GMS location: 1412

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.994 0.132 0.452 0.485 2.765 NaN NaN
forest winter 2016 0.994 0.105 0.412 0.436 2.765 0.470 2.096
baseline winter 2017 0.971 0.062 0.555 0.536 3.182 NaN NaN
forest winter 2017 0.981 0.042 0.497 0.504 2.497 0.480 2.099
baseline winter 2018 0.993 0.048 0.397 0.489 2.145 NaN NaN
forest winter 2018 0.977 0.000e+00 0.328 0.440 1.906 0.486 1.916
baseline winter 2019 0.979 0.071 0.381 0.459 2.177 NaN NaN
forest winter 2019 0.986 0.286 0.337 0.432 2.287 0.481 1.909
baseline all 0.985 0.077 0.445 0.492 3.182 NaN NaN
forest all 0.985 0.070 0.393 0.451 2.765 0.479 2.009

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 0.452 0.485 2.765 NaN NaN
elr winter 2016 0.994 0.105 0.401 0.452 2.546 0.530 2.802
baseline winter 2017 0.971 0.062 0.555 0.536 3.182 NaN NaN
elr winter 2017 0.991 0.062 0.521 0.525 2.645 0.520 3.162
baseline winter 2018 0.993 0.048 0.397 0.489 2.145 NaN NaN
elr winter 2018 0.962 0.000e+00 0.390 0.478 2.031 0.530 2.614
baseline winter 2019 0.979 0.071 0.381 0.459 2.177 NaN NaN
elr winter 2019 0.986 0.286 0.371 0.473 2.278 0.513 2.508
baseline all 0.985 0.077 0.445 0.492 3.182 NaN NaN
elr all 0.984 0.077 0.418 0.480 2.645 0.524 2.768

Extended logistic regression plots

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