GMS location: 1411

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 1.000 0.088 0.371 0.459 2.481 NaN NaN
forest winter 2016 1.000 0.059 0.316 0.414 2.389 0.495 4.792
baseline winter 2017 0.983 0.053 0.485 0.498 3.291 NaN NaN
forest winter 2017 0.983 0.026 0.417 0.451 2.705 0.493 4.314
baseline winter 2018 0.979 0.032 0.326 0.436 1.851 NaN NaN
forest winter 2018 0.979 0.032 0.284 0.415 1.724 0.493 3.405
baseline winter 2019 0.977 0.176 0.234 0.371 1.356 NaN NaN
forest winter 2019 0.992 0.176 0.188 0.333 1.216 0.490 3.263
baseline all 0.986 0.075 0.356 0.443 3.291 NaN NaN
forest all 0.989 0.058 0.303 0.405 2.705 0.493 4.003

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 0.088 0.371 0.459 2.481 NaN NaN
elr winter 2016 0.994 0.029 0.344 0.444 2.419 0.556 4.977
baseline winter 2017 0.983 0.053 0.485 0.498 3.291 NaN NaN
elr winter 2017 0.983 0.053 0.433 0.474 2.915 0.532 5.359
baseline winter 2018 0.979 0.032 0.326 0.436 1.851 NaN NaN
elr winter 2018 0.986 0.032 0.318 0.449 1.903 0.581 5.198
baseline winter 2019 0.977 0.176 0.234 0.371 1.356 NaN NaN
elr winter 2019 0.992 0.235 0.208 0.366 1.293 0.532 3.476
baseline all 0.986 0.075 0.356 0.443 3.291 NaN NaN
elr all 0.989 0.067 0.328 0.435 2.915 0.552 4.796

Extended logistic regression plots

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