A Comparison of Scientific and Engineering Criteria for Bayesian Model Selection

For each possible model m, we define the random (vector) variable \Theta m whose values correspond to the possible values of the parameters for m. We encode our uncertainty about \Theta m using the probability distribution p(\Theta m jm). In this paper, we assume that p(\Theta m jm) is a probability density function.