GMS location: 1217

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.987 0.065 0.389 0.464 2.414 NaN NaN
forest winter 2016 0.987 0.129 0.308 0.419 2.292 0.482 3.763
baseline winter 2017 0.974 0.000e+00 0.476 0.488 2.377 NaN NaN
forest winter 2017 0.991 0.000e+00 0.338 0.416 1.785 0.473 3.739
baseline winter 2018 0.993 0.086 0.368 0.464 2.320 NaN NaN
forest winter 2018 0.986 0.029 0.328 0.429 1.799 0.490 2.683
baseline winter 2019 1.000 0.071 0.350 0.413 2.722 NaN NaN
forest winter 2019 1.000 0.071 0.252 0.352 2.380 0.470 2.553
baseline all 0.989 0.053 0.393 0.458 2.722 NaN NaN
forest all 0.991 0.053 0.307 0.406 2.380 0.479 3.183

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.987 0.065 0.389 0.464 2.414 NaN NaN
elr winter 2016 0.987 0.161 0.319 0.442 2.204 0.546 4.188
baseline winter 2017 0.974 0.000e+00 0.476 0.488 2.377 NaN NaN
elr winter 2017 0.991 0.000e+00 0.383 0.461 1.895 0.542 4.477
baseline winter 2018 0.993 0.086 0.368 0.464 2.320 NaN NaN
elr winter 2018 0.986 0.029 0.355 0.463 2.086 0.555 4.276
baseline winter 2019 1.000 0.071 0.350 0.413 2.722 NaN NaN
elr winter 2019 1.000 0.071 0.307 0.414 2.543 0.535 3.912
baseline all 0.989 0.053 0.393 0.458 2.722 NaN NaN
elr all 0.991 0.061 0.340 0.445 2.543 0.545 4.210

Extended logistic regression plots

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