Advanced Predictive Modeling Application

This course discusses Bayesian methods for estimating linear models. We discuss three methods for estimating the Bayesian posterior: grid approximation, quadratic approximation, and Markov Chain Monte Carlo (MCMC) methods. Bayesian methods are used to estimate linear regression models and generalized linear models. We also use Bayesian methods to estimate multilevel models, also known as linear mixed models. We also estimate linear mixed models using non-Bayesian methods. We learn how to build, estimate, and evaluate these models and how to select the best one.

This class covers most of the material of Exam MAS II of the Casualty Actuarial Society. This is a core class of the Actuarial Science program. Students may take either this class or Actuarial Methods II. Those who have already taken and passed the MAS II exam for CAS are exempted from this class and can substitute an elective.