GMS location: 1407

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.983 0.069 0.339 0.436 2.184 NaN NaN
forest winter 2016 1.000 0.035 0.299 0.403 2.148 0.449 5.822
baseline winter 2017 0.991 0.053 0.396 0.465 2.779 NaN NaN
forest winter 2017 0.991 0.053 0.345 0.439 2.235 0.446 5.234
baseline winter 2018 0.993 0.147 0.355 0.455 1.780 NaN NaN
forest winter 2018 1.000 0.147 0.282 0.406 1.637 0.454 4.739
baseline winter 2019 0.985 0.000e+00 0.349 0.432 1.799 NaN NaN
forest winter 2019 0.985 0.000e+00 0.278 0.388 1.744 0.452 4.530
baseline all 0.987 0.080 0.358 0.446 2.779 NaN NaN
forest all 0.995 0.071 0.300 0.409 2.235 0.450 5.137

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.983 0.069 0.339 0.436 2.184 NaN NaN
elr winter 2016 0.989 0.103 0.338 0.429 2.329 0.509 4.256
baseline winter 2017 0.991 0.053 0.396 0.465 2.779 NaN NaN
elr winter 2017 0.991 0.026 0.349 0.456 2.554 0.506 4.117
baseline winter 2018 0.993 0.147 0.355 0.455 1.780 NaN NaN
elr winter 2018 1.000 0.147 0.311 0.432 1.733 0.526 4.472
baseline winter 2019 0.985 0.000e+00 0.349 0.432 1.799 NaN NaN
elr winter 2019 0.985 0.000e+00 0.282 0.393 1.814 0.514 3.892
baseline all 0.987 0.080 0.358 0.446 2.779 NaN NaN
elr all 0.991 0.080 0.321 0.428 2.554 0.514 4.199

Extended logistic regression plots

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