AMS580 SBU
This course will first review classical linear and generalized linear models such as Linear Regression, Logistic Regression, and Linear Discriminant Analysis. We shall then study modern Resampling Methods such as Bootstrapping, and modern variable selection methods such as the Shrinkage Method. We will study traditional multivariate analysis methods including cluster analysis, principal component analysis, and multivariate regression methods such as structural equation modeling. Finally, we shall introduce modern non-linear statistical learning methods such as the Generalized Additive Models, Decision Trees, Random Forest, Boosting, Bagging, Support Vector Machines, and various Neural Networks.