GMS location: 1202

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.970 0.111 0.348 0.444 2.394 NaN NaN
forest winter 2016 0.964 0.074 0.272 0.393 2.248 0.477 3.054
baseline winter 2017 0.974 0.027 0.630 0.565 2.606 NaN NaN
forest winter 2017 0.974 0.027 0.409 0.461 2.062 0.467 3.644
baseline winter 2018 0.993 0.105 0.349 0.436 2.252 NaN NaN
forest winter 2018 1.000 0.053 0.301 0.409 1.603 0.472 2.455
baseline winter 2019 0.993 0.000e+00 0.300 0.400 1.596 NaN NaN
forest winter 2019 1.000 0.071 0.252 0.382 1.709 0.465 2.666
baseline all 0.983 0.069 0.399 0.458 2.606 NaN NaN
forest all 0.984 0.052 0.305 0.410 2.248 0.471 2.939

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.970 0.111 0.348 0.444 2.394 NaN NaN
elr winter 2016 0.964 0.074 0.286 0.431 2.148 0.556 3.376
baseline winter 2017 0.974 0.027 0.630 0.565 2.606 NaN NaN
elr winter 2017 0.974 0.027 0.492 0.507 2.135 0.522 4.143
baseline winter 2018 0.993 0.105 0.349 0.436 2.252 NaN NaN
elr winter 2018 0.986 0.079 0.338 0.432 1.873 0.553 4.175
baseline winter 2019 0.993 0.000e+00 0.300 0.400 1.596 NaN NaN
elr winter 2019 1.000 0.071 0.289 0.424 1.655 0.519 2.987
baseline all 0.983 0.069 0.399 0.458 2.606 NaN NaN
elr all 0.981 0.060 0.346 0.446 2.148 0.539 3.660

Extended logistic regression plots

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