GMS location: 508

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.989 0.056 0.359 0.470 1.799 NaN NaN
forest winter 2016 0.989 0.056 0.274 0.400 1.599 0.480 4.015
baseline winter 2017 0.968 0.000e+00 0.395 0.480 2.054 NaN NaN
forest winter 2017 0.952 0.000e+00 0.282 0.404 1.697 0.484 3.735
baseline winter 2018 1.000 0.207 0.332 0.440 2.131 NaN NaN
forest winter 2018 1.000 0.207 0.269 0.396 1.852 0.495 3.275
baseline winter 2019 0.993 0.091 0.247 0.364 1.974 NaN NaN
forest winter 2019 0.993 0.091 0.210 0.353 1.228 0.476 2.953
baseline all 0.989 0.093 0.334 0.440 2.131 NaN NaN
forest all 0.985 0.093 0.260 0.389 1.852 0.484 3.520

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.989 0.056 0.359 0.470 1.799 NaN NaN
elr winter 2016 0.989 0.056 0.302 0.423 1.595 0.573 6.378
baseline winter 2017 0.968 0.000e+00 0.395 0.480 2.054 NaN NaN
elr winter 2017 0.960 0.000e+00 0.343 0.449 1.732 0.528 5.267
baseline winter 2018 1.000 0.207 0.332 0.440 2.131 NaN NaN
elr winter 2018 1.000 0.172 0.275 0.401 1.764 0.576 6.152
baseline winter 2019 0.993 0.091 0.247 0.364 1.974 NaN NaN
elr winter 2019 0.993 0.091 0.277 0.421 1.279 0.563 5.335
baseline all 0.989 0.093 0.334 0.440 2.131 NaN NaN
elr all 0.987 0.081 0.298 0.422 1.764 0.562 5.839

Extended logistic regression plots

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