In this paper, we consider tests of correlation when the sample size is much lower than the dimension. We propose a new estimation methodology called the extended cross-data-matrix methodology. By applying the method, we give a new test statistic for high-dimensional correlations. We show that the test statistic is asymptotically normal when p?? and n??. We propose a test procedure along with sample size determination to ensure both prespecified size and power for testing high-dimensional correlations. We further develop a multiple testing procedure to control both family wise error rate and power. Finally, we demonstrate how the test procedures perform in actual data analyses by using two microarray data sets. © 2013 Elsevier Inc.
CITATION STYLE
Yata, K., & Aoshima, M. (2013). Correlation tests for high-dimensional data using extended cross-data-matrix methodology. Journal of Multivariate Analysis, 117, 313–331. https://doi.org/10.1016/j.jmva.2013.03.007
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