GMS location: 1108

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.981 0.062 0.395 0.422 2.550 NaN NaN
forest winter 2016 0.962 0.031 0.341 0.401 2.405 0.541 3.062
baseline winter 2017 0.964 0.048 0.465 0.471 2.101 NaN NaN
forest winter 2017 0.964 0.048 0.347 0.411 2.186 0.509 3.342
baseline winter 2018 0.977 0.186 0.399 0.434 3.692 NaN NaN
forest winter 2018 0.977 0.116 0.338 0.413 3.447 0.532 3.667
baseline winter 2019 0.993 0.000e+00 0.302 0.399 2.147 NaN NaN
forest winter 2019 0.986 0.000e+00 0.240 0.371 1.888 0.530 3.281
baseline all 0.980 0.092 0.390 0.431 3.692 NaN NaN
forest all 0.973 0.061 0.318 0.399 3.447 0.529 3.334

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.981 0.062 0.395 0.422 2.550 NaN NaN
elr winter 2016 0.975 0.031 0.352 0.432 2.258 0.618 4.498
baseline winter 2017 0.964 0.048 0.465 0.471 2.101 NaN NaN
elr winter 2017 0.964 0.048 0.381 0.445 2.155 0.529 3.431
baseline winter 2018 0.977 0.186 0.399 0.434 3.692 NaN NaN
elr winter 2018 0.977 0.186 0.366 0.434 3.462 0.591 3.890
baseline winter 2019 0.993 0.000e+00 0.302 0.399 2.147 NaN NaN
elr winter 2019 0.993 0.000e+00 0.276 0.419 1.739 0.557 3.073
baseline all 0.980 0.092 0.390 0.431 3.692 NaN NaN
elr all 0.978 0.085 0.344 0.433 3.462 0.577 3.766

Extended logistic regression plots

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