GMS location: 521

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.982 0.048 0.391 0.473 2.601 NaN NaN
forest winter 2016 0.994 0.048 0.296 0.410 2.404 0.523 3.943
baseline winter 2017 0.983 0.094 0.420 0.470 2.738 NaN NaN
forest winter 2017 0.983 0.125 0.316 0.402 2.063 0.504 3.814
baseline winter 2018 0.993 0.071 0.354 0.421 2.344 NaN NaN
forest winter 2018 0.993 0.071 0.310 0.405 2.238 0.530 3.433
baseline winter 2019 0.993 0.000e+00 0.264 0.388 1.626 NaN NaN
forest winter 2019 0.993 0.000e+00 0.193 0.327 1.309 0.514 3.176
baseline all 0.988 0.065 0.358 0.439 2.738 NaN NaN
forest all 0.991 0.076 0.280 0.387 2.404 0.518 3.603

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.982 0.048 0.391 0.473 2.601 NaN NaN
elr winter 2016 0.982 0.048 0.335 0.440 2.334 0.607 6.403
baseline winter 2017 0.983 0.094 0.420 0.470 2.738 NaN NaN
elr winter 2017 0.983 0.062 0.410 0.450 2.810 0.581 6.119
baseline winter 2018 0.993 0.071 0.354 0.421 2.344 NaN NaN
elr winter 2018 0.993 0.107 0.339 0.450 2.352 0.625 6.312
baseline winter 2019 0.993 0.000e+00 0.264 0.388 1.626 NaN NaN
elr winter 2019 0.993 0.000e+00 0.230 0.368 1.326 0.554 4.293
baseline all 0.988 0.065 0.358 0.439 2.738 NaN NaN
elr all 0.988 0.065 0.329 0.428 2.810 0.593 5.815

Extended logistic regression plots

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