GMS location: 831

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.960 0.278 0.361 0.446 2.421 NaN NaN
forest winter 2016 0.994 0.111 0.285 0.385 2.367 0.451 3.945
baseline winter 2017 0.958 0.121 0.398 0.451 2.902 NaN NaN
forest winter 2017 0.992 0.061 0.299 0.379 2.223 0.446 3.415
baseline winter 2018 0.987 0.148 0.321 0.394 2.199 NaN NaN
forest winter 2018 0.974 0.111 0.301 0.381 2.462 0.439 3.088
baseline winter 2019 0.981 0.067 0.264 0.371 2.071 NaN NaN
forest winter 2019 0.994 0.067 0.183 0.318 1.363 0.446 2.761
baseline all 0.972 0.150 0.335 0.415 2.902 NaN NaN
forest all 0.988 0.086 0.267 0.366 2.462 0.446 3.317

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.960 0.278 0.361 0.446 2.421 NaN NaN
elr winter 2016 0.977 0.056 0.295 0.401 2.220 0.529 5.077
baseline winter 2017 0.958 0.121 0.398 0.451 2.902 NaN NaN
elr winter 2017 0.975 0.091 0.284 0.381 2.211 0.499 4.460
baseline winter 2018 0.987 0.148 0.321 0.394 2.199 NaN NaN
elr winter 2018 0.980 0.111 0.320 0.404 2.304 0.525 6.285
baseline winter 2019 0.981 0.067 0.264 0.371 2.071 NaN NaN
elr winter 2019 0.994 0.067 0.172 0.320 1.239 0.480 3.348
baseline all 0.972 0.150 0.335 0.415 2.902 NaN NaN
elr all 0.982 0.086 0.269 0.377 2.304 0.510 4.830

Extended logistic regression plots

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