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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…
Combining predictive distributions for statistical post-processing of ensemble forecasts
Sándor Baran, Sebastian Lerch
Statistical post-processing techniques are now widely used to correct systematic biases and errors in calibration of ensemble forecasts obtained from multiple runs of numerical wea…
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…
Log-normal distribution based EMOS models for probabilistic wind speed forecasting
Sándor Baran, Sebastian Lerch
Ensembles of forecasts are obtained from multiple runs of numerical weather forecasting models with different initial conditions and typically employed to account for forecast unce…