Correlation tests for high-dimensional data using extended cross-data-matrix methodology Correlation tests for high-dimensional data using extended cross-data-matrix methodology
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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→∞p→∞ and n→∞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.
- Journal of multivariate analysis
Journal of multivariate analysis (117), 313-331, 2013-05