GMS location: 1201

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.995 0.095 0.338 0.444 1.799 NaN NaN
forest winter 2016 0.989 0.095 0.276 0.403 1.681 0.571 4.550
baseline winter 2017 0.992 0.000e+00 0.582 0.568 2.738 NaN NaN
forest winter 2017 0.992 0.000e+00 0.447 0.492 2.262 0.537 5.273
baseline winter 2018 0.980 0.107 0.325 0.434 2.236 NaN NaN
forest winter 2018 0.974 0.071 0.277 0.410 1.974 0.560 4.318
baseline winter 2019 0.993 0.083 0.277 0.395 1.634 NaN NaN
forest winter 2019 0.993 0.083 0.226 0.353 1.750 0.574 4.913
baseline all 0.990 0.062 0.375 0.458 2.738 NaN NaN
forest all 0.987 0.052 0.303 0.413 2.262 0.561 4.730

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 0.095 0.338 0.444 1.799 NaN NaN
elr winter 2016 0.989 0.048 0.303 0.440 1.829 0.655 6.599
baseline winter 2017 0.992 0.000e+00 0.582 0.568 2.738 NaN NaN
elr winter 2017 0.992 0.000e+00 0.444 0.494 2.308 0.595 6.957
baseline winter 2018 0.980 0.107 0.325 0.434 2.236 NaN NaN
elr winter 2018 0.974 0.071 0.293 0.427 1.728 0.651 5.650
baseline winter 2019 0.993 0.083 0.277 0.395 1.634 NaN NaN
elr winter 2019 0.993 0.083 0.265 0.411 1.757 0.622 5.209
baseline all 0.990 0.062 0.375 0.458 2.738 NaN NaN
elr all 0.987 0.042 0.323 0.442 2.308 0.634 6.124

Extended logistic regression plots

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