Bayesian Analysis Using Monte Carlo Integration - a Powerful Methodology for Handling Some Difficult Problems

A brief description of Bayesian analysis using Monte Carlo integration is given. An example is presented that illustrates the Bayesian estimation of an asymmetric density and includes a display of distribution and density functions generated from the posterior distribution. Other papers are referenced that contain examples that illustrate the power of this approach (a) to handle more accurate formulations of real problems, (b) to analyse difficult models and data for small samples, and (c) to compute predictive distributions and posterior distributions for many functions of the parameters.