GMS location: 1431

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.988 0.080 0.324 0.415 2.500 NaN NaN
forest winter 2016 0.976 0.040 0.301 0.397 2.330 0.506 4.315
baseline winter 2017 1.000 0.000e+00 0.519 0.511 2.497 NaN NaN
forest winter 2017 0.991 0.026 0.438 0.480 2.067 0.483 3.487
baseline winter 2018 0.992 0.135 0.274 0.370 1.719 NaN NaN
forest winter 2018 0.984 0.135 0.240 0.364 1.783 0.483 2.914
baseline winter 2019 0.992 0.000e+00 0.295 0.377 2.178 NaN NaN
forest winter 2019 0.992 0.067 0.242 0.357 1.577 0.500 3.208
baseline all 0.992 0.061 0.350 0.418 2.500 NaN NaN
forest all 0.985 0.070 0.305 0.399 2.330 0.493 3.534

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.988 0.080 0.324 0.415 2.500 NaN NaN
elr winter 2016 0.976 0.040 0.321 0.421 2.354 0.542 3.685
baseline winter 2017 1.000 0.000e+00 0.519 0.511 2.497 NaN NaN
elr winter 2017 0.982 0.026 0.507 0.519 2.436 0.557 5.238
baseline winter 2018 0.992 0.135 0.274 0.370 1.719 NaN NaN
elr winter 2018 0.968 0.135 0.267 0.374 1.673 0.530 3.315
baseline winter 2019 0.992 0.000e+00 0.295 0.377 2.178 NaN NaN
elr winter 2019 0.992 0.067 0.283 0.409 1.654 0.511 3.338
baseline all 0.992 0.061 0.350 0.418 2.500 NaN NaN
elr all 0.979 0.070 0.342 0.429 2.436 0.536 3.876

Extended logistic regression plots

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