bayesRecon
1.0.1Probabilistic Reconciliation via Conditioning
Overview
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) https://proceedings.mlr.press/v244/zambon24a.html, analytical reconciliation with Bayesian treatment of the covariance matrix (Carrara et al., 2025) <doi: 10.48550/arXiv.2506.19554>.
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- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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Checks run against github.com/idsia/bayesrecon on 2026-07-19.
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People & History
10 releases. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.0.1Latest
- 1.0.02026-03-08 · diff ↗
- 0.3.32025-07-21 · diff ↗
- RR 4.5.0 released · 2025-04-11
- 0.3.22024-11-04 · diff ↗
- 0.3.12024-08-28 · diff ↗
- 0.3.02024-05-30 · diff ↗
- RR 4.4.0 released · 2024-04-24
- 0.2.02023-12-19 · diff ↗
- 0.1.22023-08-24 · diff ↗
- 0.1.12023-06-10 · diff ↗
- 0.1.02023-05-26
- RR 4.3.0 released · 2023-04-21
Package metadata
- First published
- 2023-05-26
- Total releases
- 10 / 3 yrs
- License
- LGPL (>= 3) OSI
- Download size
- 2.9 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet