Professor Arkady Shemyakin, University of St. Thomas in Minnesota.
The proposed course “Introduction to Bayesian Statistics and MCMC” has been presented in parts at the University of St. Thomas, Master of Financial Mathematics program at the University of Minnesota, and High School of Economics in Moscow. The four-lecture course will cover the foundations of Bayesian inference, principles of prior elicitation, Monte Carlo simulation, and Markov chain Monte Carlo methods (MCMC) such as Metropolis-Hastings algorithm and Gibbs sampling. Case studies deal with applications to Insurance and Finance.
Arkady Shemyakin is a Professor and Director of the Statistics Program at the University of St. Thomas in Minnesota. He is a graduate of Novosibirsk State University (1980) and did his post-graduate study at the Sobolev Institute of Mathematics. His main research interests lie in the fields of Bayesian Statistics, non-informative priors, history of randomized decisions, and applied copula models.
