An Official Journal of the Institute of Mathematical Statistics.
Volume 36, Number 6
Publication Date: December 2008
Frontmatter
Table of Contents
Editorial Staff
High Dimensional Inference and Random Matrices. Articles
Random matrix theory: A program of the statistics and applied mathematical sciences institute (SAMSI)
Peter Bickel; 2551-2552
A CLT for regularized sample covariance matrices
Greg W. Anderson and Ofer Zeitouni; 2553-2576
Covariance regularization by thresholding
Peter J. Bickel and Elizaveta Levina; 2577-2604
High-dimensional classification using features annealed independence rules
Jianqing Fan and Yingying Fan; 2605-2637
Multivariate analysis and Jacobi ensembles: Largest eigenvalue, Tracy–Widom limits and rates of convergence
Iain M. Johnstone; 2638-2716
Operator norm consistent estimation of large-dimensional sparse covariance matrices
Noureddine El Karoui; 2717-2756
Spectrum estimation for large dimensional covariance matrices using random matrix theory
Noureddine El Karoui; 2757-2790
Finite sample approximation results for principal component analysis: A matrix perturbation approach
Boaz Nadler; 2791-2817
Flexible covariance estimation in graphical Gaussian models
Bala Rajaratnam, Hélène Massam and Carlos M. Carvalho; 2818-2849
Statistical eigen-inference from large Wishart matrices
N. Raj Rao, James A. Mingo, Roland Speicher and Alan Edelman; 2850-2885
Inference for eigenvalues and eigenvectors of Gaussian symmetric matrices
Armin Schwartzman, Walter F. Mascarenhas and Jonathan E. Taylor; 2886-2919
