Groups
Random Matrix Theory (RMT) explains how eigenvalues of large random matrices behave when the dimension p is comparable to the sample size n.
The Marchenko–Pastur (MP) distribution describes the limiting eigenvalue distribution of sample covariance matrices S = (1/n) XX^{\top} when both the dimension p and the sample size n grow with p/n \to \gamma.