GMS location: 712

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.995 0.000e+00 0.288 0.405 1.636 NaN NaN
forest winter 2016 1.000 0.000e+00 0.231 0.361 1.691 0.461 4.911
baseline winter 2017 0.968 0.100 0.325 0.437 2.010 NaN NaN
forest winter 2017 0.976 0.033 0.249 0.381 1.536 0.470 4.931
baseline winter 2018 0.986 0.115 0.279 0.410 1.726 NaN NaN
forest winter 2018 0.986 0.115 0.235 0.373 1.685 0.463 4.126
baseline winter 2019 0.993 0.000e+00 0.237 0.334 1.950 NaN NaN
forest winter 2019 0.993 0.083 0.218 0.343 1.536 0.460 4.693
baseline all 0.986 0.071 0.283 0.398 2.010 NaN NaN
forest all 0.990 0.059 0.234 0.365 1.691 0.463 4.666

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.995 0.000e+00 0.288 0.405 1.636 NaN NaN
elr winter 2016 1.000 0.000e+00 0.228 0.365 1.672 0.510 6.045
baseline winter 2017 0.968 0.100 0.325 0.437 2.010 NaN NaN
elr winter 2017 0.976 0.067 0.257 0.399 1.683 0.533 7.392
baseline winter 2018 0.986 0.115 0.279 0.410 1.726 NaN NaN
elr winter 2018 0.986 0.115 0.232 0.377 1.714 0.496 5.123
baseline winter 2019 0.993 0.000e+00 0.237 0.334 1.950 NaN NaN
elr winter 2019 0.993 0.083 0.238 0.352 1.820 0.496 5.732
baseline all 0.986 0.071 0.283 0.398 2.010 NaN NaN
elr all 0.990 0.071 0.238 0.373 1.820 0.509 6.048

Extended logistic regression plots

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