GMS location: 1231

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.976 0.038 0.410 0.486 2.326 NaN NaN
forest winter 2016 0.982 0.038 0.329 0.430 2.175 0.573 4.054
baseline winter 2017 0.976 0.033 0.384 0.466 1.904 NaN NaN
forest winter 2017 0.968 0.000e+00 0.325 0.432 1.751 0.552 3.263
baseline winter 2018 0.986 0.139 0.438 0.449 3.400 NaN NaN
forest winter 2018 0.979 0.167 0.418 0.437 3.584 0.597 3.927
baseline winter 2019 0.987 0.077 0.310 0.422 1.870 NaN NaN
forest winter 2019 0.993 0.077 0.224 0.358 1.599 0.582 3.686
baseline all 0.981 0.076 0.388 0.457 3.400 NaN NaN
forest all 0.981 0.076 0.326 0.415 3.584 0.577 3.757

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.976 0.038 0.410 0.486 2.326 NaN NaN
elr winter 2016 0.976 0.077 0.336 0.463 1.906 0.672 6.720
baseline winter 2017 0.976 0.033 0.384 0.466 1.904 NaN NaN
elr winter 2017 0.968 0.067 0.359 0.466 1.654 0.636 5.426
baseline winter 2018 0.986 0.139 0.438 0.449 3.400 NaN NaN
elr winter 2018 0.986 0.139 0.400 0.442 2.888 0.639 6.395
baseline winter 2019 0.987 0.077 0.310 0.422 1.870 NaN NaN
elr winter 2019 0.987 0.077 0.240 0.376 1.630 0.630 4.603
baseline all 0.981 0.076 0.388 0.457 3.400 NaN NaN
elr all 0.979 0.095 0.335 0.438 2.888 0.646 5.845

Extended logistic regression plots

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