462 citations · 706 across the 37 of their papers we have counts for
13 papers · 1 filter
Spatial Aggregation of ROC and Precision-Recall Curves
Romain Pic, Zhongwei Zhang, Sebastian Engelke +1
Receiver Operating Characteristic (ROC) and Precision-Recall (PR) curves are widely used to assess the discrimination ability of forecasts for binary events, such as threshold exce…
Decompositions of the mean continuous ranked probability score
Sebastian Arnold, Eva-Maria Walz, Johanna Ziegel +1
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 fore…
Assessing the calibration of multivariate probabilistic forecasts
Sam Allen, Johanna Ziegel, David Ginsbourger
Rank and PIT histograms are established tools to assess the calibration of probabilistic forecasts. They not only check whether an ensemble forecast is calibrated, but they also re…
Isotonic Recalibration under a Low Signal-to-Noise Ratio
Mario V. Wüthrich, Johanna Ziegel
Insurance pricing systems should fulfill the auto-calibration property to ensure that there is no systematic cross-financing between different price cohorts. Often, regression mode…
Easy Uncertainty Quantification (EasyUQ): Generating Predictive Distributions from Single-valued Model Output
Eva-Maria Walz, Alexander Henzi, Johanna Ziegel +1
How can we quantify uncertainty if our favorite computational tool - be it a numerical, a statistical, or a machine learning approach, or just any computer model - provides single-…
A safe Hosmer-Lemeshow test
Alexander Henzi, Marius Puke, Timo Dimitriadis +1
This article proposes an alternative to the Hosmer-Lemeshow (HL) test for evaluating the calibration of probability forecasts for binary events. The approach is based on e-values,…
Sequentially valid tests for forecast calibration
Sebastian Arnold, Alexander Henzi, Johanna F. Ziegel
Forecasting and forecast evaluation are inherently sequential tasks. Predictions are often issued on a regular basis, such as every hour, day, or month, and their quality is monito…
Valid sequential inference on probability forecast performance
Alexander Henzi, Johanna F. Ziegel
Probability forecasts for binary events play a central role in many applications. Their quality is commonly assessed with proper scoring rules, which assign forecasts a numerical s…
Distributional (Single) Index Models
Alexander Henzi, Gian-Reto Kleger, Johanna F. Ziegel
A Distributional (Single) Index Model (DIM) is a semi-parametric model for distributional regression, that is, estimation of conditional distributions given covariates. The method…
Isotonic Distributional Regression
Alexander Henzi, Johanna F. Ziegel, Tilmann Gneiting
Isotonic distributional regression (IDR) is a powerful nonparametric technique for the estimation of conditional distributions under order restrictions. In a nutshell, IDR learns c…
Generic Conditions for Forecast Dominance
Fabian Krüger, Johanna F. Ziegel
Recent studies have analyzed whether one forecast method dominates another under a class of consistent scoring functions. While the existing literature focuses on empirical tests o…
Cross-calibration of probabilistic forecasts
Christof Strähl, Johanna F. Ziegel
When providing probabilistic forecasts for uncertain future events, it is common to strive for calibrated forecasts, that is, the predictive distribution should be compatible with…
Copula Calibration
Johanna F. Ziegel, Tilmann Gneiting
We propose notions of calibration for probabilistic forecasts of general multivariate quantities. Probabilistic copula calibration is a natural analogue of probabilistic calibratio…