GMS location: 206

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.988 0.156 0.589 0.579 2.385 NaN NaN
forest winter 2016 0.988 0.156 0.460 0.502 2.141 0.474 4.194
baseline winter 2017 0.964 0.071 0.532 0.533 2.367 NaN NaN
forest winter 2017 0.973 0.071 0.349 0.441 1.791 0.469 3.372
baseline winter 2018 0.993 0.100 0.351 0.440 2.003 NaN NaN
forest winter 2018 0.993 0.100 0.293 0.416 1.701 0.463 2.437
baseline winter 2019 0.979 0.160 0.374 0.465 1.837 NaN NaN
forest winter 2019 0.990 0.200 0.282 0.399 1.579 0.467 2.817
baseline all 0.983 0.115 0.471 0.509 2.385 NaN NaN
forest all 0.987 0.122 0.356 0.445 2.141 0.469 3.269

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 0.156 0.589 0.579 2.385 NaN NaN
elr winter 2016 0.983 0.125 0.555 0.568 2.231 0.568 4.345
baseline winter 2017 0.964 0.071 0.532 0.533 2.367 NaN NaN
elr winter 2017 0.964 0.071 0.394 0.455 2.181 0.502 2.566
baseline winter 2018 0.993 0.100 0.351 0.440 2.003 NaN NaN
elr winter 2018 0.993 0.075 0.300 0.421 1.748 0.549 2.460
baseline winter 2019 0.979 0.160 0.374 0.465 1.837 NaN NaN
elr winter 2019 1.000 0.200 0.309 0.403 1.692 0.517 2.369
baseline all 0.983 0.115 0.471 0.509 2.385 NaN NaN
elr all 0.985 0.108 0.402 0.471 2.231 0.538 3.051

Extended logistic regression plots

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