TABLE 3.
Comparison of the influence of the approximation on the power of LBF for simple models with different migration schemes
Evidence | Counts (based on ![]() ![]() |
|||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Model | 1a | 1b | 2a | 2b | ||||||||
Nm | ∞ | 1250 | 0.25 | 0.0025 | ||||||||
Approximation | 16 | 4 | H | 16 | 4 | H | 16 | 4 | H | 16 | 4 | H |
Against M0 | 0 | 5 | 26 | 0 | 8 | 29 | 70 | 49 | 53 | 100 | 100 | 78 |
Against M1 | 100 | 94 | 73 | 100 | 92 | 71 | 30 | 51 | 47 | 0 | 0 | 22 |
LBF compared a full model (model M1 = □⇆▪) with a panmictic population (model M0 = ). Models used to simulate the data were as follows: 1a, a single population, the sampled individuals split randomly into two sets (
); 1b, two populations exchanging many migrants (Nm = 1250); 2a, two populations exchanging a moderate number of migrants (Nm = 0.25); and 2b, two populations with very low migration rate (Nm = 0.0025). The marginal likelihoods used in the LBF were approximated with thermodynamic integration (TI) with 16 and 4 scaler bins and with the harmonic mean (HM4).