Optimising and adapting the Metropolis algorithm
Seminar Room 1, Newton Institute
AbstractThe Metropolis algorithm is a very popular method of approximately sampling from complicated probability distributions, especially those arising in Bayesian inference. A wide variety of proposal distributions are available, and it can be dió cult to choose among them. We will discuss optimal proposals under various circumstances. We will also consider the possibility of having the computer automatically "adapt" the algorithm while it runs, to improve and tune on the fly.
If it doesn't, something may have gone wrong with our embedded player.
We'll get it fixed as soon as possible.