GMS location: 714

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.984 0.056 0.302 0.412 1.862 NaN NaN
forest winter 2016 0.995 0.167 0.220 0.363 1.659 0.431 3.123
baseline winter 2017 0.992 0.161 0.344 0.463 1.778 NaN NaN
forest winter 2017 0.984 0.097 0.250 0.383 1.440 0.440 4.910
baseline winter 2018 0.985 0.111 0.392 0.472 2.364 NaN NaN
forest winter 2018 0.993 0.111 0.326 0.402 2.584 0.435 3.478
baseline winter 2019 0.974 0.000e+00 0.332 0.443 1.851 NaN NaN
forest winter 2019 0.974 0.083 0.226 0.365 1.561 0.424 3.322
baseline all 0.984 0.102 0.341 0.445 2.364 NaN NaN
forest all 0.988 0.114 0.255 0.378 2.584 0.433 3.672

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 0.056 0.302 0.412 1.862 NaN NaN
elr winter 2016 0.995 0.167 0.233 0.377 1.656 0.499 4.729
baseline winter 2017 0.992 0.161 0.344 0.463 1.778 NaN NaN
elr winter 2017 0.984 0.097 0.260 0.408 1.521 0.508 4.837
baseline winter 2018 0.985 0.111 0.392 0.472 2.364 NaN NaN
elr winter 2018 0.985 0.148 0.348 0.415 3.072 0.501 5.752
baseline winter 2019 0.974 0.000e+00 0.332 0.443 1.851 NaN NaN
elr winter 2019 0.974 0.000e+00 0.257 0.401 1.715 0.492 4.562
baseline all 0.984 0.102 0.341 0.445 2.364 NaN NaN
elr all 0.986 0.114 0.273 0.399 3.072 0.500 4.980

Extended logistic regression plots

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