GMS location: 456

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.988 0.000e+00 0.495 0.500 2.601 NaN NaN
forest winter 2016 0.994 0.000e+00 0.479 0.477 2.402 0.456 2.711
baseline winter 2017 0.964 0.023 0.454 0.474 2.287 NaN NaN
forest winter 2017 0.964 0.000e+00 0.398 0.456 1.841 0.493 2.351
baseline winter 2019 1.000 0.059 0.284 0.364 2.164 NaN NaN
forest winter 2019 1.000 0.118 0.240 0.356 1.651 0.459 1.791
baseline all 0.984 0.023 0.428 0.457 2.601 NaN NaN
forest all 0.987 0.023 0.391 0.440 2.402 0.469 2.358

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.988 0.000e+00 0.495 0.500 2.601 NaN NaN
elr winter 2016 1.000 0.038 0.464 0.489 2.430 0.550 3.927
baseline winter 2017 0.964 0.023 0.454 0.474 2.287 NaN NaN
elr winter 2017 0.964 0.000e+00 0.443 0.511 1.870 0.624 4.819
baseline winter 2019 1.000 0.059 0.284 0.364 2.164 NaN NaN
elr winter 2019 1.000 0.118 0.222 0.354 1.403 0.488 2.301
baseline all 0.984 0.023 0.428 0.457 2.601 NaN NaN
elr all 0.989 0.035 0.395 0.462 2.430 0.559 3.811

Extended logistic regression plots

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