GMS location: 520

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.978 0.048 0.359 0.422 2.868 NaN NaN
forest winter 2016 0.978 0.048 0.282 0.373 2.441 0.517 2.961
baseline winter 2017 0.966 0.062 0.433 0.460 2.234 NaN NaN
forest winter 2017 0.975 0.062 0.361 0.429 2.041 0.502 4.008
baseline winter 2018 0.990 0.091 0.439 0.482 3.187 NaN NaN
forest winter 2018 0.990 0.091 0.405 0.465 2.925 0.498 2.964
baseline winter 2019 1.000 0.100 0.234 0.357 2.133 NaN NaN
forest winter 2019 1.000 0.100 0.199 0.322 1.844 0.528 2.819
baseline all 0.983 0.073 0.367 0.430 3.187 NaN NaN
forest all 0.985 0.073 0.309 0.395 2.925 0.512 3.185

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.978 0.048 0.359 0.422 2.868 NaN NaN
elr winter 2016 0.978 0.048 0.318 0.412 2.353 0.589 4.129
baseline winter 2017 0.966 0.062 0.433 0.460 2.234 NaN NaN
elr winter 2017 0.975 0.062 0.411 0.462 2.223 0.552 4.777
baseline winter 2018 0.990 0.091 0.439 0.482 3.187 NaN NaN
elr winter 2018 0.990 0.061 0.389 0.448 3.068 0.568 5.098
baseline winter 2019 1.000 0.100 0.234 0.357 2.133 NaN NaN
elr winter 2019 1.000 0.100 0.233 0.368 1.790 0.555 3.521
baseline all 0.983 0.073 0.367 0.430 3.187 NaN NaN
elr all 0.985 0.062 0.337 0.422 3.068 0.568 4.362

Extended logistic regression plots

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