4 papers · 1 filter
Residual Distribution Predictive Systems
Sam Allen, Enrico Pescara, Johanna Ziegel
Conformal predictive systems are sets of predictive distributions with theoretical out-of-sample calibration guarantees. The calibration guarantees are typically that the set of pr…
Assessing the conditional calibration of interval forecasts using decompositions of the interval score
Sam Allen, Julia Burnello, Johanna Ziegel
Forecasts for uncertain future events should be probabilistic. Probabilistic forecasts are commonly issued as prediction intervals, which provide a measure of uncertainty in the un…
Enforcing tail calibration when training probabilistic forecast models
Jakob Benjamin Wessel, Maybritt Schillinger, Frank Kwasniok +1
Probabilistic forecasts are typically obtained using state-of-the-art statistical and machine learning models, with model parameters estimated by optimizing a proper scoring rule o…
In-sample calibration yields conformal calibration guarantees
Sam Allen, Georgios Gavrilopoulos, Alexander Henzi +2
Conformal prediction produces a set of predictions that has out-of-sample calibration guarantees by construction, under the assumption of exchangeability. In this work, we study th…