English

Local Laws for Sparse Sample Covariance Matrices without the truncation condition

Probability 2022-09-28 v1

Abstract

We consider sparse sample covariance matrices 1npnXX\frac1{np_n}\mathbf X\mathbf X^*, where X\mathbf X is a sparse matrix of order n×mn\times m with the sparse probability pnp_n. We prove the local Marchenko--Pastur law in some complex domain assuming that npn>logβnnp_n>\log^{\beta}n, β>0\beta>0 and some (4+δ)(4+\delta)-moment condition is fulfilled, δ>0\delta>0.

Keywords

Cite

@article{arxiv.2209.13207,
  title  = {Local Laws for Sparse Sample Covariance Matrices without the truncation condition},
  author = {F. Götze and A. Tikhomirov and D. Timushev},
  journal= {arXiv preprint arXiv:2209.13207},
  year   = {2022}
}
R2 v1 2026-06-28T02:10:30.957Z