GMS location: 1104

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.988 0.151 0.334 0.427 2.018 NaN NaN
forest winter 2016 0.988 0.151 0.280 0.375 1.966 0.436 3.116
baseline winter 2017 0.966 0.083 0.548 0.518 2.652 NaN NaN
forest winter 2017 0.974 0.028 0.368 0.433 2.440 0.456 4.087
baseline winter 2018 0.979 0.062 0.357 0.435 2.368 NaN NaN
forest winter 2018 0.986 0.062 0.307 0.404 2.188 0.449 3.868
baseline winter 2019 0.993 0.000e+00 0.272 0.372 1.812 NaN NaN
forest winter 2019 0.993 0.000e+00 0.232 0.365 1.432 0.427 3.078
baseline all 0.982 0.090 0.375 0.438 2.652 NaN NaN
forest all 0.986 0.072 0.297 0.393 2.440 0.442 3.522

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 0.151 0.334 0.427 2.018 NaN NaN
elr winter 2016 0.994 0.061 0.317 0.417 2.087 0.509 3.324
baseline winter 2017 0.966 0.083 0.548 0.518 2.652 NaN NaN
elr winter 2017 0.966 0.056 0.440 0.480 2.439 0.482 3.725
baseline winter 2018 0.979 0.062 0.357 0.435 2.368 NaN NaN
elr winter 2018 0.979 0.062 0.346 0.431 2.526 0.498 3.204
baseline winter 2019 0.993 0.000e+00 0.272 0.372 1.812 NaN NaN
elr winter 2019 0.993 0.000e+00 0.281 0.413 1.501 0.502 3.217
baseline all 0.982 0.090 0.375 0.438 2.652 NaN NaN
elr all 0.984 0.054 0.345 0.434 2.526 0.498 3.360

Extended logistic regression plots

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