bayesRecon: Probabilistic Reconciliation via Conditioning
Dario Azzimonti, Lorenzo Zambon, Stefano Damato, Nicolò Rubattu, Giorgio Corani · 2023
Provides methods for probabilistic reconciliation of hierarchical forecasts of time series. The available methods include analytical Gaussian reconciliation (Corani et al., 2021) , MCMC reconciliation of count time series (Corani et al., 2024) , Bottom-Up Importance Sampling (Zambon et al., 2024) , methods for the reconciliation of mixed hierarchies (Mix-Cond and TD-cond) (Zambon et al., 2024) .