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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "bayesRecon" in publications use:'
type: software
license: LGPL-3.0-or-later
title: 'bayesRecon: Probabilistic Reconciliation via Conditioning'
version: 0.3.2
doi: 10.32614/CRAN.package.bayesRecon
abstract: Provides methods for probabilistic reconciliation of hierarchical forecasts
  of time series. The available methods include analytical Gaussian reconciliation
  (Corani et al., 2021) <https://doi.org/10.1007/978-3-030-67664-3_13>, MCMC reconciliation
  of count time series (Corani et al., 2024) <https://doi.org/10.1016/j.ijforecast.2023.04.003>,
  Bottom-Up Importance Sampling (Zambon et al., 2024) <https://doi.org/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:
- family-names: Azzimonti
  given-names: Dario
  email: dario.azzimonti@gmail.com
  orcid: https://orcid.org/0000-0001-5080-3061
- family-names: Rubattu
  given-names: Nicolò
  email: nicolo.rubattu@idsia.ch
  orcid: https://orcid.org/0000-0002-2703-1005
- family-names: Zambon
  given-names: Lorenzo
  email: lorenzo.zambon@idsia.ch
  orcid: https://orcid.org/0000-0002-8939-993X
- family-names: Corani
  given-names: Giorgio
  email: giorgio.corani@idsia.ch
  orcid: https://orcid.org/0000-0002-1541-8384
repository: https://CRAN.R-project.org/package=bayesRecon
repository-code: https://github.com/IDSIA/bayesRecon
url: https://github.com/IDSIA/bayesRecon
date-released: '2024-11-04'
contact:
- family-names: Azzimonti
  given-names: Dario
  email: dario.azzimonti@gmail.com
  orcid: https://orcid.org/0000-0001-5080-3061