Bayesian methods are becoming increasingly popular in the academic and practitioner communities because of the recent development of techniques like Markov chain Monte Carlo (MCMC) simulation. The Bayesian paradigm is an attempt to utilize all available information in decision-making. Prior knowledge coming from experience, expert judgment, or previously collected data is used with current data to characterize the current state of knowledge. These methods allow the use of models of complex physical phenomena that were previously too difficult to estimate. Bayesian methods offer a means of more fully understanding issues that are central to many practical problems by allowing researchers to build integrated models of behavior that can be estimated with limited amounts of data.
Click here for the Bayesian working group website
