GMS location: 611

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.968 0.105 0.352 0.464 1.602 NaN NaN
forest winter 2016 0.968 0.105 0.272 0.397 1.384 0.498 2.469
baseline winter 2017 0.966 0.111 0.482 0.502 2.835 NaN NaN
forest winter 2017 0.966 0.111 0.409 0.456 2.161 0.479 2.046
baseline winter 2018 0.985 0.108 0.393 0.449 2.830 NaN NaN
forest winter 2018 0.985 0.108 0.360 0.439 3.109 0.497 2.445
baseline winter 2019 0.993 0.071 0.576 0.500 3.670 NaN NaN
forest winter 2019 0.993 0.071 0.519 0.472 3.526 0.496 3.104
baseline all 0.979 0.104 0.451 0.478 3.670 NaN NaN
forest all 0.979 0.104 0.391 0.442 3.526 0.493 2.515

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.968 0.105 0.352 0.464 1.602 NaN NaN
elr winter 2016 0.944 0.053 0.343 0.446 1.631 0.536 2.532
baseline winter 2017 0.966 0.111 0.482 0.502 2.835 NaN NaN
elr winter 2017 0.974 0.139 0.428 0.461 2.367 0.504 2.372
baseline winter 2018 0.985 0.108 0.393 0.449 2.830 NaN NaN
elr winter 2018 0.978 0.027 0.410 0.503 3.132 0.598 3.223
baseline winter 2019 0.993 0.071 0.576 0.500 3.670 NaN NaN
elr winter 2019 0.993 0.071 0.527 0.483 3.775 0.542 3.295
baseline all 0.979 0.104 0.451 0.478 3.670 NaN NaN
elr all 0.973 0.075 0.428 0.475 3.775 0.547 2.874

Extended logistic regression plots

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