Monthly Archives: October 2013


Understanding the Metropolis Hasting algorithm - A tutorial

The Problem Say you want to evaluate the expectation of a function over a random variable \(E[f(x)] = \int p(x)f(x)dx\), or perhaps find the max of a probability distribution, typically the posterior, \(\arg \max p(x|y)\), where calculating the derivate is intractable since it depends on some feature that comes from some algorithm or some unknown […]