GMS location: 1420

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.983 0.000e+00 0.291 0.400 2.098 NaN NaN
forest winter 2016 0.978 0.053 0.238 0.353 2.002 0.461 3.782
baseline winter 2017 0.991 0.077 0.374 0.416 2.613 NaN NaN
forest winter 2017 0.991 0.103 0.281 0.361 2.537 0.448 3.162
baseline winter 2018 0.985 0.114 0.409 0.448 2.180 NaN NaN
forest winter 2018 1.000 0.143 0.292 0.371 2.227 0.444 3.472
baseline winter 2019 1.000 0.077 0.337 0.416 2.011 NaN NaN
forest winter 2019 1.000 0.077 0.246 0.372 1.601 0.445 3.224
baseline all 0.991 0.075 0.343 0.416 2.613 NaN NaN
forest all 0.991 0.104 0.259 0.363 2.537 0.451 3.425

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.983 0.000e+00 0.291 0.400 2.098 NaN NaN
elr winter 2016 0.978 0.000e+00 0.267 0.379 2.028 0.524 4.862
baseline winter 2017 0.991 0.077 0.374 0.416 2.613 NaN NaN
elr winter 2017 0.991 0.128 0.317 0.382 2.439 0.503 4.708
baseline winter 2018 0.985 0.114 0.409 0.448 2.180 NaN NaN
elr winter 2018 1.000 0.171 0.289 0.380 2.019 0.492 4.344
baseline winter 2019 1.000 0.077 0.337 0.416 2.011 NaN NaN
elr winter 2019 1.000 0.077 0.298 0.421 1.715 0.502 5.002
baseline all 0.991 0.075 0.343 0.416 2.613 NaN NaN
elr all 0.991 0.113 0.291 0.392 2.439 0.508 4.780

Extended logistic regression plots

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