ABSTRACT
In many applications of statistical modeling, the data analyst would like to use a more complex model for a data set, but is forced to resort to an oversimplified model in order to use available techniques. Markov chain Monte Carlo (MCMC) methods are simulation-based and enable the statistician or engineer to examine data using realistic statistical models.
