bayesRecon

Provides methods for probabilistic reconciliation of hierarchical forecasts of time series. The available methods include analytical Gaussian reconciliation (Corani et al., 2021) doi:10.1007/978-3-030-67664-3_13, MCMC reconciliation of count time series (Corani et al., 2024) doi:10.1016/j.ijforecast.2023.04.003, Bottom-Up Importance Sampling (Zambon et al., 2024) doi:10.1007/s11222-023-10343-y, methods for the reconciliation of mixed hierarchies (Mix-Cond and TD-cond) (Zambon et al., 2024. The 40th Conference on Uncertainty in Artificial Intelligence, accepted).

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