Table 5.
Summary of the DIYABC analysis.
| Scenario | Parameter | Mean | Median | Q0.05 | Q0.95 | Direct | Logistic |
|---|---|---|---|---|---|---|---|
| 7 | 0.18 [0.01,0.52] | 0.37 [0.16,0.59] | |||||
| N1 | 1.22E + 03 | 1.09E + 03 | 4.25E + 02 | 2.41E + 03 | |||
| N2 | 1.29E + 03 | 7.87E + 02 | 2.02E + 02 | 4.49E + 03 | |||
| N3 | 2.88E + 02 | 1.35E + 02 | 4.05E + 01 | 8.68E + 02 | |||
| N4 | 2.91E + 03 | 2.32E + 03 | 6.16E + 02 | 7.56E + 03 | |||
| N5 | 5.47E + 03 | 5.33E + 03 | 2.20E + 03 | 9.08E + 03 | |||
| N6 | 3.38E + 03 | 3.09E + 03 | 1.19E + 03 | 6.74E + 03 | |||
| t1 | 6.28E + 02 | 6.38E + 02 | 2.94E + 02 | 9.28E + 02 | |||
| r2 | 6.09E − 01 | 6.20E − 01 | 3.57E − 01 | 8.20E − 01 | |||
| d | 5.99E + 01 | 6.24E + 01 | 1.59E + 01 | 9.68E + 01 | |||
| r1 | 4.92E − 01 | 4.92E − 01 | 2.22E − 01 | 7.65E − 01 | |||
| t2 | 6.69E + 03 | 5.97E + 03 | 5.06E + 03 | 1.10E + 04 | |||
| N1a | 4.03E + 03 | 3.50E + 03 | 8.59E + 02 | 8.70E + 03 | |||
| µ_cpSSR | 1.35E − 04 | 1.23E − 04 | 3.15E − 05 | 6.56E − 05 | |||
| µ_nrSSR | 2.06E − 04 | 1.49E − 04 | 1.00E − 04 | 2.06E − 04 | |||
| 1 | 0.09 [0.00, 0.34] | 0.00 [0.00, 0.16] | |||||
| 2 | 0.08 [0.00, 0.32] | 0.00 [0.00, 0.16] | |||||
| 3 | 0.03 [0.00, 0.17] | 0.00 [0.00, 0.16] | |||||
| 4 | 0.11 [0.00, 0.38] | 0.27 [0.00, 0.57] | |||||
| 5 | 0.13 [0.00, 0.43] | 0.02 [0.00, 0.18] | |||||
| 6 | 0.07 [0.00, 0.29] | 0.00 [0.00, 0.16] | |||||
| 8 | 0.17 [0.00, 0.49] | 0.32 [0.16, 0.49] | |||||
| 9 | 0.15 [0.00, 0.46] | 0.02 [0.00, 0.17] |
The direct posterior probability estimates (95% confidence interval) and those calculated by logistic regression for the top 1% of simulated data sets closest to the empirical data for all scenarios are present. For the most probable evolutionary scenario (7), the posterior mean and median values with 95% confidence intervals of parameters integrated in the scenario of choice are provided. The most probable scenario is marked in bold for the posterior probability estimates.