UCLA

Donoho and Gavish(2013) proposed a method of recovering a matrix by selecting singular values above a hard threshold. In their paper, 4/√3 is proved to be asymptotic MSE-optimal choice of hard threshold. We empirically test the applicability of Donoho and Gavish's method in factor analysis with simulated datasets and assess its asymptotic property when both the matrix and sample size grow while keeping the true number of factors fixed.