GMS location: 812

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.976 0.048 0.404 0.461 2.722 NaN NaN
forest winter 2016 0.976 0.095 0.336 0.411 2.155 0.489 1.703
baseline winter 2017 0.991 0.054 0.435 0.442 2.468 NaN NaN
forest winter 2017 0.982 0.054 0.332 0.413 2.015 0.481 1.842
baseline winter 2018 0.986 0.103 1.108 0.644 5.513 NaN NaN
forest winter 2018 0.986 0.069 1.005 0.594 5.153 0.487 2.811
baseline winter 2019 0.978 0.105 0.271 0.382 2.236 NaN NaN
forest winter 2019 0.985 0.053 0.344 0.416 2.327 0.521 1.746
baseline all 0.982 0.075 0.561 0.485 5.513 NaN NaN
forest all 0.982 0.066 0.509 0.460 5.153 0.494 2.030

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 0.048 0.404 0.461 2.722 NaN NaN
elr winter 2016 0.958 0.095 0.355 0.454 2.173 0.560 1.996
baseline winter 2017 0.991 0.054 0.435 0.442 2.468 NaN NaN
elr winter 2017 0.982 0.135 0.345 0.435 1.988 0.529 1.880
baseline winter 2018 0.986 0.103 1.108 0.644 5.513 NaN NaN
elr winter 2018 0.986 0.069 1.091 0.613 5.378 0.533 3.826
baseline winter 2019 0.978 0.105 0.271 0.382 2.236 NaN NaN
elr winter 2019 0.978 0.053 0.234 0.384 1.128 0.508 1.651
baseline all 0.982 0.075 0.561 0.485 5.513 NaN NaN
elr all 0.975 0.094 0.514 0.474 5.378 0.534 2.361

Extended logistic regression plots

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