Abstract
In this paper, we establish a new central limit theorem for the linear spectral statistics of high-dimensional sample covariance matrices. The underlying population belongs to the family of elliptical distributions, and the dimension of the population is allowed to grow to infinity, in proportion to the sample size. As an application, we construct confidence intervals for the model parameters of a Gaussian scale mixture.
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