GMS location: 1113

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.979 0.067 0.336 0.397 2.364 NaN NaN
forest winter 2016 0.979 0.067 0.325 0.433 1.935 0.516 2.323
baseline winter 2017 0.972 0.071 0.458 0.466 3.501 NaN NaN
forest winter 2017 0.954 0.048 0.355 0.418 3.144 0.551 3.420
baseline winter 2018 0.966 0.095 0.337 0.415 1.803 NaN NaN
forest winter 2018 0.949 0.095 0.302 0.426 1.448 0.545 2.815
baseline winter 2019 0.992 0.158 0.417 0.481 2.479 NaN NaN
forest winter 2019 0.983 0.105 0.342 0.430 2.390 0.541 3.842
baseline all 0.977 0.093 0.394 0.446 3.501 NaN NaN
forest all 0.964 0.076 0.331 0.425 3.144 0.542 3.209

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.979 0.067 0.336 0.397 2.364 NaN NaN
elr winter 2016 0.979 0.067 0.353 0.440 2.036 0.616 5.270
baseline winter 2017 0.972 0.071 0.458 0.466 3.501 NaN NaN
elr winter 2017 0.963 0.048 0.431 0.475 3.002 0.661 6.458
baseline winter 2018 0.966 0.095 0.337 0.415 1.803 NaN NaN
elr winter 2018 0.949 0.095 0.308 0.448 1.463 0.655 5.001
baseline winter 2019 0.992 0.158 0.417 0.481 2.479 NaN NaN
elr winter 2019 0.992 0.210 0.352 0.440 2.087 0.592 4.392
baseline all 0.977 0.093 0.394 0.446 3.501 NaN NaN
elr all 0.969 0.093 0.362 0.453 3.002 0.635 5.299

Extended logistic regression plots

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