Section 12 The Metropolis-Hastings Algorithm

In Sections 9 and 10 we discussed likelihood and cost functions, and Section 11 introduced the idea of sampling. For this section we will combine all these concepts to discover a powerful algorithm that can efficiently sample a probability distribution (think likelihood function) to estimate model parameters.