GMS location: 207

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.989 0.056 0.290 0.411 1.500 NaN NaN
forest winter 2016 1.000 0.111 0.242 0.376 1.417 0.469 6.080
baseline winter 2017 0.965 0.029 0.387 0.463 2.096 NaN NaN
forest winter 2017 0.974 0.029 0.285 0.405 1.557 0.478 6.041
baseline winter 2018 0.992 0.120 0.297 0.417 1.629 NaN NaN
forest winter 2018 1.000 0.120 0.239 0.375 1.489 0.490 3.870
baseline winter 2019 0.993 0.000e+00 0.264 0.376 1.821 NaN NaN
forest winter 2019 0.993 0.071 0.189 0.314 1.422 0.486 3.927
baseline all 0.986 0.054 0.307 0.415 2.096 NaN NaN
forest all 0.993 0.076 0.238 0.367 1.557 0.480 5.050

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.989 0.056 0.290 0.411 1.500 NaN NaN
elr winter 2016 0.989 0.111 0.256 0.396 1.371 0.550 6.458
baseline winter 2017 0.965 0.029 0.387 0.463 2.096 NaN NaN
elr winter 2017 0.974 0.029 0.301 0.416 1.850 0.520 5.573
baseline winter 2018 0.992 0.120 0.297 0.417 1.629 NaN NaN
elr winter 2018 1.000 0.080 0.249 0.395 1.629 0.545 6.058
baseline winter 2019 0.993 0.000e+00 0.264 0.376 1.821 NaN NaN
elr winter 2019 0.993 0.000e+00 0.203 0.330 1.479 0.520 4.456
baseline all 0.986 0.054 0.307 0.415 2.096 NaN NaN
elr all 0.990 0.054 0.252 0.384 1.850 0.535 5.678

Extended logistic regression plots

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