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., 2022) <doi:10.48550/arXiv.2207.09322>, Bottom-Up Importance Sampling (Zambon et al., 2022) <doi:10.48550/arXiv.2210.02286>.
| Version: | 0.2.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | stats, utils, lpSolve (≥ 5.6.18) |
| Suggests: | knitr, rmarkdown, forecast, glarma, scoringRules, testthat (≥ 3.0.0) |
| Published: | 2023-12-19 |
| Author: | Dario Azzimonti 
[aut, cre],
Nicolò Rubattu
[aut],
Lorenzo Zambon
[aut],
Giorgio Corani
[aut] |
| Maintainer: | Dario Azzimonti <dario.azzimonti at gmail.com> |
| License: | LGPL (≥ 3) |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| In views: | TimeSeries |
| CRAN checks: | bayesRecon results |
Documentation:
| Reference manual: | bayesRecon.pdf |
| Vignettes: |
Probabilistic Reconciliation via Conditioning with 'bayesRecon' Properties of the reconciled distribution via conditioning |
Downloads:
| Package source: | bayesRecon_0.2.0.tar.gz |
| Windows binaries: | r-devel: bayesRecon_0.2.0.zip, r-release: bayesRecon_0.2.0.zip, r-oldrel: bayesRecon_0.2.0.zip |
| macOS binaries: | r-release (arm64): bayesRecon_0.2.0.tgz, r-oldrel (arm64): bayesRecon_0.2.0.tgz, r-release (x86_64): bayesRecon_0.2.0.tgz, r-oldrel (x86_64): bayesRecon_0.2.0.tgz |
| Old sources: | bayesRecon archive |
Linking:
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