A diversity-based predictive prior added to the latent weight dynamics of a Bayesian forecast combination method (DTVW) improves point and density forecasts in simulations and in oil price and U.S. macro applications, compared with equal weights, BMA, and baseline TVW.
, author Casarin, R
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ME 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Bayesian Forecast Combination with Predictive Priors via Particle Filtering
A diversity-based predictive prior added to the latent weight dynamics of a Bayesian forecast combination method (DTVW) improves point and density forecasts in simulations and in oil price and U.S. macro applications, compared with equal weights, BMA, and baseline TVW.