GMS location: 1004

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.990 0.071 0.317 0.392 2.501 NaN NaN
forest winter 2016 0.990 0.071 0.290 0.387 1.944 0.504 2.950
baseline winter 2017 0.977 0.040 0.475 0.488 2.521 NaN NaN
forest winter 2017 0.977 0.080 0.394 0.448 2.262 0.505 4.720
baseline winter 2018 0.980 0.053 0.352 0.459 1.718 NaN NaN
forest winter 2018 0.974 0.053 0.274 0.398 1.303 0.514 3.015
baseline winter 2019 1.000 0.071 0.264 0.377 1.739 NaN NaN
forest winter 2019 1.000 0.071 0.226 0.341 1.620 0.512 2.996
baseline all 0.987 0.056 0.349 0.427 2.521 NaN NaN
forest all 0.985 0.069 0.294 0.393 2.262 0.508 3.371

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.990 0.071 0.317 0.392 2.501 NaN NaN
elr winter 2016 0.990 0.071 0.296 0.410 2.269 0.585 4.599
baseline winter 2017 0.977 0.040 0.475 0.488 2.521 NaN NaN
elr winter 2017 0.969 0.040 0.408 0.476 2.070 0.588 5.447
baseline winter 2018 0.980 0.053 0.352 0.459 1.718 NaN NaN
elr winter 2018 0.974 0.053 0.293 0.431 1.556 0.565 4.120
baseline winter 2019 1.000 0.071 0.264 0.377 1.739 NaN NaN
elr winter 2019 1.000 0.071 0.235 0.378 1.489 0.561 3.715
baseline all 0.987 0.056 0.349 0.427 2.521 NaN NaN
elr all 0.984 0.056 0.306 0.423 2.269 0.575 4.468

Extended logistic regression plots

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