GMS location: 1417

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.994 0.065 0.307 0.392 3.087 NaN NaN
forest winter 2016 0.994 0.032 0.267 0.367 2.874 0.474 3.902
baseline winter 2017 0.981 0.023 0.370 0.449 1.725 NaN NaN
forest winter 2017 0.990 0.045 0.295 0.407 1.473 0.472 3.646
baseline winter 2018 0.986 0.059 0.364 0.416 2.703 NaN NaN
forest winter 2018 0.972 0.088 0.294 0.368 2.522 0.465 2.951
baseline winter 2019 0.979 0.118 0.417 0.479 1.941 NaN NaN
forest winter 2019 1.000 0.118 0.307 0.411 1.683 0.452 3.013
baseline all 0.985 0.056 0.362 0.431 3.087 NaN NaN
forest all 0.989 0.064 0.290 0.386 2.874 0.466 3.384

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 0.065 0.307 0.392 3.087 NaN NaN
elr winter 2016 1.000 0.097 0.286 0.396 2.750 0.532 3.990
baseline winter 2017 0.981 0.023 0.370 0.449 1.725 NaN NaN
elr winter 2017 0.981 0.045 0.321 0.416 1.464 0.504 3.575
baseline winter 2018 0.986 0.059 0.364 0.416 2.703 NaN NaN
elr winter 2018 0.986 0.088 0.295 0.376 2.343 0.533 4.285
baseline winter 2019 0.979 0.118 0.417 0.479 1.941 NaN NaN
elr winter 2019 1.000 0.118 0.340 0.444 1.992 0.498 3.612
baseline all 0.985 0.056 0.362 0.431 3.087 NaN NaN
elr all 0.993 0.079 0.309 0.406 2.750 0.518 3.889

Extended logistic regression plots

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