GMS location: 612

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.982 0.033 0.405 0.456 2.371 NaN NaN
forest winter 2016 0.982 0.033 0.327 0.407 2.143 0.522 3.317
baseline winter 2017 0.964 0.049 0.535 0.533 3.299 NaN NaN
forest winter 2017 0.964 0.073 0.415 0.465 2.521 0.503 3.279
baseline winter 2018 0.986 0.081 0.450 0.474 2.895 NaN NaN
forest winter 2018 0.965 0.054 0.400 0.455 2.630 0.538 3.407
baseline winter 2019 1.000 0.250 0.235 0.343 1.762 NaN NaN
forest winter 2019 1.000 0.250 0.171 0.309 1.329 0.530 2.701
baseline all 0.984 0.075 0.410 0.454 3.299 NaN NaN
forest all 0.978 0.075 0.333 0.412 2.630 0.524 3.200

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.982 0.033 0.405 0.456 2.371 NaN NaN
elr winter 2016 0.982 0.033 0.357 0.442 2.112 0.624 4.663
baseline winter 2017 0.964 0.049 0.535 0.533 3.299 NaN NaN
elr winter 2017 0.973 0.073 0.450 0.485 2.779 0.556 3.900
baseline winter 2018 0.986 0.081 0.450 0.474 2.895 NaN NaN
elr winter 2018 0.972 0.054 0.432 0.479 2.574 0.617 4.674
baseline winter 2019 1.000 0.250 0.235 0.343 1.762 NaN NaN
elr winter 2019 1.000 0.250 0.223 0.386 1.313 0.559 3.013
baseline all 0.984 0.075 0.410 0.454 3.299 NaN NaN
elr all 0.982 0.075 0.369 0.450 2.779 0.593 4.139

Extended logistic regression plots

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