GMS location: 719

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 1.000 0.000e+00 0.328 0.402 2.400 NaN NaN
forest winter 2016 1.000 0.133 0.286 0.391 2.092 0.449 2.933
baseline winter 2017 0.984 0.154 0.465 0.488 2.501 NaN NaN
forest winter 2017 0.984 0.154 0.346 0.423 2.411 0.458 3.453
baseline winter 2018 0.972 0.250 0.311 0.422 1.700 NaN NaN
forest winter 2018 0.979 0.167 0.241 0.374 1.442 0.446 2.279
baseline winter 2019 0.980 0.000e+00 0.291 0.402 1.956 NaN NaN
forest winter 2019 0.993 0.000e+00 0.228 0.356 1.819 0.431 2.350
baseline all 0.985 0.109 0.346 0.426 2.501 NaN NaN
forest all 0.990 0.125 0.275 0.386 2.411 0.446 2.760

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 1.000 0.000e+00 0.328 0.402 2.400 NaN NaN
elr winter 2016 1.000 0.067 0.276 0.384 2.207 0.498 3.886
baseline winter 2017 0.984 0.154 0.465 0.488 2.501 NaN NaN
elr winter 2017 0.976 0.154 0.355 0.447 2.238 0.520 5.013
baseline winter 2018 0.972 0.250 0.311 0.422 1.700 NaN NaN
elr winter 2018 0.972 0.250 0.260 0.394 1.571 0.492 3.401
baseline winter 2019 0.980 0.000e+00 0.291 0.402 1.956 NaN NaN
elr winter 2019 0.986 0.000e+00 0.247 0.381 1.530 0.491 3.424
baseline all 0.985 0.109 0.346 0.426 2.501 NaN NaN
elr all 0.985 0.125 0.283 0.400 2.238 0.500 3.917

Extended logistic regression plots

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