GMS location: 211

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.977 0.185 0.329 0.426 1.988 NaN NaN
forest winter 2016 0.977 0.074 0.360 0.438 3.033 0.520 1.490
baseline winter 2017 0.964 0.024 0.443 0.481 2.366 NaN NaN
forest winter 2017 0.964 0.024 0.396 0.462 1.907 0.477 1.392
baseline winter 2018 0.986 0.098 1.186 0.745 5.898 NaN NaN
forest winter 2018 0.971 0.098 1.151 0.721 5.717 0.528 1.984
baseline winter 2019 0.973 0.200 1.492 0.671 6.787 NaN NaN
forest winter 2019 0.980 0.200 1.410 0.645 6.893 0.453 1.392
baseline all 0.976 0.108 0.851 0.578 6.787 NaN NaN
forest all 0.974 0.085 0.821 0.565 6.893 0.497 1.571

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.977 0.185 0.329 0.426 1.988 NaN NaN
elr winter 2016 0.977 0.111 0.454 0.505 3.305 0.501 1.285
baseline winter 2017 0.964 0.024 0.443 0.481 2.366 NaN NaN
elr winter 2017 0.973 0.122 0.423 0.491 1.958 0.455 1.189
baseline winter 2018 0.986 0.098 1.186 0.745 5.898 NaN NaN
elr winter 2018 0.957 0.073 1.311 0.763 5.732 0.528 1.544
baseline winter 2019 0.973 0.200 1.492 0.671 6.787 NaN NaN
elr winter 2019 0.973 0.200 1.594 0.686 7.245 0.467 1.464
baseline all 0.976 0.108 0.851 0.578 6.787 NaN NaN
elr all 0.971 0.116 0.939 0.611 7.245 0.490 1.373

Extended logistic regression plots

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