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cff-version: 1.2.0
message: 'To cite package "bayesianVARs" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'bayesianVARs: MCMC Estimation of Bayesian Vectorautoregressions'
version: 0.1.4
doi: 10.32614/CRAN.package.bayesianVARs
abstract: Efficient Markov Chain Monte Carlo (MCMC) algorithms for the fully Bayesian
  estimation of vectorautoregressions (VARs) featuring stochastic volatility (SV).
  Implements state-of-the-art shrinkage priors following Gruber & Kastner (2023) <https://doi.org/10.48550/arXiv.2206.04902>.
  Efficient equation-per-equation estimation following Kastner & Huber (2020) <https://doi.org/10.1002/for.2680>
  and Carrerio et al. (2021) <https://doi.org/10.1016/j.jeconom.2021.11.010>.
authors:
- family-names: Gruber
  given-names: Luis
  email: Luis.Gruber@aau.at
  orcid: https://orcid.org/0000-0002-2399-738X
repository: https://CRAN.R-project.org/package=bayesianVARs
repository-code: https://github.com/luisgruber/bayesianVARs
url: https://luisgruber.github.io/bayesianVARs/
date-released: '2024-09-06'
contact:
- family-names: Gruber
  given-names: Luis
  email: Luis.Gruber@aau.at
  orcid: https://orcid.org/0000-0002-2399-738X