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Jeffrey Rosenthal - The mathematics of Markov chain Monte Carlo algorithms

JEFFREY ROSENTHAL, Department of Mathematics, University of Toronto, Toronto, Ontario  M5S 3G3, Canada
The mathematics of Markov chain Monte Carlo algorithms

Markov chain Monte Carlo ( MCMC) algorithms, such as the Gibbs sampler and the Metropolis-Hastings algorithm, are now widely used in statistics, computer science, physics, and chemistry to understand complicated probability distributions. While the implementation of these algorithms is often routine, many fundamental questions--such as convergence rates--are much more difficult. In this talk, we will review some of these issues and the partial progress that has been made towards resolving them.


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