Bayesian Statistics: MCMC – EFavDB

We review the Metropolis algorithm -- a simple Markov Chain Monte Carlo (MCMC) sampling method -- and its application to estimating posteriors in Bayesian statistics. A simple python example is provided. Follow @efavdb Follow us on twitter for new submission alerts! One of the central aims of statistics is to identify good methods for fitting models to data. Notice that if we could solve for this function, we would be able to identify which parameter values are most likely -- those that are good candidates for a fit.