Statistical postprocessing techniques are nowadays key components of the forecasting
suites in many national meteorological services (NMS), with, for most of them, the objective …

Computer simulation models have been widely used to generate hydrometeorological
forecasts. As the raw forecasts contain uncertainties arising from various sources, including …

Ensemble weather predictions require statistical postprocessing of systematic errors to
obtain reliable and accurate probabilistic forecasts. Traditionally, this is accomplished with …

Clustered covariances or clustered standard errors are very widely used to account for
correlated or clustered data, especially in economics, political sciences, and other social …

Probabilistic forecasts in the form of probability distributions over future events have become
popular in several fields including meteorology, hydrology, economics, and demography. In …

Predictions and forecasts of machine learning models should take the form of probability
distributions, aiming to increase the quantity of information communicated to end users …

Postprocessing ensemble weather predictions to correct systematic errors has become a
standard practice in research and operations. However, only a few recent studies have …

Objectives The wording of the Hungarian EQ-5D-3L and EQ-5D-5L descriptive systems
differ a great deal. This study aimed to (1) develop EQ-5D-3L and EQ-5D-5L value sets for …

Statistical postprocessing of medium-range weather forecasts is an important component of
modern forecasting systems. Since the beginning of modern data science, numerous new …

Supplement A: Different response distributions. To assess the goodness of fit of the
Gaussian distribution, left-censored at zero, this supplement employs the same evaluations …