GMS location: 1419

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.976 0.043 0.279 0.396 2.448 NaN NaN
forest winter 2016 0.976 0.043 0.229 0.348 2.156 0.454 2.202
baseline winter 2017 0.982 0.048 0.460 0.475 2.731 NaN NaN
forest winter 2017 0.991 0.048 0.352 0.433 2.021 0.455 2.577
baseline winter 2018 0.978 0.111 0.374 0.417 2.995 NaN NaN
forest winter 2018 0.985 0.111 0.345 0.391 3.035 0.469 2.992
baseline winter 2019 0.991 0.000e+00 0.394 0.445 2.187 NaN NaN
forest winter 2019 0.991 0.154 0.328 0.428 1.515 0.468 2.693
baseline all 0.981 0.061 0.370 0.430 2.995 NaN NaN
forest all 0.985 0.079 0.309 0.395 3.035 0.461 2.598

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.976 0.043 0.279 0.396 2.448 NaN NaN
elr winter 2016 0.976 0.043 0.253 0.391 2.021 0.551 3.425
baseline winter 2017 0.982 0.048 0.460 0.475 2.731 NaN NaN
elr winter 2017 0.955 0.048 0.453 0.481 2.449 0.531 3.820
baseline winter 2018 0.978 0.111 0.374 0.417 2.995 NaN NaN
elr winter 2018 0.993 0.083 0.350 0.399 2.971 0.535 3.903
baseline winter 2019 0.991 0.000e+00 0.394 0.445 2.187 NaN NaN
elr winter 2019 0.991 0.154 0.349 0.449 1.634 0.547 4.345
baseline all 0.981 0.061 0.370 0.430 2.995 NaN NaN
elr all 0.979 0.070 0.345 0.426 2.971 0.541 3.825

Extended logistic regression plots

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