SINGULAR VECTOR DISTRIBUTION OF SAMPLE COVARIANCE MATRICES

We consider a class of sample covariance matrices of the form Q = TXX*T*, where X= (x(ij)) is an M x N rectangular matrix consisting of independent and identically distributed entries, and T is a deterministic matrix such that T*T is diagonal. Assuming that M is comparable to N, we prove that the distribution of the components of the right singular vectors close to the edge singular values agrees with that of Gaussian ensembles provided the first two moments of x(ij) coincide with the Gaussian random variables. For the right singular vectors associated with the bulk singular values, the same conclusion holds if the first four moments of x(ij) match those of the Gaussian random variables. Similar results hold for the left singular vectors if we further assume that T is diagonal.