GMS location: 410

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 1.000 0.103 0.340 0.414 2.313 NaN NaN
forest winter 2016 0.994 0.103 0.309 0.390 2.617 0.484 2.562
baseline winter 2017 0.955 0.024 0.293 0.428 1.937 NaN NaN
forest winter 2017 0.937 0.024 0.216 0.364 1.160 0.467 2.391
baseline winter 2018 1.000 0.098 0.297 0.407 1.601 NaN NaN
forest winter 2018 0.992 0.073 0.266 0.389 1.665 0.474 2.137
baseline winter 2019 1.000 0.107 0.620 0.533 2.699 NaN NaN
forest winter 2019 1.000 0.179 0.626 0.535 3.015 0.495 3.294
baseline all 0.990 0.079 0.381 0.442 2.699 NaN NaN
forest all 0.983 0.086 0.348 0.416 3.015 0.480 2.579

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 1.000 0.103 0.340 0.414 2.313 NaN NaN
elr winter 2016 0.994 0.069 0.278 0.391 2.159 0.596 4.154
baseline winter 2017 0.955 0.024 0.293 0.428 1.937 NaN NaN
elr winter 2017 0.946 0.024 0.216 0.363 1.399 0.535 2.946
baseline winter 2018 1.000 0.098 0.297 0.407 1.601 NaN NaN
elr winter 2018 1.000 0.073 0.262 0.397 1.741 0.550 3.228
baseline winter 2019 1.000 0.107 0.620 0.533 2.699 NaN NaN
elr winter 2019 1.000 0.214 0.654 0.562 3.008 0.551 5.968
baseline all 0.990 0.079 0.381 0.442 2.699 NaN NaN
elr all 0.987 0.086 0.344 0.425 3.008 0.560 4.046

Extended logistic regression plots

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