GMS location: 605

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.995 0.095 0.378 0.459 2.183 NaN NaN
forest winter 2016 0.989 0.095 0.335 0.432 1.702 0.558 3.205
baseline winter 2017 1.000 0.053 0.482 0.493 2.814 NaN NaN
forest winter 2017 1.000 0.053 0.402 0.455 2.080 0.517 3.173
baseline winter 2018 1.000 0.036 0.443 0.480 2.371 NaN NaN
forest winter 2018 0.993 0.036 0.394 0.474 2.037 0.549 3.448
baseline winter 2019 1.000 0.000e+00 0.265 0.379 1.671 NaN NaN
forest winter 2019 1.000 0.000e+00 0.189 0.334 1.255 0.542 2.453
baseline all 0.998 0.050 0.391 0.453 2.814 NaN NaN
forest all 0.995 0.050 0.330 0.424 2.080 0.543 3.083

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 0.378 0.459 2.183 NaN NaN
elr winter 2016 0.978 0.095 0.365 0.474 1.941 0.682 5.223
baseline winter 2017 1.000 0.053 0.482 0.493 2.814 NaN NaN
elr winter 2017 0.991 0.053 0.379 0.456 2.200 0.611 4.545
baseline winter 2018 1.000 0.036 0.443 0.480 2.371 NaN NaN
elr winter 2018 0.987 0.071 0.422 0.507 1.975 0.645 5.175
baseline winter 2019 1.000 0.000e+00 0.265 0.379 1.671 NaN NaN
elr winter 2019 1.000 0.000e+00 0.238 0.386 1.374 0.566 3.074
baseline all 0.998 0.050 0.391 0.453 2.814 NaN NaN
elr all 0.988 0.059 0.353 0.458 2.200 0.630 4.558

Extended logistic regression plots

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