Table 1. Performance of methods as a function of sampling strategy and mean migration rate in the two-population “fixed tree” scenario.
Sampling | Rate c | Method | Calibration d | Correlation e | RMSE f |
---|---|---|---|---|---|
Even a | Fast | DTA | 0.56 | 0.58 | 1.83 |
MTT | 0.87 | 0.77 | 1.32 | ||
BASTA | 0.95 | 0.83 | 1.51 | ||
Even | Slow | DTA | 0.81 | 0.64 | 1.65 |
MTT | 0.96 | 0.75 | 1.52 | ||
BASTA | 0.97 | 0.81 | 1.30 | ||
Uneven b | Fast | DTA | 0.68 | 0.33 | 1.79 |
MTT | 0.80 | 0.46 | 2.50 | ||
BASTA | 0.84 | 0.70 | 2.08 | ||
Uneven | Slow | DTA | 0.80 | 0.39 | 1.73 |
MTT | 0.85 | 0.42 | 2.49 | ||
BASTA | 0.88 | 0.51 | 2.29 |
For each combination of sampling strategy, migration rate and method, we assessed the methods’ performance across 100 replicates by recording the “true” (i.e. simulated) ratio of the migration rates f 1,2/f 2,1, the point estimate (posterior median) and the 95% credible interval.
a 100 samples per population.
b 10 samples for one population and 190 for the other.
c total mean migration rate: fast () or slow ().
d proportion of replicates for which the truth fell within the 95% credible interval.
e correlation between the truth and the point estimate.
f root mean square error of the point estimate.