GMS location: 1415

Random forest results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.987 0.121 0.724 0.585 4.577 NaN NaN
forest winter 2016 0.974 0.030 0.619 0.545 3.578 0.486 1.439
baseline winter 2017 0.971 0.085 1.012 0.677 4.200 NaN NaN
forest winter 2017 0.981 0.085 0.852 0.619 5.679 0.516 1.599
baseline winter 2018 0.967 0.026 1.230 0.682 4.876 NaN NaN
forest winter 2018 0.950 0.053 0.909 0.649 4.118 0.542 1.662
baseline winter 2019 0.984 0.136 0.492 0.491 2.483 NaN NaN
forest winter 2019 0.984 0.091 0.408 0.470 2.675 0.480 1.400
baseline all 0.978 0.086 0.862 0.609 4.876 NaN NaN
forest all 0.972 0.064 0.696 0.571 5.679 0.506 1.522

Random forest plots

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Extended logistic regression results

names period power significance meanSquareError absError maxError CRPS IGN
baseline winter 2016 0.987 0.121 0.724 0.585 4.577 NaN NaN
elr winter 2016 0.981 0.091 0.576 0.562 3.539 0.530 1.460
baseline winter 2017 0.971 0.085 1.012 0.677 4.200 NaN NaN
elr winter 2017 0.971 0.128 0.968 0.666 4.552 0.439 1.163
baseline winter 2018 0.967 0.026 1.230 0.682 4.876 NaN NaN
elr winter 2018 0.958 0.079 0.939 0.693 3.747 0.519 1.568
baseline winter 2019 0.984 0.136 0.492 0.491 2.483 NaN NaN
elr winter 2019 0.984 0.182 0.536 0.561 2.249 0.560 1.524
baseline all 0.978 0.086 0.862 0.609 4.876 NaN NaN
elr all 0.974 0.114 0.748 0.618 4.552 0.513 1.431

Extended logistic regression plots

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