GMS location: 871

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.978 0.000e+00 0.330 0.429 2.049 NaN NaN
forest winter 2016 0.983 0.040 0.279 0.387 1.819 0.500 4.743
baseline winter 2017 0.991 0.000e+00 0.426 0.444 2.557 NaN NaN
forest winter 2017 0.991 0.000e+00 0.345 0.399 2.261 0.473 4.402
baseline winter 2018 0.979 0.125 0.296 0.397 2.563 NaN NaN
forest winter 2018 0.993 0.094 0.265 0.369 2.422 0.470 2.969
baseline winter 2019 0.963 0.000e+00 0.284 0.392 1.842 NaN NaN
forest winter 2019 0.972 0.000e+00 0.196 0.326 1.597 0.472 3.542
baseline all 0.978 0.036 0.333 0.417 2.563 NaN NaN
forest all 0.985 0.036 0.274 0.373 2.422 0.481 3.956

Random forest plots

My plot :) My plot :) My plot :) My plot :) My plot :) My plot :) My plot :) My plot :) My plot :) My plot :)

Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.978 0.000e+00 0.330 0.429 2.049 NaN NaN
elr winter 2016 0.983 0.000e+00 0.301 0.418 1.947 0.576 6.688
baseline winter 2017 0.991 0.000e+00 0.426 0.444 2.557 NaN NaN
elr winter 2017 0.981 0.000e+00 0.353 0.426 2.103 0.554 6.657
baseline winter 2018 0.979 0.125 0.296 0.397 2.563 NaN NaN
elr winter 2018 0.993 0.094 0.249 0.368 2.236 0.519 3.881
baseline winter 2019 0.963 0.000e+00 0.284 0.392 1.842 NaN NaN
elr winter 2019 0.982 0.000e+00 0.212 0.360 1.592 0.512 3.681
baseline all 0.978 0.036 0.333 0.417 2.563 NaN NaN
elr all 0.985 0.027 0.281 0.395 2.236 0.543 5.343

Extended logistic regression plots

My plot :) My plot :) My plot :) My plot :) My plot :) My plot :) My plot :) My plot :) My plot :) My plot :)