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).

Last 30 days

This package has been downloaded 600 times in the last 30 days. Not bad! The download count is somewhere between 'small-town buzz' and 'moderate academic conference'. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 60 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 7,122 times in the last 365 days. Impressive! The kind of number that makes colleagues ask, 'How did you do it?' The day with the most downloads was Feb 20, 2025 with 78 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.