GMS location: 1105

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.994 0.132 0.386 0.435 2.845 NaN NaN
forest winter 2016 0.988 0.132 0.346 0.411 2.676 0.517 2.803
baseline winter 2017 0.980 0.053 0.460 0.473 2.215 NaN NaN
forest winter 2017 0.980 0.053 0.425 0.453 2.256 0.535 4.085
baseline winter 2018 0.983 0.139 0.387 0.455 2.609 NaN NaN
forest winter 2018 0.992 0.083 0.350 0.444 2.429 0.535 2.892
baseline winter 2019 0.992 0.091 0.271 0.386 1.617 NaN NaN
forest winter 2019 0.992 0.000e+00 0.197 0.332 1.313 0.521 2.530
baseline all 0.988 0.106 0.378 0.438 2.845 NaN NaN
forest all 0.988 0.081 0.333 0.411 2.676 0.526 3.049

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.994 0.132 0.386 0.435 2.845 NaN NaN
elr winter 2016 0.994 0.132 0.362 0.432 2.767 0.574 3.896
baseline winter 2017 0.980 0.053 0.460 0.473 2.215 NaN NaN
elr winter 2017 0.980 0.026 0.424 0.463 2.252 0.590 4.846
baseline winter 2018 0.983 0.139 0.387 0.455 2.609 NaN NaN
elr winter 2018 0.966 0.056 0.382 0.483 2.157 0.621 5.249
baseline winter 2019 0.992 0.091 0.271 0.386 1.617 NaN NaN
elr winter 2019 1.000 0.091 0.247 0.380 1.502 0.565 3.580
baseline all 0.988 0.106 0.378 0.438 2.845 NaN NaN
elr all 0.986 0.073 0.356 0.440 2.767 0.587 4.367

Extended logistic regression plots

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