GMS location: 534

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 1.000 0.043 0.381 0.454 1.937 NaN NaN
forest winter 2016 1.000 0.043 0.283 0.396 1.814 0.561 2.901
baseline winter 2017 0.992 0.062 0.585 0.575 2.440 NaN NaN
forest winter 2017 0.984 0.062 0.517 0.518 2.401 0.555 3.545
baseline winter 2018 0.966 0.000e+00 0.401 0.404 3.668 NaN NaN
forest winter 2018 0.966 0.000e+00 0.426 0.426 3.846 0.597 3.719
baseline winter 2019 0.993 0.105 0.244 0.349 2.300 NaN NaN
forest winter 2019 0.993 0.158 0.218 0.334 1.989 0.564 2.899
baseline all 0.988 0.050 0.399 0.444 3.668 NaN NaN
forest all 0.986 0.059 0.356 0.416 3.846 0.569 3.250

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 0.043 0.381 0.454 1.937 NaN NaN
elr winter 2016 0.994 0.043 0.335 0.450 1.753 0.649 4.812
baseline winter 2017 0.992 0.062 0.585 0.575 2.440 NaN NaN
elr winter 2017 0.984 0.062 0.469 0.516 2.405 0.616 5.617
baseline winter 2018 0.966 0.000e+00 0.401 0.404 3.668 NaN NaN
elr winter 2018 0.980 0.000e+00 0.297 0.404 2.243 0.692 6.754
baseline winter 2019 0.993 0.105 0.244 0.349 2.300 NaN NaN
elr winter 2019 1.000 0.158 0.254 0.388 1.931 0.647 4.332
baseline all 0.988 0.050 0.399 0.444 3.668 NaN NaN
elr all 0.990 0.059 0.336 0.438 2.405 0.652 5.368

Extended logistic regression plots

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