GMS location: 1237

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.994 0.062 0.429 0.459 2.768 NaN NaN
forest winter 2016 0.994 0.062 0.331 0.410 2.564 0.551 2.438
baseline winter 2017 0.991 0.054 0.592 0.548 2.600 NaN NaN
forest winter 2017 0.983 0.027 0.499 0.516 2.514 0.550 3.220
baseline winter 2018 0.987 0.029 0.482 0.490 2.723 NaN NaN
forest winter 2018 0.953 0.029 0.468 0.488 2.995 0.585 2.850
baseline winter 2019 0.993 0.000e+00 0.337 0.412 2.124 NaN NaN
forest winter 2019 0.993 0.000e+00 0.264 0.390 1.552 0.573 2.441
baseline all 0.991 0.044 0.460 0.477 2.768 NaN NaN
forest all 0.981 0.035 0.391 0.450 2.995 0.565 2.722

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.994 0.062 0.429 0.459 2.768 NaN NaN
elr winter 2016 0.989 0.062 0.349 0.437 2.599 0.617 3.429
baseline winter 2017 0.991 0.054 0.592 0.548 2.600 NaN NaN
elr winter 2017 0.983 0.000e+00 0.515 0.533 2.217 0.615 4.519
baseline winter 2018 0.987 0.029 0.482 0.490 2.723 NaN NaN
elr winter 2018 0.953 0.029 0.463 0.497 2.884 0.643 4.102
baseline winter 2019 0.993 0.000e+00 0.337 0.412 2.124 NaN NaN
elr winter 2019 0.993 0.000e+00 0.353 0.480 1.829 0.584 3.096
baseline all 0.991 0.044 0.460 0.477 2.768 NaN NaN
elr all 0.979 0.026 0.417 0.483 2.884 0.616 3.779

Extended logistic regression plots

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