The limiting spectral distribution of the sample canonical correlation matrix

In this paper, we investigate the global spectral properties of the sample canonical correlation (SCC) matrix under the alternative hypothesis to provide a more comprehensive description of the association between two sets of variables. Our research involves establishing the relationship between the eigenvalues of the SCC matrix and that of the block correlation matrix, as well as proving the universality of the limiting spectral distribution (LSD) of the block correlation matrix. By combining the results from the normal case, we establish the limiting spectral distribution (LSD) of the SCC matrix with a general underlying distribution under the arbitrary rank alternative hypothesis. Finally, we present several simulation examples and find that they fit well with our theoretical results.

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Publication Details

Journal
Random Matrices Theory and Application
Published
2025-03-28
DOI
https://doi.org/10.1142/s2010326325500091
Primary Topic
Random Matrices and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

The limiting spectral distribution of the sample canonical correlation matrix

Xiaozhuo Zhang
Random Matrices Theory and Application
Random Matrices and Applications
article

The limiting spectral distribution of the sample canonical correlation matrix

Xiaozhuo Zhang
article en

Abstract

In this paper, we investigate the global spectral properties of the sample canonical correlation (SCC) matrix under the alternative hypothesis to provide a more comprehensive description of the association between two sets of variables. Our research involves establishing the relationship between the eigenvalues of the SCC matrix and that of the block correlation matrix, as well as proving the universality of the limiting spectral distribution (LSD) of the block correlation matrix. By combining the results from the normal case, we establish the limiting spectral distribution (LSD) of the SCC matrix with a general underlying distribution under the arbitrary rank alternative hypothesis. Finally, we present several simulation examples and find that they fit well with our theoretical results.

Random Matrices Theory and ApplicationVol. 14(03)
Northeast Normal University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation
Reduced inequalities
Openalex Percentile: Top 94%
Random Matrices and Applications
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