GMS location: 607

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.994 0.065 0.376 0.450 2.996 NaN NaN
forest winter 2016 0.994 0.097 0.320 0.404 3.163 0.482 3.180
baseline winter 2017 0.967 0.070 0.501 0.503 3.110 NaN NaN
forest winter 2017 0.967 0.046 0.377 0.444 2.180 0.481 3.780
baseline winter 2018 0.971 0.075 0.403 0.454 2.872 NaN NaN
forest winter 2018 0.964 0.050 0.386 0.449 2.525 0.500 2.969
baseline winter 2019 0.992 0.000e+00 0.309 0.411 1.910 NaN NaN
forest winter 2019 1.000 0.000e+00 0.222 0.362 1.343 0.503 2.574
baseline all 0.983 0.061 0.395 0.454 3.110 NaN NaN
forest all 0.983 0.054 0.329 0.415 3.163 0.491 3.117

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 0.065 0.376 0.450 2.996 NaN NaN
elr winter 2016 0.977 0.065 0.336 0.430 2.980 0.579 4.480
baseline winter 2017 0.967 0.070 0.501 0.503 3.110 NaN NaN
elr winter 2017 0.967 0.046 0.396 0.467 2.335 0.555 4.561
baseline winter 2018 0.971 0.075 0.403 0.454 2.872 NaN NaN
elr winter 2018 0.978 0.050 0.361 0.468 2.264 0.583 4.630
baseline winter 2019 0.992 0.000e+00 0.309 0.411 1.910 NaN NaN
elr winter 2019 1.000 0.062 0.235 0.378 1.306 0.547 3.410
baseline all 0.983 0.061 0.395 0.454 3.110 NaN NaN
elr all 0.981 0.054 0.333 0.437 2.980 0.568 4.310

Extended logistic regression plots

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