GMS location: 1110

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.994 0.059 0.396 0.464 2.372 NaN NaN
forest winter 2016 0.971 0.029 0.372 0.450 2.586 0.498 2.448
baseline winter 2017 0.953 0.133 0.495 0.501 3.640 NaN NaN
forest winter 2017 0.953 0.067 0.453 0.473 3.363 0.512 3.592
baseline winter 2018 0.977 0.059 0.367 0.438 1.899 NaN NaN
forest winter 2018 0.977 0.029 0.322 0.438 1.629 0.519 2.819
baseline winter 2019 0.993 0.000e+00 0.331 0.407 1.786 NaN NaN
forest winter 2019 0.985 0.000e+00 0.238 0.350 1.622 0.505 2.291
baseline all 0.982 0.076 0.396 0.453 3.640 NaN NaN
forest all 0.972 0.038 0.347 0.429 3.363 0.508 2.759

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.994 0.059 0.396 0.464 2.372 NaN NaN
elr winter 2016 0.971 0.029 0.377 0.466 2.375 0.563 3.992
baseline winter 2017 0.953 0.133 0.495 0.501 3.640 NaN NaN
elr winter 2017 0.953 0.044 0.457 0.481 3.310 0.563 4.300
baseline winter 2018 0.977 0.059 0.367 0.438 1.899 NaN NaN
elr winter 2018 0.954 0.059 0.334 0.459 1.752 0.582 4.013
baseline winter 2019 0.993 0.000e+00 0.331 0.407 1.786 NaN NaN
elr winter 2019 1.000 0.053 0.254 0.365 1.737 0.530 3.065
baseline all 0.982 0.076 0.396 0.453 3.640 NaN NaN
elr all 0.971 0.045 0.357 0.445 3.310 0.560 3.856

Extended logistic regression plots

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