GMS location: 1418

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 1.000 0.031 0.499 0.519 3.316 NaN NaN
forest winter 2016 0.987 0.031 0.429 0.470 3.255 0.501 3.654
baseline winter 2017 0.981 0.089 0.290 0.382 2.312 NaN NaN
forest winter 2017 0.981 0.067 0.282 0.391 2.047 0.534 2.681
baseline winter 2018 0.993 0.075 0.422 0.430 3.503 NaN NaN
forest winter 2018 0.970 0.025 0.418 0.438 3.160 0.564 3.262
baseline winter 2019 0.992 0.125 0.378 0.464 2.006 NaN NaN
forest winter 2019 0.992 0.125 0.333 0.438 1.933 0.517 2.356
baseline all 0.992 0.075 0.404 0.452 3.503 NaN NaN
forest all 0.983 0.053 0.371 0.436 3.255 0.529 3.045

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 0.031 0.499 0.519 3.316 NaN NaN
elr winter 2016 0.994 0.031 2.039 0.540 1.766e+01 0.647 1.554e+01
baseline winter 2017 0.981 0.089 0.290 0.382 2.312 NaN NaN
elr winter 2017 0.972 0.067 0.331 0.434 2.160 0.607 4.139
baseline winter 2018 0.993 0.075 0.422 0.430 3.503 NaN NaN
elr winter 2018 0.970 0.050 0.410 0.459 3.122 0.643 5.136
baseline winter 2019 0.992 0.125 0.378 0.464 2.006 NaN NaN
elr winter 2019 0.992 0.125 0.357 0.454 1.877 0.564 3.591
baseline all 0.992 0.075 0.404 0.452 3.503 NaN NaN
elr all 0.983 0.060 0.849 0.476 1.766e+01 0.619 7.567

Extended logistic regression plots

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