GMS location: 1013

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.995 0.167 0.320 0.411 2.101 NaN NaN
forest winter 2016 0.995 0.167 0.276 0.376 1.874 0.605 6.698
baseline winter 2017 0.985 0.000e+00 0.343 0.402 2.101 NaN NaN
forest winter 2017 0.978 0.000e+00 0.309 0.381 2.169 0.576 5.836
baseline winter 2018 0.994 0.111 0.226 0.358 1.781 NaN NaN
forest winter 2018 1.000 0.111 0.174 0.318 1.444 0.586 5.136
baseline winter 2019 0.993 0.222 0.249 0.375 1.832 NaN NaN
forest winter 2019 1.000 0.222 0.222 0.338 1.625 0.607 5.418
baseline all 0.992 0.100 0.285 0.388 2.101 NaN NaN
forest all 0.994 0.100 0.245 0.354 2.169 0.594 5.823

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 0.167 0.320 0.411 2.101 NaN NaN
elr winter 2016 0.995 0.000e+00 0.283 0.384 1.891 0.658 9.111
baseline winter 2017 0.985 0.000e+00 0.343 0.402 2.101 NaN NaN
elr winter 2017 0.956 0.000e+00 0.291 0.388 1.796 0.628 8.491
baseline winter 2018 0.994 0.111 0.226 0.358 1.781 NaN NaN
elr winter 2018 0.968 0.056 0.198 0.340 1.467 0.662 6.758
baseline winter 2019 0.993 0.222 0.249 0.375 1.832 NaN NaN
elr winter 2019 0.987 0.222 0.245 0.371 1.683 0.696 7.884
baseline all 0.992 0.100 0.285 0.388 2.101 NaN NaN
elr all 0.978 0.060 0.255 0.371 1.891 0.661 8.102

Extended logistic regression plots

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