Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1145900 | Journal of Multivariate Analysis | 2013 | 19 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Mathematics
Numerical Analysis
Authors
Kazuyoshi Yata, Makoto Aoshima,