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DESCRIPTION
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DESCRIPTION
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Package: bayesRecon
Type: Package
Date: 2024-11-04
Title: Probabilistic Reconciliation via Conditioning
Version: 0.3.2
Authors@R: c(person(given = "Dario",
family = "Azzimonti",
role = c("aut","cre"),
email = "[email protected]",
comment = c(ORCID = "0000-0001-5080-3061")),
person(given = "Nicolò",
family = "Rubattu",
role = c("aut"),
email = "[email protected]",
comment = c(ORCID = "0000-0002-2703-1005")),
person(given = "Lorenzo",
family = "Zambon",
role = c("aut"),
email = "[email protected]",
comment = c(ORCID = "0000-0002-8939-993X")),
person(given = "Giorgio",
family = "Corani",
role = c("aut"),
email = "[email protected]",
comment = c(ORCID = "0000-0002-1541-8384")))
Maintainer: Dario Azzimonti <[email protected]>
Description: 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).
License: LGPL (>= 3)
Depends: R (>= 4.1.0)
Imports:
stats,
utils,
lpSolve (>= 5.6.18)
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown=TRUE)
RoxygenNote: 7.3.2
Suggests:
knitr,
rmarkdown,
forecast,
glarma,
scoringRules,
testthat (>= 3.0.0)
Config/testthat/edition: 3
VignetteBuilder: knitr
URL: https://github.com/IDSIA/bayesRecon
BugReports: https://github.com/IDSIA/bayesRecon/issues