Package: bayesRecon 0.3.2
Dario Azzimonti
bayesRecon: Probabilistic Reconciliation via Conditioning
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).
Authors:
bayesRecon_0.3.2.tar.gz
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bayesRecon_0.3.2.tgz(r-4.4-any)bayesRecon_0.3.2.tgz(r-4.3-any)
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bayesRecon.pdf |bayesRecon.html✨
bayesRecon/json (API)
NEWS
| # Install 'bayesRecon' in R: |
| install.packages('bayesRecon', repos = c('https://idsia.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/idsia/bayesrecon/issues
Pkgdown site:https://idsia.github.io
- M3_example - Example of a time series from the M3 forecasting competition
- M5_CA1_basefc - Example of hierarchical forecasts for a store from the M5 competition
- carparts_example - Example of a time series from carparts
- extr_mkt_events - Extreme market events dataset
- extr_mkt_events_basefc - Base forecasts for the extreme market events dataset
- infantMortality - Infant Mortality grouped time series dataset
Last updated 12 days agofrom:6a5e23860d. Checks:7 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Jan 20 2025 |
| R-4.5-win | OK | Jan 20 2025 |
| R-4.5-linux | OK | Jan 20 2025 |
| R-4.4-win | OK | Jan 20 2025 |
| R-4.4-mac | OK | Jan 20 2025 |
| R-4.3-win | OK | Jan 20 2025 |
| R-4.3-mac | OK | Jan 20 2025 |
Exports:get_reconc_matricesPMF.get_meanPMF.get_quantilePMF.get_varPMF.samplePMF.summaryreconc_BUISreconc_gaussianreconc_MCMCreconc_MixCondreconc_TDcondschaferStrimmer_covtemporal_aggregation
Dependencies:lpSolve
Probabilistic Reconciliation via Conditioning with bayesRecon
Rendered frombayesRecon.Rmdusingknitr::rmarkdownon Jan 20 2025.Last update: 2024-11-13
Started: 2023-07-26
Properties of the reconciled distribution via conditioning
Rendered fromreconciliation_properties.Rmdusingknitr::rmarkdownon Jan 20 2025.Last update: 2024-11-26
Started: 2023-12-14
Reconciliation of M5 hierarchy with mixed-type forecasts
Rendered frommixed_reconciliation.Rmdusingknitr::rmarkdownon Jan 20 2025.Last update: 2024-11-26
Started: 2024-05-29
