A Bayesian dynamic compositional model is introduced that can deal with combining a large set of predictive densities. It extends the mixture of experts and the smoothly mixing regression models by allowing for combination weight dependence across models and time. A compositional model with...

A flexible predictive density combination is introduced for large financial data sets which allows for model set incompleteness. Dimension reduction procedures that include learning allocate the large sets of predictive densities and combination weights to relatively small subsets. Given the...

The track record of a sixteen-year history of density forecasts of state tax revenue in Iowa is studied, and potential improvements sought through a search for better performing priors similar to that conducted two decades ago for point forecasts by Doan, Litterman, and Sims (Econometric...