GMS location: 514

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.989 0.048 0.303 0.423 1.563 NaN NaN
forest winter 2016 0.989 0.048 0.237 0.369 1.723 0.486 4.362
baseline winter 2017 0.947 0.079 0.386 0.467 1.822 NaN NaN
forest winter 2017 0.974 0.079 0.286 0.392 1.691 0.483 4.558
baseline winter 2018 0.979 0.154 0.367 0.442 2.045 NaN NaN
forest winter 2018 0.986 0.128 0.282 0.374 2.144 0.487 4.412
baseline winter 2019 1.000 0.000e+00 0.245 0.379 1.598 NaN NaN
forest winter 2019 1.000 0.000e+00 0.172 0.308 1.223 0.490 3.717
baseline all 0.981 0.091 0.327 0.428 2.045 NaN NaN
forest all 0.988 0.082 0.246 0.362 2.144 0.487 4.283

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.989 0.048 0.303 0.423 1.563 NaN NaN
elr winter 2016 0.983 0.048 0.268 0.395 1.668 0.534 5.179
baseline winter 2017 0.947 0.079 0.386 0.467 1.822 NaN NaN
elr winter 2017 0.956 0.079 0.325 0.439 1.686 0.546 5.326
baseline winter 2018 0.979 0.154 0.367 0.442 2.045 NaN NaN
elr winter 2018 0.986 0.128 0.297 0.385 2.263 0.540 5.046
baseline winter 2019 1.000 0.000e+00 0.245 0.379 1.598 NaN NaN
elr winter 2019 1.000 0.000e+00 0.212 0.351 1.350 0.527 4.112
baseline all 0.981 0.091 0.327 0.428 2.045 NaN NaN
elr all 0.983 0.082 0.277 0.393 2.263 0.537 4.950

Extended logistic regression plots

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