Open Access
Table C.1.
Validation of SFH Classification with Bayes factor for realistic simulated observations with bursty and smooth SFHs as a function of S/N.
| S/N bin | Simulated Bursty SFH | Simulated smooth SFH | ||||||
|---|---|---|---|---|---|---|---|---|
| Classify as Bursty | Classify as Smooth | Classify as Bursty | Classify as Smooth | |||||
| (True positive) | (False negative) | (False negative) | (True positive) | |||||
| BF > 1 | BF > 3 | BF > 1 | BF > 3 | BF > 1 | BF > 3 | BF > 1 | BF > 3 | |
| [0–5] | 0.40 | 0.13 | 0.60 | 0.87 | 0.30 | 0.03 | 0.70 | 0.97 |
| [5–10] | 0.60 | 0.35 | 0.40 | 0.65 | 0.31 | 0.05 | 0.68 | 0.95 |
| [10–20] | 0.76 | 0.61 | 0.24 | 0.39 | 0.34 | 0.05 | 0.65 | 0.95 |
| [20–30] | 0.88 | 0.88 | 0.22 | 0.22 | 0.27 | 0.05 | 0.73 | 0.95 |
Notes. The table shows the fraction of objects classified as bursty or smooth for each SFH type (true or false positives or negatives) using two BF thresholds (BF > 1 and BF > 3).
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