A0430
Title: Limiting spectral distribution of large dimensional Spearman's rank correlation matrices
Authors: Cheng Wang - Shanghai Jiao Tong University (China) [presenting]
Abstract: The empirical spectral distribution of Spearman's rank correlation matrices is studied 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 Marcenko-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.
