Figure 12.

In BOLFI, the estimated model of is used to approximate by computing the probability that the distance is below a threshold . This kind of likelihood approximation leads to a model-based approximation of . The KL-divergence between the reference solution and the BOLFI solution with 30 data points is 0.09, and for 200 data points it is 0.01. Comparison with Figure 6 shows that BOLFI increases the computational efficiency of ABC by several orders of magnitude. a) Approximate likelihood function. b) Model-based posteriors.