GMS location: 1206

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.989 0.037 0.350 0.444 1.632 NaN NaN
forest winter 2016 0.994 0.037 0.275 0.382 1.969 0.477 3.057
baseline winter 2017 0.974 0.028 0.496 0.491 2.914 NaN NaN
forest winter 2017 1.000 0.028 0.366 0.435 2.072 0.492 4.712
baseline winter 2018 0.961 0.036 0.414 0.459 2.184 NaN NaN
forest winter 2018 0.951 0.000e+00 0.367 0.448 2.098 0.500 3.504
baseline winter 2019 1.000 0.071 0.336 0.429 2.440 NaN NaN
forest winter 2019 1.000 0.071 0.246 0.388 1.374 0.502 3.437
baseline all 0.983 0.038 0.395 0.455 2.914 NaN NaN
forest all 0.989 0.029 0.309 0.410 2.098 0.491 3.633

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.989 0.037 0.350 0.444 1.632 NaN NaN
elr winter 2016 0.983 0.074 0.270 0.416 1.464 0.607 4.375
baseline winter 2017 0.974 0.028 0.496 0.491 2.914 NaN NaN
elr winter 2017 0.974 0.028 0.456 0.483 2.932 0.555 4.754
baseline winter 2018 0.961 0.036 0.414 0.459 2.184 NaN NaN
elr winter 2018 0.971 0.071 0.371 0.469 2.021 0.557 4.100
baseline winter 2019 1.000 0.071 0.336 0.429 2.440 NaN NaN
elr winter 2019 1.000 0.143 0.301 0.439 1.648 0.557 3.853
baseline all 0.983 0.038 0.395 0.455 2.914 NaN NaN
elr all 0.983 0.067 0.343 0.448 2.932 0.573 4.291

Extended logistic regression plots

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