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, the Pearson's correlation matrix, the Kendall's correlation matrix and the Spearman's correlation matrix.

翻译：在本文中,我们研究了Spearman级相关矩阵的经验光谱分布,假设观测是独立的,分布相同的随机矢量和特征是相互关联的。我们表明,限制光谱分布是通用的Mar\u{c}enko-Pastur法和标准化变换后观测的共变量矩阵。根据这些结果,我们比较了几个古老的共变/共变矩阵,包括样本常变矩阵、Pearson的关联矩阵、Kendall的关联矩阵和Spearman的关联矩阵。