Multivariate Analysis

Multivariate normal and Wishart distributions, estimation and hypothesis testing of mean vectors and covariance matrices and their extensions to high-dimensional setting (n<p), principal component analysis (PCA), factor analysis, canonical analysis, discrimination, and classification with a focus on linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA). Precision matrices for high-dimensional data, high dimensional, and sparse PCA, Nonlinear PCA.