The Annals of Statistics, Vol. 36, No. 6, High Dimensional Inference and Random Matrices (Dec., 2008), pp. 2791-2817 (27 pages) Principal component analysis (PCA) is a standard tool for dimensional ...

We show that in a common high-dimensional covariance model, the choice of loss function has a profound effect on optimal estimation. In an asymptotic framework based on the spiked covariance model and ...

Eigensensitivity analysis addresses how the spectral properties of damped systems—specifically, the eigenvalues and eigenvectors—respond to variations in system parameters. This analytical approach is ...