  We describe a method to determine the eigenvalue density of empirical
covariance matrix in the presence of correlations between samples. This is a
straightforward generalization of the method developed earlier by the authors
for uncorrelated samples. The method allows for exact determination of the
experimental spectrum for a given covariance matrix and given correlations
between samples in the limit of large N and N/T=r=const with N being the number
of degrees of freedom and T being the number of samples. We discuss the effect
of correlations on several examples.
