with the likelihood L( f 2 , F 2 |θ), the prior p(θ) and the evidence p( f 2 , F 2 ). The evidence can be absorbed in the normalization of the posterior since it does not depend on the model. Note that the quantities in equation ( ) are probability densities since the random variables are continuous, see appendix A for more details. If not mentioned otherwise we will assume a flat prior with support in r 1 , r 2 ∈ (0, ∞).