GMS location: 1171

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 1.000 0.097 0.409 0.468 2.104 NaN NaN
forest winter 2016 0.994 0.097 0.299 0.405 1.825 0.561 2.599
baseline winter 2017 0.983 0.057 0.524 0.535 2.664 NaN NaN
forest winter 2017 0.983 0.029 0.398 0.456 2.233 0.567 3.057
baseline winter 2018 0.985 0.214 0.472 0.482 3.303 NaN NaN
forest winter 2018 0.985 0.143 0.411 0.439 3.221 0.589 2.819
baseline winter 2019 0.986 0.077 0.441 0.502 2.130 NaN NaN
forest winter 2019 0.986 0.000e+00 0.300 0.412 1.754 0.600 3.090
baseline all 0.990 0.124 0.458 0.494 3.303 NaN NaN
forest all 0.988 0.083 0.350 0.426 3.221 0.579 2.869

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 0.097 0.409 0.468 2.104 NaN NaN
elr winter 2016 0.983 0.032 0.348 0.469 1.884 0.660 4.550
baseline winter 2017 0.983 0.057 0.524 0.535 2.664 NaN NaN
elr winter 2017 0.975 0.029 0.473 0.541 2.183 0.678 5.060
baseline winter 2018 0.985 0.214 0.472 0.482 3.303 NaN NaN
elr winter 2018 0.985 0.238 0.420 0.474 2.944 0.654 4.521
baseline winter 2019 0.986 0.077 0.441 0.502 2.130 NaN NaN
elr winter 2019 0.986 0.000e+00 0.343 0.455 1.847 0.639 4.367
baseline all 0.990 0.124 0.458 0.494 3.303 NaN NaN
elr all 0.983 0.099 0.393 0.483 2.944 0.658 4.613

Extended logistic regression plots

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