GMS location: 1410

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.976 0.042 0.346 0.451 2.149 NaN NaN
forest winter 2016 0.976 0.042 0.242 0.372 2.107 0.473 3.556
baseline winter 2017 0.963 0.093 0.561 0.549 2.298 NaN NaN
forest winter 2017 0.972 0.046 0.400 0.453 2.112 0.463 3.191
baseline winter 2018 0.992 0.125 0.349 0.442 1.884 NaN NaN
forest winter 2018 0.992 0.125 0.304 0.406 2.123 0.482 2.889
baseline winter 2019 0.980 0.000e+00 0.386 0.454 2.227 NaN NaN
forest winter 2019 0.994 0.000e+00 0.288 0.400 2.124 0.469 2.885
baseline all 0.978 0.081 0.406 0.471 2.298 NaN NaN
forest all 0.984 0.063 0.304 0.405 2.124 0.472 3.146

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 0.042 0.346 0.451 2.149 NaN NaN
elr winter 2016 0.964 0.042 0.289 0.424 2.069 0.528 3.391
baseline winter 2017 0.963 0.093 0.561 0.549 2.298 NaN NaN
elr winter 2017 0.981 0.116 0.459 0.496 2.311 0.471 3.530
baseline winter 2018 0.992 0.125 0.349 0.442 1.884 NaN NaN
elr winter 2018 0.984 0.125 0.312 0.414 2.310 0.522 3.160
baseline winter 2019 0.980 0.000e+00 0.386 0.454 2.227 NaN NaN
elr winter 2019 1.000 0.000e+00 0.340 0.447 2.043 0.503 3.277
baseline all 0.978 0.081 0.406 0.471 2.298 NaN NaN
elr all 0.982 0.090 0.345 0.444 2.311 0.508 3.339

Extended logistic regression plots

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