GMS location: 517

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.978 0.000e+00 0.277 0.415 1.643 NaN NaN
forest winter 2016 0.994 0.000e+00 0.207 0.350 1.660 0.450 7.094
baseline winter 2017 0.992 0.077 0.328 0.448 1.649 NaN NaN
forest winter 2017 1.000 0.077 0.191 0.351 1.372 0.454 5.775
baseline winter 2018 0.993 0.077 0.270 0.390 1.591 NaN NaN
forest winter 2018 1.000 0.077 0.210 0.348 1.641 0.458 5.275
baseline winter 2019 0.986 0.000e+00 0.242 0.370 1.639 NaN NaN
forest winter 2019 1.000 0.000e+00 0.182 0.315 1.407 0.462 5.401
baseline all 0.986 0.055 0.279 0.406 1.649 NaN NaN
forest all 0.998 0.055 0.198 0.342 1.660 0.456 5.944

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.978 0.000e+00 0.277 0.415 1.643 NaN NaN
elr winter 2016 0.994 0.000e+00 0.223 0.373 1.754 0.515 6.950
baseline winter 2017 0.992 0.077 0.328 0.448 1.649 NaN NaN
elr winter 2017 1.000 0.077 0.238 0.388 1.438 0.501 6.492
baseline winter 2018 0.993 0.077 0.270 0.390 1.591 NaN NaN
elr winter 2018 0.993 0.038 0.229 0.361 1.876 0.515 6.938
baseline winter 2019 0.986 0.000e+00 0.242 0.370 1.639 NaN NaN
elr winter 2019 1.000 0.000e+00 0.175 0.303 1.404 0.503 6.286
baseline all 0.986 0.055 0.279 0.406 1.649 NaN NaN
elr all 0.997 0.041 0.217 0.358 1.876 0.509 6.693

Extended logistic regression plots

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