Figure 3.
Accuracy of different algorithms as a function of model complexity (K) on two simulated data sets, one in which ancestry is easy to resolve (A; r = 1) and one in which ancestry is difficult to resolve: (B; r = 0.5) Solid lines correspond to parameter estimates computed with a convergence criterion of |Δℰ| < 10−8, while the dashed lines correspond to a weaker criterion of |Δℰ| < 10−6. (Left) Mean admixture divergence between the true and inferred admixture proportions; (middle) mean binomial deviance of held-out genotype entries. Note that for values of K greater than the optimal value, any change in prediction error lies within the standard error of estimates of prediction error suggesting that we should choose the smallest value of model complexity above which a decrease in prediction error is statistically insignificant. (Right) Approximations to the marginal likelihood of the data computed by STRUCTURE and fastSTRUCTURE.