Table 1 Performance comparison for drifter and crane datasets using SplineCurve, SplineCurve_Ind, SmoothSpline, GAM and K-Smooth methods. SplineCurve_Ind represents the result of applying the SplineCurve method to univariate data. The mean and standard deviation (values in parentheses) of the MSE, MAE, and MXDV from 50 random sampling trials are presented.
From: Efficient curve fitting with penalized B-splines for oceanographic and ecological applications
Data | Method | MSE | MAE | MXDV |
|---|---|---|---|---|
Drifter | SplineCurve | 0.1157 (0.0025) | 0.2514 (0.0028) | 0.9486 (0.0107) |
SplineCurve_Ind | 0.1146 (0.0025) | 0.2499 (0.0028) | 0.9399 (0.0108) | |
SmoothSpline | 0.1134 (0.0024) | 0.2479 (0.0028) | 0.9444 (0.0113) | |
GAM | 0.1138 (0.0024) | 0.2513 (0.0028) | 0.9313 (0.0113) | |
K-Smooth | 0.1160 (0.0025) | 0.2554 (0.0028) | 0.9337 (0.0096) | |
Crane | SplineCurve | 11.3931 (0.1199) | 1.8034 (0.0053) | 33.9721 (0.4086) |
SplineCurve_Ind | 5.6981 (0.0600) | 1.1298 (0.0032) | 33.9469 (0.4084) | |
SmoothSpline | 11.4142 (0.1131) | 1.7975 (0.0049) | 34.0229 (0.4844) | |
GAM | 15.2868 (0.0304) | 2.3014 (0.0034) | 32.0444 (0.1393) | |
K-Smooth | 11.1998 (0.1099) | 1.7708 (0.0049) | 33.3594 (0.4569) |
