GMS location: 502

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.984 0.053 0.333 0.442 2.018 NaN NaN
forest winter 2016 0.989 0.053 0.259 0.385 1.883 0.507 3.746
baseline winter 2017 0.957 0.028 0.432 0.492 2.433 NaN NaN
forest winter 2017 0.949 0.056 0.318 0.421 1.881 0.497 4.290
baseline winter 2018 0.971 0.069 0.369 0.453 1.896 NaN NaN
forest winter 2018 0.971 0.069 0.291 0.399 1.919 0.515 3.931
baseline winter 2019 1.000 0.083 0.288 0.387 1.854 NaN NaN
forest winter 2019 1.000 0.083 0.245 0.379 1.575 0.505 3.654
baseline all 0.979 0.052 0.355 0.445 2.433 NaN NaN
forest all 0.979 0.062 0.278 0.396 1.919 0.506 3.899

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.984 0.053 0.333 0.442 2.018 NaN NaN
elr winter 2016 0.984 0.053 0.297 0.425 1.683 0.560 3.889
baseline winter 2017 0.957 0.028 0.432 0.492 2.433 NaN NaN
elr winter 2017 0.957 0.083 0.384 0.465 2.278 0.537 4.212
baseline winter 2018 0.971 0.069 0.369 0.453 1.896 NaN NaN
elr winter 2018 0.971 0.069 0.324 0.432 1.867 0.574 4.259
baseline winter 2019 1.000 0.083 0.288 0.387 1.854 NaN NaN
elr winter 2019 1.000 0.083 0.303 0.422 1.962 0.550 3.765
baseline all 0.979 0.052 0.355 0.445 2.433 NaN NaN
elr all 0.979 0.073 0.325 0.435 2.278 0.556 4.031

Extended logistic regression plots

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