GMS location: 424

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.994 0.035 0.275 0.396 1.740 NaN NaN
forest winter 2016 0.989 0.035 0.243 0.367 1.707 0.465 3.686
baseline winter 2017 0.982 0.049 0.434 0.477 2.433 NaN NaN
forest winter 2017 1.000 0.049 0.317 0.412 2.324 0.449 3.838
baseline winter 2018 0.970 0.061 0.409 0.457 2.604 NaN NaN
forest winter 2018 0.977 0.091 0.300 0.400 1.957 0.458 3.521
baseline winter 2019 0.962 0.105 0.434 0.471 3.371 NaN NaN
forest winter 2019 0.993 0.158 0.310 0.387 3.428 0.450 3.662
baseline all 0.978 0.057 0.379 0.446 3.371 NaN NaN
forest all 0.989 0.074 0.289 0.390 3.428 0.456 3.675

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.994 0.035 0.275 0.396 1.740 NaN NaN
elr winter 2016 0.972 0.035 0.254 0.390 1.802 0.519 3.395
baseline winter 2017 0.982 0.049 0.434 0.477 2.433 NaN NaN
elr winter 2017 0.982 0.049 0.362 0.440 2.417 0.479 3.555
baseline winter 2018 0.970 0.061 0.409 0.457 2.604 NaN NaN
elr winter 2018 0.977 0.091 0.341 0.433 2.232 0.522 4.241
baseline winter 2019 0.962 0.105 0.434 0.471 3.371 NaN NaN
elr winter 2019 0.985 0.053 0.367 0.441 3.498 0.483 3.286
baseline all 0.978 0.057 0.379 0.446 3.371 NaN NaN
elr all 0.978 0.057 0.325 0.423 3.498 0.503 3.613

Extended logistic regression plots

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