GMS location: 511

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.983 0.048 0.324 0.449 1.801 NaN NaN
forest winter 2016 0.994 0.095 0.257 0.385 1.665 0.445 3.325
baseline winter 2017 0.941 0.065 0.401 0.490 2.050 NaN NaN
forest winter 2017 0.992 0.065 0.276 0.401 1.569 0.463 4.075
baseline winter 2018 1.000 0.083 0.367 0.445 2.280 NaN NaN
forest winter 2018 1.000 0.167 0.308 0.403 2.182 0.465 2.999
baseline winter 2019 0.986 0.000e+00 0.293 0.412 1.472 NaN NaN
forest winter 2019 0.993 0.091 0.214 0.351 1.458 0.461 2.951
baseline all 0.979 0.058 0.345 0.449 2.280 NaN NaN
forest all 0.995 0.103 0.264 0.385 2.182 0.458 3.327

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.983 0.048 0.324 0.449 1.801 NaN NaN
elr winter 2016 0.989 0.048 0.310 0.431 2.033 0.521 4.099
baseline winter 2017 0.941 0.065 0.401 0.490 2.050 NaN NaN
elr winter 2017 0.958 0.032 0.325 0.454 1.736 0.516 4.509
baseline winter 2018 1.000 0.083 0.367 0.445 2.280 NaN NaN
elr winter 2018 0.993 0.167 0.339 0.410 2.273 0.508 5.108
baseline winter 2019 0.986 0.000e+00 0.293 0.412 1.472 NaN NaN
elr winter 2019 0.993 0.091 0.259 0.390 1.588 0.516 4.139
baseline all 0.979 0.058 0.345 0.449 2.280 NaN NaN
elr all 0.985 0.081 0.309 0.422 2.273 0.516 4.451

Extended logistic regression plots

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