Package: BGVAR
Type: Package
Title: Bayesian Global Vector Autoregressions
Version: 2.6.0
Author: Maximilian Boeck [aut, cre]
        (<https://orcid.org/0000-0001-6024-8305>), Martin Feldkircher
        [aut] (<https://orcid.org/0000-0002-5511-9215>), Florian Huber
        [aut] (<https://orcid.org/0000-0002-2896-7921>), Darjus
        Hosszejni [ctb] (<https://orcid.org/0000-0002-3803-691X>)
Authors@R: c(person("Maximilian","Boeck",role=c("aut","cre"), email="maximilian.boeck@fau.de",
                    comment = c(ORCID = "0000-0001-6024-8305")),
             person("Martin","Feldkircher", role="aut",
                    comment = c(ORCID = "0000-0002-5511-9215")),
             person("Florian","Huber", role="aut",
                    comment = c(ORCID = "0000-0002-2896-7921")),
             person("Darjus","Hosszejni", role="ctb",
                    comment = c(ORCID = "0000-0002-3803-691X")))
Maintainer: Maximilian Boeck <maximilian.boeck@fau.de>
Description: Estimation of Bayesian Global Vector Autoregressions
        (BGVAR) with different prior setups and the possibility to
        introduce stochastic volatility. Built-in priors include the
        Minnesota, the stochastic search variable selection and
        Normal-Gamma (NG) prior. For a reference see also Crespo
        Cuaresma, J., Feldkircher, M. and F. Huber (2016) "Forecasting
        with Global Vector Autoregressive Models: a Bayesian Approach",
        Journal of Applied Econometrics, Vol. 31(7), pp. 1371-1391
        <doi:10.1002/jae.2504>. Post-processing functions allow for
        doing predictions, structurally identify the model with
        short-run or sign-restrictions and compute impulse response
        functions, historical decompositions and forecast error
        variance decompositions. Plotting functions are also available.
        The package has a companion paper: Boeck, M., Feldkircher, M.
        and F. Huber (2022) "BGVAR: Bayesian Global Vector
        Autoregressions with Shrinkage Priors in R", Journal of
        Statistical Software, Vol. 104(9), pp. 1-28
        <doi:10.18637/jss.v104.i09>.
Encoding: UTF-8
License: GPL-3
Language: en-US
URL: https://github.com/mboeck11/BGVAR
BugReports: https://github.com/mboeck11/BGVAR/issues
Depends: R (>= 3.5.0)
SystemRequirements: GNU make
Imports: abind, bayesm, coda, GIGrvg, graphics, knitr, MASS, Matrix,
        methods, parallel, Rcpp (>= 1.0.3), RcppParallel, readxl,
        stats, stochvol (>= 3.0.3), utils, xts, zoo
Suggests: rmarkdown, testthat (>= 2.1.0)
LazyData: true
LinkingTo: Rcpp, RcppArmadillo, RcppProgress, RcppParallel, stochvol,
        GIGrvg
RoxygenNote: 7.3.2
VignetteBuilder: knitr
Config/pak/sysreqs: make
Repository: https://mboeck11.r-universe.dev
Date/Publication: 2025-10-31 08:43:23 UTC
RemoteUrl: https://github.com/mboeck11/bgvar
RemoteRef: HEAD
RemoteSha: 6f3f74e4c62c76e4c7d9c749d87ac53f9e44a61e
NeedsCompilation: yes
Packaged: 2026-07-03 18:42:32 UTC; root