Gaussian Fluctuations for Sample Covariance Matrices with Dependent Data
Probability
2012-03-21 v1 Statistics Theory
Statistics Theory
Abstract
It is known (Hofmann-Credner and Stolz (2008)) that the convergence of the mean empirical spectral distribution of a sample covariance matrix W_n = 1/n Y_n Y_n^t to the Mar\v{c}enko-Pastur law remains unaffected if the rows and columns of Y_n exhibit some dependence, where only the growth of the number of dependent entries, but not the joint distribution of dependent entries needs to be controlled. In this paper we show that the well-known CLT for traces of powers of W_n also extends to the dependent case.
Keywords
Cite
@article{arxiv.1203.4387,
title = {Gaussian Fluctuations for Sample Covariance Matrices with Dependent Data},
author = {Olga Friesen and Matthias Löwe and Michael Stolz},
journal= {arXiv preprint arXiv:1203.4387},
year = {2012}
}
Comments
28 pages