264 citations · 904 across the 34 of their papers we have counts for
8 papers · 1 filter
Shape from Texture using Locally Scaled Point Processes
Eva-Maria Didden, Thordis Linda Thorarinsdottir, Alex Lenkoski +1
Shape from texture refers to the extraction of 3D information from 2D images with irregular texture. This paper introduces a statistical framework to learn shape from texture where…
Assessing the calibration of high-dimensional ensemble forecasts using rank histograms
Thordis L. Thorarinsdottir, Michael Scheuerer, Christopher Heinz
Any decision making process that relies on a probabilistic forecast of future events necessarily requires a calibrated forecast. This paper proposes new methods for empirically ass…
Bayesian hierarchical modeling of extreme hourly precipitation in Norway
Anita V. Dyrrdal, Alex Lenkoski, Thordis L. Thorarinsdottir +1
Spatial maps of extreme precipitation are a critical component of flood estimation in hydrological modeling, as well as in the planning and design of important infrastructure. This…
Bayesian Motion Estimation for Dust Aerosols
Fabian E. Bachl, Alex Lenkoski, Thordis L. Thorarinsdottir +1
Dust storms in the earth's major desert regions significantly influence microphysical weather processes, the CO-cycle and the global climate in general. Recent increases in the…
Calibration diagnostics for point process models via the probability integral transform
Thordis L. Thorarinsdottir
We propose the use of the probability integral transform (PIT) for model validation in point process models. The simple PIT diagnostics assess the calibration of the model and can…
Comparison of nonhomogeneous regression models for probabilistic wind speed forecasting
Sebastian Lerch, Thordis L. Thorarinsdottir
In weather forecasting, nonhomogeneous regression is used to statistically postprocess forecast ensembles in order to obtain calibrated predictive distributions. For wind speed for…
Uncertainty Quantification in Complex Simulation Models Using Ensemble Copula Coupling
Roman Schefzik, Thordis L. Thorarinsdottir, Tilmann Gneiting
Critical decisions frequently rely on high-dimensional output from complex computer simulation models that show intricate cross-variable, spatial and temporal dependence structures…
Using proper divergence functions to evaluate climate models
Thordis L. Thorarinsdottir, Tilmann Gneiting, Nadine Gissibl
It has been argued persuasively that, in order to evaluate climate models, the probability distributions of model output need to be compared to the corresponding empirical distribu…