We offer a dynamic Bayesian forecasting model for multiparty elections. It combines data from published pre-election public opinion polls with information from fundamentals-based forecasting models.

Bayesian model averaging (BMA) is a popular ensemble-based postprocessing approach where the weighted average of the individual members is used to generate predictive forecasts. As the BMA formulation ...

A novel Bayesian Hierarchical Network Model (BHNM) is designed for ensemble predictions of daily river stage, leveraging the spatial interdependence of river networks and hydrometeorological variables ...