主成分分析の固有値の一致性について

抄録

We study the empirical spectral distribution of so-called large dimensional random matrices. By empirical process theory and measure concentration inequalities, we provide a sufficient condition for the sum of the largest eigenvalues of the sample covariance matrix to be consistent, in the limit of the sample size n with the dimension d of data in the sample varying along n.