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On singular value distribution of large dimensional data matrices whose columns have different correlations

Statistics Theory 2020-01-20 v3 Probability Statistics Theory

Abstract

Suppose Yn=(y1,,yn)\mathbf Y_n=(\mathbf y_1,\cdots,\mathbf y_n) is a p×np\times n data matrix whose columns yj,1jn\mathbf y_j, 1\leq j\leq n have different correlations. The asymptotic spectral property of Sn=1nYnYn\mathbf S_n=\frac1n\mathbf Y_n\mathbf Y^*_n when pp increase with nn has been considered by some authors recently. This model has known an increasing popularity due to its widely applications in multi-user multiple-input single-output (MISO) systems and robust signal processing. In this paper, for more convenient applications in practice, we will investigate the spectral distribution of Sn\mathbf S_n under milder moment conditions than existing work. We also discuss a potential application in sample classification.

Keywords

Cite

@article{arxiv.1802.01245,
  title  = {On singular value distribution of large dimensional data matrices whose columns have different correlations},
  author = {Yanqing Yin},
  journal= {arXiv preprint arXiv:1802.01245},
  year   = {2020}
}

Comments

The final version of this paper will be published in Statistics

R2 v1 2026-06-23T00:10:35.385Z