We computed the distribution of the prediction error E := P 0 a -P 0 a in Fig. by (i) finding the inverse function of the transformation (δ, p 0 a , p 0 i ) → (E, p 0 a , p 0 i ) under the model, (ii) computing its Jacobian matrix J via numerical differentiation, (iii) constructing the density of (E, p 0 a , p 0 i ) as the known density of (δ, p 0 a , p 0 i ) times the absolute value of the determinant of J. We then marginalize this distribution over the variables p 0 a , p 0 i using numerical quadrature.