BGVAR: Bayesian Global Vector Autoregressions

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>.

Version: 2.5.9
Depends: R (≥ 3.5.0)
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
LinkingTo: Rcpp, RcppArmadillo, RcppProgress, RcppParallel, stochvol, GIGrvg
Suggests: rmarkdown, testthat (≥ 2.1.0)
Published: 2025-09-22
DOI: 10.32614/CRAN.package.BGVAR
Author: Maximilian Boeck ORCID iD [aut, cre], Martin Feldkircher ORCID iD [aut], Florian Huber ORCID iD [aut], Darjus Hosszejni ORCID iD [ctb]
Maintainer: Maximilian Boeck <maximilian.boeck at fau.de>
BugReports: https://github.com/mboeck11/BGVAR/issues
License: GPL-3
URL: https://github.com/mboeck11/BGVAR
NeedsCompilation: yes
SystemRequirements: GNU make
Language: en-US
Citation: BGVAR citation info
Materials: README, NEWS
In views: TimeSeries
CRAN checks: BGVAR results

Documentation:

Reference manual: BGVAR.html , BGVAR.pdf
Vignettes: BGVAR: Bayesian Global Vector Autoregression (source, R code)

Downloads:

Package source: BGVAR_2.5.9.tar.gz
Windows binaries: r-devel: BGVAR_2.5.9.zip, r-release: BGVAR_2.5.9.zip, r-oldrel: BGVAR_2.5.9.zip
macOS binaries: r-release (arm64): BGVAR_2.5.9.tgz, r-oldrel (arm64): BGVAR_2.5.9.tgz, r-release (x86_64): BGVAR_2.5.9.tgz, r-oldrel (x86_64): BGVAR_2.5.9.tgz
Old sources: BGVAR archive

Linking:

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