On asymptotic expansion and CLT of linear eigenvalue statistics for sample covariance matrices when N/M→0N/M\rightarrow0

preprint2011arXivOpen access

Abstract

We study the renormalized real sample covariance matrix H=XTX/MN−M/NH=X^TX/\sqrt{MN}-\sqrt{M/N} with N/M→0N/M\rightarrow0 as N,M→∞N, M\rightarrow \infty in this paper. And we always assume M=M(N)M=M(N). Here X=[Xjk]M×NX=[X_{jk}]_{M\times N} is an M×NM\times N real random matrix with i.i.d entries, and we assume E∣X11∣5+δ<∞\mathbb{E}|X_{11}|^{5+δ}<\infty with some small positive δδ. The Stieltjes transform mN(z)=N−1Tr(H−z)−1m_N(z)=N^{-1}Tr(H-z)^{-1} and the linear eigenvalue statistics of HH are considered. We mainly focus on the asymptotic expansion of E{mN(z)}\mathbb{E}\{m_N(z)\} in this paper. Then for some fine test function, a central limit theorem for the linear eigenvalue statistics of HH is established. We show that the variance of the limiting normal distribution coincides with the case of a real Wigner matrix with Gaussian entries.

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