Title:

Random Sampling via Markov Chain

Authors:

Shuji Kijima, Tomomi Matsui

Abstract:

The Markov chain Monte Carlo method is based on a simple idea, and works powerfully for samplinghard objects. Recently, it appears in many areas such as statistical physics, economics, statistics, and so on. There are some technical points when to use it practically, and in this talk, we focus on a topic of convergence rate of Markov chains, with some examples such as contingency tables, Ising model, and permanent. We also talk about perfect sampling.