The ability to forecast solar irradiance plays an indispensable role in solar power
forecasting, which constitutes an essential step in planning and operating power systems …

Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …

Probabilistic solar forecasts may take the form of predictive probability distributions,
ensembles, quantiles, or interval forecasts. State-of-the-art approaches build on input from …

A probabilistic forecast takes the form of a predictive probability distribution over future
quantities or events of interest. Probabilistic forecasting aims to maximize the sharpness of …

The randomness and intermittence of wind resources is the biggest challenge in the
integration of wind power into the power system. Accurate forecasting of wind power …

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

Ensemble forecasting applied to the field of hydrology is currently an established area of
research embracing a broad spectrum of operational situations. This work catalogs the …

Verifying the correctness of Bayesian computation is challenging. This is especially true for
complex models that are common in practice, as these require sophisticated model …

Structured additive regression models are perhaps the most commonly used class of models
in statistical applications. It includes, among others,(generalized) linear …

Typically, point forecasting methods are compared and assessed by means of an error
measure or scoring function, with the absolute error and the squared error being key …