GMS location: 1115

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.983 0.088 0.398 0.430 2.735 NaN NaN
forest winter 2016 0.954 0.059 0.337 0.399 2.565 0.589 3.695
baseline winter 2017 0.991 0.068 0.381 0.436 2.169 NaN NaN
forest winter 2017 0.981 0.068 0.315 0.396 2.203 0.554 3.132
baseline winter 2018 0.985 0.075 0.393 0.444 2.073 NaN NaN
forest winter 2018 0.985 0.000e+00 0.354 0.458 1.738 0.585 3.478
baseline winter 2019 0.991 0.154 0.426 0.463 2.602 NaN NaN
forest winter 2019 0.991 0.077 0.332 0.425 2.191 0.569 3.278
baseline all 0.987 0.084 0.398 0.442 2.735 NaN NaN
forest all 0.975 0.046 0.336 0.419 2.565 0.576 3.429

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.983 0.088 0.398 0.430 2.735 NaN NaN
elr winter 2016 0.971 0.059 0.342 0.419 2.447 0.633 3.757
baseline winter 2017 0.991 0.068 0.381 0.436 2.169 NaN NaN
elr winter 2017 0.981 0.091 0.411 0.436 3.303 0.647 4.398
baseline winter 2018 0.985 0.075 0.393 0.444 2.073 NaN NaN
elr winter 2018 0.978 0.000e+00 0.344 0.445 1.939 0.636 4.556
baseline winter 2019 0.991 0.154 0.426 0.463 2.602 NaN NaN
elr winter 2019 0.991 0.154 0.393 0.488 2.306 0.616 4.028
baseline all 0.987 0.084 0.398 0.442 2.735 NaN NaN
elr all 0.979 0.061 0.368 0.443 3.303 0.634 4.167

Extended logistic regression plots

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