A non-Gaussian limit for linear eigenvalue statistics of Hankel matrices
Probability
2022-09-20 v1
Abstract
This article focuses on linear eigenvalue statistics of Hankel matrices with independent entries. Using the convergence of moments we show that the linear eigenvalue statistics of Hankel matrices for odd degree monomials with degree greater than or equal to three does not converge in distribution to a Gaussian random variable. This result is a departure from the known results, Liu, Sun and Wang (2012), Kumar and Maurya (2022), of linear eigenvalue statistics of Hankel matrices for even degree monomial test functions, where the limits were Gaussian random variables.
Cite
@article{arxiv.2209.08252,
title = {A non-Gaussian limit for linear eigenvalue statistics of Hankel matrices},
author = {Kiran Kumar A. S. and Shambhu Nath Maurya and Koushik Saha},
journal= {arXiv preprint arXiv:2209.08252},
year = {2022}
}
Comments
22 Pages, 3 figures