DESCRIPTION

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 = "dario.azzimonti@gmail.com",
             comment = c(ORCID = "0000-0001-5080-3061")),
      person(given = "Nicolò",
             family = "Rubattu",
             role = c("aut"),
             email = "nicolo.rubattu@idsia.ch",
             comment = c(ORCID = "0000-0002-2703-1005")),
      person(given = "Lorenzo",
             family = "Zambon",
             role = c("aut"),
             email = "lorenzo.zambon@idsia.ch",
             comment = c(ORCID = "0000-0002-8939-993X")),
      person(given = "Giorgio",
             family = "Corani",
             role = c("aut"),
             email = "giorgio.corani@idsia.ch",
             comment = c(ORCID = "0000-0002-1541-8384")))
Maintainer: Dario Azzimonti <dario.azzimonti@gmail.com>
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, https://idsia.github.io/bayesRecon/
BugReports: https://github.com/IDSIA/bayesRecon/issues