Shrinkage-based diagonal Hotelling’s tests for high-dimensional small sample size data
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ArticleKAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionStatistics Program
Date
2015-09-16Online Publication Date
2015-09-16Print Publication Date
2016-01Permanent link to this record
http://hdl.handle.net/10754/578818
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DNA sequencing techniques bring novel tools and also statistical challenges to genetic research. In addition to detecting differentially expressed genes, testing the significance of gene sets or pathway analysis has been recognized as an equally important problem. Owing to the “large pp small nn” paradigm, the traditional Hotelling’s T2T2 test suffers from the singularity problem and therefore is not valid in this setting. In this paper, we propose a shrinkage-based diagonal Hotelling’s test for both one-sample and two-sample cases. We also suggest several different ways to derive the approximate null distribution under different scenarios of pp and nn for our proposed shrinkage-based test. Simulation studies show that the proposed method performs comparably to existing competitors when nn is moderate or large, but it is better when nn is small. In addition, we analyze four gene expression data sets and they demonstrate the advantage of our proposed shrinkage-based diagonal Hotelling’s test.Citation
Shrinkage-based diagonal Hotelling’s tests for high-dimensional small sample size data 2015 Journal of Multivariate AnalysisPublisher
Elsevier BVJournal
Journal of Multivariate AnalysisAdditional Links
http://linkinghub.elsevier.com/retrieve/pii/S0047259X15002146ae974a485f413a2113503eed53cd6c53
10.1016/j.jmva.2015.08.022