GMS location: 531

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.995 0.091 0.341 0.430 2.017 NaN NaN
forest winter 2016 1.000 0.136 0.276 0.390 1.817 0.452 2.611
baseline winter 2017 0.953 0.042 0.541 0.531 2.526 NaN NaN
forest winter 2017 0.969 0.042 0.357 0.440 2.171 0.457 3.752
baseline winter 2018 0.981 0.059 0.638 0.556 3.150 NaN NaN
forest winter 2018 0.981 0.059 0.444 0.455 2.985 0.465 2.453
baseline winter 2019 0.987 0.000e+00 0.301 0.405 2.004 NaN NaN
forest winter 2019 0.993 0.100 0.233 0.356 2.046 0.472 2.639
baseline all 0.980 0.055 0.451 0.478 3.150 NaN NaN
forest all 0.987 0.082 0.326 0.410 2.985 0.461 2.829

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 0.091 0.341 0.430 2.017 NaN NaN
elr winter 2016 0.995 0.000e+00 0.302 0.419 1.690 0.538 3.274
baseline winter 2017 0.953 0.042 0.541 0.531 2.526 NaN NaN
elr winter 2017 0.961 0.042 0.369 0.462 2.029 0.544 3.454
baseline winter 2018 0.981 0.059 0.638 0.556 3.150 NaN NaN
elr winter 2018 0.974 0.059 0.453 0.459 3.154 0.538 3.915
baseline winter 2019 0.987 0.000e+00 0.301 0.405 2.004 NaN NaN
elr winter 2019 0.993 0.100 0.268 0.401 1.973 0.517 2.831
baseline all 0.980 0.055 0.451 0.478 3.150 NaN NaN
elr all 0.982 0.041 0.347 0.435 3.154 0.534 3.373

Extended logistic regression plots

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