GMS location: 1438

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 1.000 0.083 0.351 0.429 2.900 NaN NaN
forest winter 2016 0.979 0.056 0.285 0.366 2.628 0.466 4.956
baseline winter 2017 0.971 0.087 0.387 0.446 2.489 NaN NaN
forest winter 2017 0.981 0.087 0.343 0.436 1.898 0.460 4.816
baseline winter 2018 0.986 0.081 0.351 0.430 1.953 NaN NaN
forest winter 2018 0.993 0.081 0.277 0.384 1.737 0.454 3.077
baseline winter 2019 0.985 0.091 0.276 0.391 1.623 NaN NaN
forest winter 2019 0.985 0.045 0.193 0.331 1.503 0.448 3.713
baseline all 0.987 0.085 0.342 0.425 2.900 NaN NaN
forest all 0.985 0.071 0.275 0.379 2.628 0.457 4.132

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 0.083 0.351 0.429 2.900 NaN NaN
elr winter 2016 0.979 0.083 0.295 0.404 2.699 0.505 3.589
baseline winter 2017 0.971 0.087 0.387 0.446 2.489 NaN NaN
elr winter 2017 0.971 0.065 0.346 0.436 2.118 0.507 4.512
baseline winter 2018 0.986 0.081 0.351 0.430 1.953 NaN NaN
elr winter 2018 0.979 0.081 0.323 0.412 1.838 0.499 3.652
baseline winter 2019 0.985 0.091 0.276 0.391 1.623 NaN NaN
elr winter 2019 0.985 0.091 0.220 0.369 1.544 0.492 2.981
baseline all 0.987 0.085 0.342 0.425 2.900 NaN NaN
elr all 0.979 0.078 0.297 0.406 2.699 0.501 3.677

Extended logistic regression plots

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