
Hiroki Watanabe;Masashi Hyodo;Shigekazu Nakagawa
中科院分区：
文献类型：
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作者：
Hiroki Watanabe;Masashi Hyodo;Shigekazu Nakagawa
在本文中，我们讨论了一个双向多元方差分析在高维设置。在高维环境下，我们提出了新的近似检验，在以下条件下工作良好：1。误差向量不一定遵循多元正态分布，2。细胞大小不等，3。单元格协方差矩阵是不相等的，并且4.尺寸p比总单元尺寸n大得多。有限样本的准确性所提出的测试显示，通过模拟各种高维场景。
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.