  We present an analytic method for calculating spectral densities of empirical
covariance matrices for correlated data. In this approach the data is
represented as a rectangular random matrix whose columns correspond to sampled
states of the system. The method is applicable to a class of random matrices
with radial measures including those with heavy (power-law) tails in the
probability distribution. As an example we apply it to a multivariate Student
distribution.
