Correlation tests for high-dimensional data using extended cross-data-matrix methodology

Kazuyoshi Yata and Makoto Aoshima

Journal of Multivariate Analysis, 2013, vol. 117, issue C, 313-331

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→∞ 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.

Keywords: Cross-data-matrix methodology; Graphical modeling; HDLSS; High-dimensional regression; Pathway analysis; Two-stage procedure (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (9)

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DOI: 10.1016/j.jmva.2013.03.007

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