GMS location: 1107

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.982 0.097 0.338 0.410 2.394 NaN NaN
forest winter 2016 0.959 0.065 0.317 0.388 2.332 0.490 3.281
baseline winter 2017 0.982 0.049 0.492 0.473 2.773 NaN NaN
forest winter 2017 0.991 0.000e+00 0.382 0.424 2.100 0.497 3.744
baseline winter 2018 0.993 0.184 0.453 0.476 2.509 NaN NaN
forest winter 2018 0.986 0.184 0.402 0.450 2.393 0.481 3.404
baseline winter 2019 0.993 0.000e+00 0.269 0.368 1.992 NaN NaN
forest winter 2019 0.993 0.000e+00 0.220 0.353 1.489 0.482 3.331
baseline all 0.988 0.098 0.388 0.432 2.773 NaN NaN
forest all 0.980 0.074 0.333 0.405 2.393 0.488 3.428

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 0.097 0.338 0.410 2.394 NaN NaN
elr winter 2016 0.977 0.065 0.340 0.418 2.448 0.568 3.853
baseline winter 2017 0.982 0.049 0.492 0.473 2.773 NaN NaN
elr winter 2017 0.973 0.024 0.464 0.468 2.749 0.554 3.849
baseline winter 2018 0.993 0.184 0.453 0.476 2.509 NaN NaN
elr winter 2018 0.993 0.210 0.479 0.506 2.629 0.569 4.762
baseline winter 2019 0.993 0.000e+00 0.269 0.368 1.992 NaN NaN
elr winter 2019 0.993 0.000e+00 0.286 0.420 1.782 0.523 2.937
baseline all 0.988 0.098 0.388 0.432 2.773 NaN NaN
elr all 0.984 0.090 0.393 0.453 2.749 0.555 3.893

Extended logistic regression plots

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