GMS location: 1109

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 1.000 0.105 0.279 0.397 1.770 NaN NaN
forest winter 2016 0.994 0.053 0.248 0.367 1.684 0.496 3.774
baseline winter 2017 0.963 0.091 0.467 0.495 3.382 NaN NaN
forest winter 2017 0.973 0.068 0.396 0.444 3.144 0.517 6.180
baseline winter 2018 0.992 0.119 0.295 0.392 1.873 NaN NaN
forest winter 2018 1.000 0.119 0.269 0.386 1.497 0.502 3.759
baseline winter 2019 0.992 0.133 0.324 0.406 1.636 NaN NaN
forest winter 2019 0.992 0.133 0.242 0.362 1.565 0.501 4.205
baseline all 0.989 0.108 0.335 0.420 3.382 NaN NaN
forest all 0.991 0.086 0.286 0.388 3.144 0.504 4.412

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 0.105 0.279 0.397 1.770 NaN NaN
elr winter 2016 0.988 0.053 0.254 0.395 1.639 0.569 5.030
baseline winter 2017 0.963 0.091 0.467 0.495 3.382 NaN NaN
elr winter 2017 0.963 0.068 0.387 0.450 3.010 0.552 5.290
baseline winter 2018 0.992 0.119 0.295 0.392 1.873 NaN NaN
elr winter 2018 0.992 0.119 0.293 0.424 1.637 0.579 5.314
baseline winter 2019 0.992 0.133 0.324 0.406 1.636 NaN NaN
elr winter 2019 0.992 0.133 0.268 0.412 1.643 0.571 5.054
baseline all 0.989 0.108 0.335 0.420 3.382 NaN NaN
elr all 0.985 0.086 0.297 0.418 3.010 0.568 5.166

Extended logistic regression plots

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