GMS location: 713

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.989 0.000e+00 0.297 0.402 1.751 NaN NaN
forest winter 2016 0.984 0.000e+00 0.290 0.402 1.720 0.492 2.767
baseline winter 2017 0.984 0.067 0.336 0.441 1.729 NaN NaN
forest winter 2017 0.976 0.000e+00 0.317 0.428 1.657 0.469 2.848
baseline winter 2018 0.986 0.062 0.317 0.399 2.640 NaN NaN
forest winter 2018 0.986 0.094 0.301 0.392 2.787 0.498 3.191
baseline winter 2019 0.992 0.154 0.442 0.479 1.905 NaN NaN
forest winter 2019 0.992 0.154 0.392 0.450 1.867 0.490 2.913
baseline all 0.988 0.065 0.340 0.425 2.640 NaN NaN
forest all 0.984 0.054 0.319 0.415 2.787 0.488 2.926

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.989 0.000e+00 0.297 0.402 1.751 NaN NaN
elr winter 2016 0.979 0.000e+00 0.327 0.434 1.844 0.574 4.016
baseline winter 2017 0.984 0.067 0.336 0.441 1.729 NaN NaN
elr winter 2017 0.976 0.033 0.348 0.458 1.592 0.528 3.901
baseline winter 2018 0.986 0.062 0.317 0.399 2.640 NaN NaN
elr winter 2018 0.979 0.062 0.320 0.407 2.867 0.553 4.082
baseline winter 2019 0.992 0.154 0.442 0.479 1.905 NaN NaN
elr winter 2019 0.992 0.154 0.429 0.471 1.950 0.522 3.956
baseline all 0.988 0.065 0.340 0.425 2.640 NaN NaN
elr all 0.981 0.054 0.350 0.440 2.867 0.548 3.995

Extended logistic regression plots

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