Marchenko Pastur Law

In Random Matrix Theory, MP law gives the probability density function of singular values of large rectangular random matrices; when the dimensions of matrix tend to infinity.
This contribution illustrates the PDF of matrix Y(N,N)=(T^-1)X*X^T, where X is random matrix whose entries X_i,j are independent and identically distributed random variables with zero mean and variance s^2. The program is applicable for both uniform and random distributions.
Ref :
Marchenko,V. A., Pastur, L. A. (1967) "Distribution of eigenvalues for some sets of
random matrices", Mat. Sb. (N.S.), 72(114):4, 507–536