Figure 3From: Bayesian inference of transition matrices from incomplete graph data with a topological priorEffects of the use of constraints on the inference of a transition matrix in synthetic data. The left panel shows results on Erdős Rényi graphs, the middle panel shows results on geometric Euclidean random graphs, and the right panel shows results on geometric hyperbolic random graphs. We measure performance with the Frobenius distance between the transition matrix of the ground truth and that of the inferred model. Error bars represent the 95% confidence interval (mostly too small to be visible). The inclusion of the constraints allows BaCon to recover the transition matrix more precisely than both the frequentist and the noninformative Bayesian approachesBack to article page