You regard m potential models, M1,…, Mm, to be (a priori) equally likely.

Use Bayes’ theorem to conduct Bayesian model averaging by finding an expression for the posterior P(Mi ∣ y) in terms of the marginal {P(y ∣ Mj)}

for the models (integrating out the parameters). Extend the result to possibly unequal prior probabilities {P(Mi)}.