Post-detection parameter inference on Gaussian Synthetic Data Setting II (500 independent runs)
0.47Conditional LengthWu (2006)
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| Wu (2006)F0=N(−0.25, 1), F1=N(0.25, 1), T=100, target conditional coverage=0.852025.02 | 0.47 | 77 | 74 | |
| Wu (2006)F0=N(−0.25, 1), F1=N(0.25, 1), T=500, target conditional coverage=0.852025.02 | 0.49 | 78 | 64 | |
| Wu (2006)F0=N(−0.3, 1), F1=N(0.3, 1), T=100, target conditional coverage=0.852025.02 | 0.51 | 76 | 75 | |
| Wu (2006)F0=N(−0.3, 1), F1=N(0.3, 1), T=500, target conditional coverage=0.852025.02 | 0.51 | 79 | 71 | |
| universal threshold frameworkF0=N(−0.3, 1), F1=N(0.3, 1), T=100, target conditional coverage=0.852025.02 | 1.43 | 98 | 98 | |
| universal threshold frameworkF0=N(−0.25, 1), F1=N(0.25, 1), T=100, target conditional coverage=0.852025.02 | 1.46 | 99 | 98 | |
| universal threshold frameworkF0=N(−0.25, 1), F1=N(0.25, 1), T=500, target conditional coverage=0.852025.02 | 1.48 | 99 | 91 | |
| universal threshold frameworkF0=N(−0.3, 1), F1=N(0.3, 1), T=500, target conditional coverage=0.852025.02 | 1.49 | 99 | 91 |