85 citations · 137 across the 8 of their papers we have counts for
9 papers
On the Calibration of Isotonic Distributional Regression
Tobias Biegert, Johannes Resin, Alexander Jordan +1
Isotonic distributional regression (IDR) has recently been proposed as a non-parametric technique for probabilistic forecasting via the estimation of conditional distributions unde…
Probabilistic measures afford fair comparisons of AIWP and NWP model output
Tilmann Gneiting, Tobias Biegert, Kristof Kraus +3
We introduce a new measure for fair and meaningful comparisons of single-valued output from artificial intelligence based weather prediction (AIWP) and numerical weather prediction…
Evaluating Probabilistic Classifiers: The Triptych
Timo Dimitriadis, Tilmann Gneiting, Alexander I. Jordan +1
Probability forecasts for binary outcomes, often referred to as probabilistic classifiers or confidence scores, are ubiquitous in science and society, and methods for evaluating an…
Evaluating probabilistic classifiers: Reliability diagrams and score decompositions revisited
Timo Dimitriadis, Tilmann Gneiting, Alexander I. Jordan
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 rel…
Optimal solutions to the isotonic regression problem
Alexander I. Jordan, Anja Mühlemann, Johanna F. Ziegel
In general, the solution to a regression problem is the minimizer of a given loss criterion, and depends on the specified loss function. The nonparametric isotonic regression probl…
Evaluating probabilistic forecasts with scoringRules
Alexander Jordan, Fabian Krüger, Sebastian Lerch
Probabilistic forecasts in the form of probability distributions over future events have become popular in several fields including meteorology, hydrology, economics, and demograph…
Murphy Diagrams: Forecast Evaluation of Expected Shortfall
Johanna F. Ziegel, Fabian Krüger, Alexander Jordan +1
Motivated by the Basel 3 regulations, recent studies have considered joint forecasts of Value-at-Risk and Expected Shortfall. A large family of scoring functions can be used to eva…
Of Quantiles and Expectiles: Consistent Scoring Functions, Choquet Representations, and Forecast Rankings
Werner Ehm, Tilmann Gneiting, Alexander Jordan +1
In the practice of point prediction, it is desirable that forecasters receive a directive in the form of a statistical functional, such as the mean or a quantile of the predictive…
Tobit Bayesian Model Averaging and the Determinants of Foreign Direct Investment
Alexander Jordan, Alex Lenkoski
We develop a fully Bayesian, computationally efficient framework for incorporating model uncertainty into Type II Tobit models and apply this to the investigation of the determinan…