GMS location: 1414

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.994 0.083 0.383 0.450 1.855 NaN NaN
forest winter 2016 0.994 0.056 0.356 0.451 1.829 0.545 2.921
baseline winter 2017 0.978 0.048 0.487 0.501 2.846 NaN NaN
forest winter 2017 0.967 0.048 0.430 0.473 2.208 0.528 3.697
baseline winter 2018 0.986 0.051 0.370 0.454 1.996 NaN NaN
forest winter 2018 0.978 0.051 0.340 0.437 1.871 0.519 2.845
baseline winter 2019 0.993 0.158 0.334 0.419 1.946 NaN NaN
forest winter 2019 0.993 0.158 0.297 0.412 1.806 0.534 2.689
baseline all 0.989 0.073 0.389 0.454 2.846 NaN NaN
forest all 0.985 0.066 0.353 0.443 2.208 0.532 3.001

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 0.083 0.383 0.450 1.855 NaN NaN
elr winter 2016 0.994 0.028 0.352 0.457 1.751 0.599 4.505
baseline winter 2017 0.978 0.048 0.487 0.501 2.846 NaN NaN
elr winter 2017 0.967 0.071 0.455 0.492 2.675 0.573 4.131
baseline winter 2018 0.986 0.051 0.370 0.454 1.996 NaN NaN
elr winter 2018 0.971 0.051 0.401 0.484 2.070 0.596 4.209
baseline winter 2019 0.993 0.158 0.334 0.419 1.946 NaN NaN
elr winter 2019 0.993 0.105 0.317 0.414 2.085 0.573 3.414
baseline all 0.989 0.073 0.389 0.454 2.846 NaN NaN
elr all 0.983 0.059 0.377 0.461 2.675 0.587 4.100

Extended logistic regression plots

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