Course Objective

The course will focus on the constructio and statistical analysis of probability models for real data. The course will provide a non-measure theoretic introduction to Markov chains, Discrete and Continuous Markov processesses, Hidden Markov Models, Markov random fields etc. All these models will be illustrated with examples. The application of these stochastic models in wide variety of fields such as Genetics, Epidemiology, Social Science will be discussed. Markov Chain Monte Carlo methds will be discussed briefly.

This is a 3 credit course. Prequisites are Stat 5101-2 or equivalent; PubH8420 and PubH8421; or instructor's consent. Some experience with Splus or R is useful; Real Analysis/Advanced Calculus at the level of Math5615 is needed.