Singular vector distribution of sample covariance matrices

Abstract

We consider a class of sample covariance matrices of the form Q=TXX*T*, where X=(xij) is an M × N rectangular matrix consisting of i.i.d entries and T is a deterministic matrix satisfying T*T is diagonal. Assuming M is comparable to N, we prove that the distribution of the components of the singular vectors close to the edge singular values agrees with that of Gaussian ensembles provided the first two moments of xij coincide with the Gaussian random variables. For the singular vectors associated with the bulk singular values, the same conclusion holds if the first four moments of xij match with those of Gaussian random variables. Similar results have been proved for Wigner matrices by Knowles and Yin.

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