Summary: Applying the replica method of statistical mechanics, we evaluate the eigenvalue density of the large random matrix (sample covariance matrix) of the form \(J = A^{\mathrm T}A\), where \(A\) is an \(M \times N\) real sparse random matrix. The difference from a dense random matrix is the most significant in the tail region of the spectrum. We compare the results of several approximation schemes, focusing on the behaviour in the tail region.