GMS location: 962

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 1.000 0.000e+00 0.457 0.478 3.176 NaN NaN
forest winter 2016 0.973 0.000e+00 0.436 0.481 3.246 0.530 4.728
baseline winter 2017 0.983 0.083 0.459 0.466 2.730 NaN NaN
forest winter 2017 0.957 0.000e+00 0.397 0.437 2.571 0.540 2.305
baseline winter 2018 0.980 0.156 0.328 0.384 2.241 NaN NaN
forest winter 2018 0.970 0.094 0.321 0.415 2.028 0.541 2.226
baseline all 0.990 0.092 0.422 0.449 3.176 NaN NaN
forest all 0.968 0.035 0.393 0.450 3.246 0.536 3.295

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 1.000 0.000e+00 0.457 0.478 3.176 NaN NaN
elr winter 2016 0.968 0.053 0.396 0.465 2.952 0.677 4.927
baseline winter 2017 0.983 0.083 0.459 0.466 2.730 NaN NaN
elr winter 2017 0.966 0.000e+00 0.409 0.457 2.305 0.640 3.871
baseline winter 2018 0.980 0.156 0.328 0.384 2.241 NaN NaN
elr winter 2018 0.980 0.125 0.391 0.472 2.046 0.589 3.255
baseline all 0.990 0.092 0.422 0.449 3.176 NaN NaN
elr all 0.970 0.058 0.399 0.464 2.952 0.642 4.144

Extended logistic regression plots

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