GMS location: 953

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 1.000 0.158 0.358 0.461 1.898 NaN NaN
forest winter 2016 0.995 0.210 0.295 0.409 1.819 0.455 6.884
baseline winter 2017 0.974 0.086 0.337 0.430 2.326 NaN NaN
forest winter 2017 0.991 0.029 0.236 0.358 1.793 0.451 5.661
baseline winter 2018 0.973 0.071 0.337 0.426 2.064 NaN NaN
forest winter 2018 0.973 0.071 0.233 0.339 2.305 0.444 4.644
baseline winter 2019 0.987 0.000e+00 0.307 0.412 2.101 NaN NaN
forest winter 2019 0.987 0.071 0.200 0.349 1.171 0.434 4.143
baseline all 0.985 0.083 0.336 0.434 2.326 NaN NaN
forest all 0.987 0.083 0.245 0.366 2.305 0.447 5.412

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 1.000 0.158 0.358 0.461 1.898 NaN NaN
elr winter 2016 1.000 0.105 0.303 0.421 2.163 0.555 8.032
baseline winter 2017 0.974 0.086 0.337 0.430 2.326 NaN NaN
elr winter 2017 0.983 0.086 0.249 0.377 1.856 0.531 6.277
baseline winter 2018 0.973 0.071 0.337 0.426 2.064 NaN NaN
elr winter 2018 0.980 0.071 0.246 0.358 2.171 0.507 5.252
baseline winter 2019 0.987 0.000e+00 0.307 0.412 2.101 NaN NaN
elr winter 2019 0.980 0.000e+00 0.227 0.372 1.779 0.538 5.576
baseline all 0.985 0.083 0.336 0.434 2.326 NaN NaN
elr all 0.987 0.073 0.259 0.384 2.171 0.534 6.374

Extended logistic regression plots

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