  In this paper, we study the empirical spectral distribution of Spearman's
rank correlation matrices, under the assumption that the observations are
independent and identically distributed random vectors and the features are
correlated. We show that the limiting spectral distribution is the generalized
Mar\u{c}enko-Pastur law with the covariance matrix of the observation after
standardized transformation. With these results, we compare several classical
covariance/correlation matrices including the sample covariance matrix,
Pearson's correlation matrix, Kendall's correlation matrix and Spearman's
correlation matrix.
