Asymptotic performance of PCA for high-dimensional heteroscedastic data

David Hong, Laura Balzano, Jeffrey A. Fessler

Principal Component Analysis (PCA) is a classical method for reducing the dimensionality of data by projecting them onto a subspace that captures most of their variation. Effective…