Benchmark id: inv1
Waveform mistfits
| Solution | Horizontal components | All components | ||||||
| 1-Norm | 2-Norm | RMSE | %VR | 1-Norm | 2-Norm | RMSE | %VR | |
| SIVdata | 0.0 | 0.0 | 0.0 | 100.0 | 0.0 | 0.0 | 0.0 | 100.0 |
| causse | 416.8 | 13.7 | 0.7 | 54.0 | 340.3 | 9.8 | 0.9 | 56.3 |
| FSG | 251.0 | 13.1 | 0.5 | 64.6 | 207.7 | 9.4 | 0.7 | 65.1 |
| gallovic2 | 15.1 | 0.2 | 0.2 | 94.4 | 12.3 | 0.1 | 0.3 | 94.4 |
| hobyT | 271.3 | 5.4 | 0.4 | 76.6 | 223.5 | 3.9 | 0.5 | 76.3 |
| hobyY1 | 249.8 | 4.2 | 0.4 | 80.6 | 204.4 | 3.0 | 0.5 | 81.6 |
| hobyY3 | 249.8 | 4.2 | 0.4 | 80.6 | 204.4 | 3.0 | 0.5 | 81.6 |
| navid | 68.5 | 2.2 | 0.7 | 46.9 | 56.5 | 1.6 | 0.8 | 48.7 |
| sanchez | 66.4 | 2.0 | 0.4 | 85.6 | 55.3 | 1.4 | 0.5 | 85.8 |
| somala | 205.5 | 6.2 | 0.4 | 81.6 | 171.8 | 4.5 | 0.5 | 82.1 |
| somala1 | 112.7 | 0.4 | 0.1 | 95.8 | 97.3 | 0.3 | 0.2 | 95.2 |
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The misfit metrics given below are computed for each waveform data and averaged for horizontal components only and for all the components.
1-Norm (sum of average absoluture errors) = Σ|y i - f(xi)|
2-Norm (sum of squares of the errors) = Σ(y i - f(xi))2
Variance Reduction (VR) (scaled sum of the squares of the errors) = 1 - [ Σ(y i - f(xi))2 ] / [ Σ y 2]
Note : The waveform misfits are scaled up by multiplying with 100 to highlight differences in the small values. Additionally, the entries indicated with *, if the waveform data has not been provided.
1-Norm (sum of average absoluture errors) = Σ|y i - f(xi)|
2-Norm (sum of squares of the errors) = Σ(y i - f(xi))2
Variance Reduction (VR) (scaled sum of the squares of the errors) = 1 - [ Σ(y i - f(xi))2 ] / [ Σ y 2]
Note : The waveform misfits are scaled up by multiplying with 100 to highlight differences in the small values. Additionally, the entries indicated with *, if the waveform data has not been provided.