Figure 7

RMSPE: ABC algorithm validation given different levels of assumed and known migration rates and D _m = π _b . Histograms depicting the distribution of RMSPE (root mean square posterior error) for 100 estimates of parameter values given 100 PODS (pseudo observed data sets) simulated with known parameter values. Panel A corresponds to estimates of E(τ) and panel B corresponds to estimates of Ω. For all PODS, Ψ (number divergence times across five taxon-pairs) is drawn from its discrete uniform hyper-prior ranging between 1 (simultaneous divergence) and 5 (the number of taxon-pairs). PODS and corresponding priors were simulated given 16 loci each from 5 taxon-pairs. Three different hyper-priors were used with respect to post-divergence migration rates as well with simulating PODS (migration rate Nm = 0, 0-1, and 0-10 migrants per generation where migration rate varies independently across taxon-pairs within each 5 taxon-pair data set). Each RMSPE is calculated from the true hyper-parameter value (E(τ) and Ω) and the corresponding 500 accepted points out of a total 1,500,000 draws from the hyper-prior using ABC with local linear regression and a summary statistic vector D _m that only included mean values of π _b across loci from every taxon-pair.