Interval prediction on Body fat data (test)
100CoverageUnion interval
Evaluation results
| Method | Links | ||
|---|---|---|---|
| Union intervalCP methodology=Split CP2025.07 | 100 | 0.1887 | |
| Logit-normal Model - M1CP methodology=Split CP2025.07 | 95 | 0.1457 | |
| Logit-normal Model - M1CP methodology=Full CP2025.07 | 95 | 0.1391 | |
| Heteroscedastic Logit-normal Model - M2CP methodology=Split CP2025.07 | 95 | 0.1599 | |
| Heteroscedastic Logit-normal Model - M2CP methodology=Full CP2025.07 | 95 | 0.1581 | |
| Beta model (μ, Pearson) - M3(P)CP methodology=Split CP2025.07 | 95 | 0.1323 | |
| Beta model (μ, Pearson) - M3(P)CP methodology=Full CP2025.07 | 95 | 0.1303 | |
| Beta model (μ, Quantile) - M3(Q)CP methodology=Split CP2025.07 | 95 | 0.1361 | |
| Beta model (μ, Quantile) - M3(Q)CP methodology=Full CP2025.07 | 95 | 0.1287 | |
| Beta model (μ, φ, Pearson) - M4(P)CP methodology=Split CP2025.07 | 95 | 0.1468 | |
| Beta model (μ, φ, Pearson) - M4(P)CP methodology=Full CP2025.07 | 95 | 0.1339 | |
| Beta model (μ, φ, Quantile) - M4(Q)CP methodology=Split CP2025.07 | 95 | 0.1552 | |
| Beta model (μ, φ, Quantile) - M4(Q)CP methodology=Full CP2025.07 | 95 | 0.1287 | |
| Union intervalCP methodology=Full CP2025.07 | 95 | 0.1717 | |
| Intersection intervalCP methodology=Full CP2025.07 | 95 | 0.1137 | |
| Intersection intervalCP methodology=Split CP2025.07 | 90 | 0.1117 | |
| Bootstrap2025.07 | 90 | 0.1338 |