In the first part , we saw a small introduction of the Bayesian inference and a first approach of Monte-Carlo techniques. Now, we will get through the Monte Carlo in order to obtain a random sample from the posterior distribution using some common techniques. Then, the next post will present the well-known Metropolis(-Hastings), Gibbs sampler, […]