GMS location: 1421

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.983 0.000e+00 0.377 0.449 2.015 NaN NaN
forest winter 2016 1.000 0.000e+00 0.241 0.348 1.894 0.438 3.345
baseline winter 2017 0.990 0.000e+00 0.536 0.518 2.420 NaN NaN
forest winter 2017 1.000 0.000e+00 0.269 0.369 1.916 0.457 4.161
baseline winter 2018 0.980 0.056 0.376 0.444 2.860 NaN NaN
forest winter 2018 0.980 0.056 0.225 0.325 2.563 0.440 4.354
baseline winter 2019 0.993 0.000e+00 0.452 0.500 2.259 NaN NaN
forest winter 2019 1.000 0.000e+00 0.270 0.387 1.559 0.429 4.227
baseline all 0.986 0.017 0.427 0.474 2.860 NaN NaN
forest all 0.995 0.017 0.249 0.355 2.563 0.440 3.985

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.983 0.000e+00 0.377 0.449 2.015 NaN NaN
elr winter 2016 0.989 0.000e+00 0.287 0.397 1.876 0.501 3.904
baseline winter 2017 0.990 0.000e+00 0.536 0.518 2.420 NaN NaN
elr winter 2017 1.000 0.000e+00 0.308 0.418 1.823 0.487 3.727
baseline winter 2018 0.980 0.056 0.376 0.444 2.860 NaN NaN
elr winter 2018 0.980 0.028 0.291 0.374 3.062 0.489 3.629
baseline winter 2019 0.993 0.000e+00 0.452 0.500 2.259 NaN NaN
elr winter 2019 1.000 0.000e+00 0.375 0.472 1.922 0.537 4.940
baseline all 0.986 0.017 0.427 0.474 2.860 NaN NaN
elr all 0.991 8.500e-03 0.312 0.413 3.062 0.503 4.032

Extended logistic regression plots

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