GMS location: 604

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.995 0.045 0.325 0.432 1.708 NaN NaN
forest winter 2016 1.000 0.045 0.235 0.364 1.551 0.469 3.936
baseline winter 2017 0.950 0.000e+00 0.545 0.526 3.201 NaN NaN
forest winter 2017 0.959 0.000e+00 0.393 0.437 2.269 0.472 4.499
baseline winter 2018 0.987 0.032 0.362 0.446 2.368 NaN NaN
forest winter 2018 0.993 0.065 0.282 0.404 1.841 0.476 3.440
baseline winter 2019 0.993 0.000e+00 0.259 0.372 2.016 NaN NaN
forest winter 2019 1.000 0.000e+00 0.230 0.358 1.524 0.463 3.659
baseline all 0.984 0.021 0.367 0.442 3.201 NaN NaN
forest all 0.990 0.031 0.280 0.389 2.269 0.470 3.867

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.995 0.045 0.325 0.432 1.708 NaN NaN
elr winter 2016 0.995 0.045 0.307 0.426 1.706 0.543 3.790
baseline winter 2017 0.950 0.000e+00 0.545 0.526 3.201 NaN NaN
elr winter 2017 0.959 0.062 0.441 0.478 2.560 0.476 3.402
baseline winter 2018 0.987 0.032 0.362 0.446 2.368 NaN NaN
elr winter 2018 0.980 0.097 0.328 0.449 2.156 0.530 3.380
baseline winter 2019 0.993 0.000e+00 0.259 0.372 2.016 NaN NaN
elr winter 2019 0.993 0.000e+00 0.319 0.443 1.713 0.496 2.930
baseline all 0.984 0.021 0.367 0.442 3.201 NaN NaN
elr all 0.984 0.062 0.344 0.447 2.560 0.514 3.402

Extended logistic regression plots

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