DESCRIPTION

Package: bayesianVARs
Title: MCMC Estimation of Bayesian Vectorautoregressions
Version: 0.1.5
Authors@R: c(
    person("Luis", "Gruber", , "Luis.Gruber@aau.at", role = c("cph", "aut", "cre"),
           comment = c(ORCID = "0000-0002-2399-738X")),
    person("Gregor", "Kastner", , "gregor.kastner@aau.at", role = "ctb",
           comment = c(ORCID = "0000-0002-8237-8271"))
  )
Description: 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) <doi:10.48550/arXiv.2206.04902>.
    Efficient equation-per-equation estimation following Kastner & Huber
    (2020) <doi:10.1002/for.2680> and Carrerio et al. (2021)
    <doi:10.1016/j.jeconom.2021.11.010>.
License: GPL (>= 3)
URL: https://github.com/luisgruber/bayesianVARs,
    https://luisgruber.github.io/bayesianVARs/
BugReports: https://github.com/luisgruber/bayesianVARs/issues
Depends: 
    R (>= 3.3.0)
Imports: 
    colorspace,
    factorstochvol (>= 1.1.0),
    GIGrvg (>= 0.7),
    graphics,
    MASS,
    mvtnorm,
    Rcpp (>= 1.0.0),
    scales,
    stats,
    stochvol (>= 3.0.3),
    utils
Suggests:
    coda,
    knitr,
    rmarkdown,
    testthat (>= 3.0.0)
LinkingTo: 
    factorstochvol,
    Rcpp,
    RcppArmadillo,
    RcppProgress,
    stochvol
VignetteBuilder: 
    knitr
Config/testthat/edition: 3
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.1