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arXiv · 1310.8123

Tests for covariance matrix with fixed or divergent dimension

Rongmao Zhang·Liang Peng·Ruodu Wang
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Abstract

Testing covariance structure is of importance in many areas of statistical analysis, such as microarray analysis and signal processing. Conventional tests for finite-dimensional covariance cannot be applied to high-dimensional data in general, and tests for high-dimensional covariance in the literature usually depend on some special structure of the matrix. In this paper, we propose some empirical likelihood ratio tests for testing whether a covariance matrix equals a given one or has a banded structure. The asymptotic distributions of the new tests are independent of the dimension.

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Rongmao Zhang, Liang Peng, Ruodu Wang. 2013-10-30. Tests for covariance matrix with fixed or divergent dimension. https://doi.org/10.1214/13-aos1136

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