— Topics in Statistical Methods & Models

Prerequisites & course information

Course Description: Topics may include Bayesian analysis, nonparametric and semiparametric regression, sequential analysis, bootstrap, statistical methods in high dimensions, reliability, spatial processes, inference for stochastic process, stochastic methods in finance, empirical processes, change-point problems, asymptotics for parametric, nonparametric and semiparametric models, nonlinear time series, robustness. Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Repeat Credit: May be repeated when topic differs and only with consent of graduate advisor. Grade Mode: Letter. Learning Activities: Lecture 3 hour(s), Discussion 1 hour(s). Repeat Credit: May be repeated when topic differs and only with consent of graduate advisor. Grade Mode: Letter.