A high-dimension two-sample test for the mean using cluster subspaces

Jie Zhang and Meng Pan

Computational Statistics & Data Analysis, 2016, vol. 97, issue C, 87-97

Abstract: A common problem in modern genetic research is that of comparing the mean vectors of two populations–typically in settings in which the data dimension is larger than the sample size–where Hotelling’s test cannot be applied.

Keywords: High-dimension data; Two-sample problem; Hierarchical clustering; Hotelling’s test (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:97:y:2016:i:c:p:87-97

DOI: 10.1016/j.csda.2015.12.004

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