GMS location: 214

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.977 0.053 0.276 0.385 1.734 NaN NaN
forest winter 2016 0.966 0.053 0.233 0.353 1.669 0.525 7.150
baseline winter 2017 0.946 0.024 0.409 0.474 1.951 NaN NaN
forest winter 2017 0.946 0.049 0.350 0.433 1.717 0.533 6.426
baseline winter 2018 0.984 0.175 0.312 0.424 1.486 NaN NaN
forest winter 2018 0.984 0.125 0.279 0.402 1.605 0.530 4.540
baseline winter 2019 1.000 0.067 0.276 0.399 1.610 NaN NaN
forest winter 2019 1.000 0.133 0.230 0.351 1.393 0.525 5.544
baseline all 0.978 0.087 0.316 0.418 1.951 NaN NaN
forest all 0.974 0.087 0.271 0.383 1.717 0.528 5.973

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.977 0.053 0.276 0.385 1.734 NaN NaN
elr winter 2016 0.971 0.053 0.255 0.387 1.508 0.613 7.753
baseline winter 2017 0.946 0.024 0.409 0.474 1.951 NaN NaN
elr winter 2017 0.938 0.049 0.355 0.459 1.744 0.633 8.630
baseline winter 2018 0.984 0.175 0.312 0.424 1.486 NaN NaN
elr winter 2018 0.976 0.075 0.295 0.426 1.616 0.605 7.271
baseline winter 2019 1.000 0.067 0.276 0.399 1.610 NaN NaN
elr winter 2019 1.000 0.133 0.223 0.367 1.158 0.599 6.449
baseline all 0.978 0.087 0.316 0.418 1.951 NaN NaN
elr all 0.972 0.070 0.281 0.409 1.744 0.613 7.543

Extended logistic regression plots

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