The idea of resolving dispute through the exchange of arguments and reasons has been
central to society for millennia. We exchange arguments as a way of getting at the truth in …

Human forecasting accuracy improves through the “wisdom of the crowd” effect, in which
aggregated predictions tend to outperform individual ones. Past research suggests that …

A probability forecast or probabilistic classifier is reliable or calibrated if the predicted
probabilities are matched by ex post observed frequencies, as examined visually in …

Regression diagnostics meets forecast evaluation: conditional calibration, reliability diagrams,
and coefficient of determinatio Page 1 Electronic Journal of Statistics Vol. 17 (2023) 3226–3286 …

Probability forecasts for binary outcomes, often referred to as probabilistic classifiers or
confidence scores, are ubiquitous in science and society, and methods for evaluating and …

The continuous ranked probability score (crps) is the most commonly used scoring rule in
the evaluation of probabilistic forecasts for real-valued outcomes. To assess and rank …

Improving ensemble forecasts is a complex process which involves proper scores such as
the continuous ranked probability score (CRPS). A homogeneous Gaussian (hoG) model is …

Ensembles of independently trained deep neural networks yield uncertainty estimates that
rival Bayesian networks in performance. They also offer sizable improvements in terms of …

Statistical theory indicates that a flexible model can attain a lower generalization error than
an inflexible model, provided that the setting is appropriate. This is highly relevant for …

Seasonal forecasts of variables like near-surface temperature or precipitation are becoming
increasingly important for a wide range of stakeholders. Due to the many possibilities of …