264 citations · 904 across the 34 of their papers we have counts for
11 papers · 1 filter
Dynamic factor and double PCA models for partially observed survival curves: Forecasting demand in short-term rental markets
Marthe Elisabeth Aastveit, Alex Lenkoski, Thordis Thorarinsdottir
This paper develops prediction models for population-level survival curves observed over time and sampled from a heterogeneous mix of populations. We consider a discrete-time setti…
What you see is not what is there: Mechanisms, models, and methods for point pattern deviations
Peter Guttorp, Janine Illian, Joel Kostensalo +4
Many natural systems are observed as point patterns in time, space, or space and time. Examples include plant and cellular systems, animal colonies, earthquakes, and wildfires. In…
Validation of point process predictions with proper scoring rules
Claudio Heinrich-Mertsching, Thordis L. Thorarinsdottir, Peter Guttorp +1
We introduce a class of proper scoring rules for evaluating spatial point process forecasts based on summary statistics. These scoring rules rely on Monte-Carlo approximations of e…
Multivariate postprocessing methods for high-dimensional seasonal weather forecasts
Claudio Heinrich, Kristoffer H. Hellton, Alex Lenkoski +1
Seasonal weather forecasts are crucial for long-term planning in many practical situations and skillful forecasts may have substantial economic and humanitarian implications. Curre…
Evaluation of time series models under non-stationarity with application to the comparison of regional climate models
T. M. Erhardt, C. Czado, T. L. Thorarinsdottir
Different disciplines pursue the aim to develop models which characterize certain phenomena as accurately as possible. Climatology is a prime example, where the temporal evolution…
Predictive Inference Based on Markov Chain Monte Carlo Output
Fabian Krüger, Sebastian Lerch, Thordis L. Thorarinsdottir +1
In Bayesian inference, predictive distributions are typically in the form of samples generated via Markov chain Monte Carlo (MCMC) or related algorithms. In this paper, we conduct…
Forecaster's Dilemma: Extreme Events and Forecast Evaluation
Sebastian Lerch, Thordis L. Thorarinsdottir, Francesco Ravazzolo +1
In public discussions of the quality of forecasts, attention typically focuses on the predictive performance in cases of extreme events. However, the restriction of conventional fo…
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…
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…
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…