GMS location: 1159

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 1.000 0.030 0.329 0.415 2.633 NaN NaN
forest winter 2016 0.994 0.030 0.279 0.385 2.273 0.535 4.244
baseline winter 2017 0.975 0.000e+00 0.423 0.458 2.114 NaN NaN
forest winter 2017 0.966 0.029 0.333 0.415 2.056 0.526 4.429
baseline winter 2018 0.985 0.135 0.322 0.411 1.849 NaN NaN
forest winter 2018 0.985 0.162 0.268 0.397 1.802 0.519 3.635
baseline winter 2019 0.993 0.000e+00 0.369 0.418 2.403 NaN NaN
forest winter 2019 0.993 0.000e+00 0.271 0.371 2.330 0.534 4.648
baseline all 0.990 0.051 0.357 0.424 2.633 NaN NaN
forest all 0.986 0.068 0.286 0.392 2.330 0.529 4.225

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 0.030 0.329 0.415 2.633 NaN NaN
elr winter 2016 0.994 0.030 0.297 0.426 2.310 0.626 5.267
baseline winter 2017 0.975 0.000e+00 0.423 0.458 2.114 NaN NaN
elr winter 2017 0.941 0.029 0.361 0.442 2.032 0.581 4.634
baseline winter 2018 0.985 0.135 0.322 0.411 1.849 NaN NaN
elr winter 2018 0.978 0.108 0.290 0.428 1.598 0.589 4.287
baseline winter 2019 0.993 0.000e+00 0.369 0.418 2.403 NaN NaN
elr winter 2019 0.993 0.000e+00 0.280 0.391 2.367 0.559 4.504
baseline all 0.990 0.051 0.357 0.424 2.633 NaN NaN
elr all 0.979 0.051 0.306 0.422 2.367 0.591 4.707

Extended logistic regression plots

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