English

High-dimensional sample covariance matrices with Curie-Weiss entries

Probability 2019-10-29 v1

Abstract

We study the limiting spectral distribution of sample covariance matrices XXTXX^T, where XX are p×np\times n random matrices with correlated entries, for the cases p/ny[0,)p/n\to y\in [0,\infty). If y>0y>0, we obtain the Mar\v{c}enko-Pastur distribution and in the case y=0y=0 the semicircle distribution (after appropriate rescaling). The entries we consider are Curie-Weiss spins, which are correlated random signs, where the degree of the correlation is governed by an inverse temperature β>0\beta>0. The model exhibits a phase transition at β=1\beta=1. The correlation between any two entries decays at a rate of O(np)O(np) for β(0,1)\beta \in (0,1), O(npO(\sqrt{np}) for β=1\beta=1, and for β>1\beta>1 the correlation does not vanish in the limit. In our proofs we use Stieltjes transforms and concentration of random quadratic forms.

Keywords

Cite

@article{arxiv.1910.12332,
  title  = {High-dimensional sample covariance matrices with Curie-Weiss entries},
  author = {Michael Fleermann and Johannes Heiny},
  journal= {arXiv preprint arXiv:1910.12332},
  year   = {2019}
}