Package: bpvars
Type: Package
Title: Forecasting with Bayesian Panel Vector Autoregressions
Description: Provides Bayesian estimation and forecasting of dynamic
        panel data using Bayesian Panel Vector Autoregressions with
        hierarchical prior distributions following the specification by
        Sanchez-Martinez & Woźniak (2026)
        <doi:10.48550/arXiv.2606.14143>. The models include
        country-specific Vector Autoregressions (VARs) that share a
        global prior distribution that extend the model by Jarociński
        (2010) <doi:10.1002/jae.1082>. Under this prior expected value,
        each country's system follows a global VAR with
        country-invariant parameters. Further flexibility is provided
        by the hierarchical prior structure that retains the Minnesota
        prior interpretation for the global VAR and features estimated
        prior covariance matrices, shrinkage, and persistence levels.
        Bayesian forecasting is developed for models including
        exogenous variables, allowing conditional forecasts given the
        future trajectories of some variables and restricted forecasts
        assuring that rates are forecasted to stay positive and less
        than 100. The package implements the model specification,
        estimation, and forecasting routines, facilitating coherent
        workflows and reproducibility. It also includes automated
        pseudo-out-of-sample forecasting and computation of forecasting
        performance measures. Beautiful plots, informative summary
        functions, and extensive documentation complement all this.
        Extraordinary computational speed is achieved thanks to
        employing frontier econometric and numerical techniques and
        algorithms written in 'C++'. The 'bpvars' package is aligned
        regarding objects, workflows, and code structure with the 'R'
        packages 'bsvars' by Woźniak (2024)
        <doi:10.32614/CRAN.package.bsvars>, 'bsvarSIGNs' by Wang &
        Woźniak (2025) <doi:10.32614/CRAN.package.bsvarSIGNs>, and
        'bvars' by Liu, Ramirez Hassan, & Woźniak (2026)
        <doi:10.32614/CRAN.package.bvars> and they constitute an
        integrated toolset. Copyright: 2025 International Labour
        Organization. The International Labour Organization should not
        be held responsible for any issues arising from the use of the
        'bpvars' package or from the results obtained with it.
Version: 2.0.0.9000
Date: 2026-06-16
Authors@R: 
  c(
    person(given="Tomasz", family="Woźniak", email="wozniak.tom@pm.me", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-2212-2378")),
    person(given="Miguel", family="Sanchez-Martinez", role = "ctb"),
    person(given="International Labour Organization", role = "cph", comment = "The International Labour Organization should not be held responsible for any issues arising from the use of the 'bpvars' package or from the results obtained with it.")
  )
Maintainer: Tomasz Woźniak <wozniak.tom@pm.me>
License: GPL (>= 3)
Depends: R (>= 4.1.0), bsvars (>= 3.2)
Imports: R6, Rcpp (>= 1.0.12), RcppProgress, RcppTN, generics,
        TruncatedNormal
LinkingTo: bsvars, Rcpp, RcppArmadillo, RcppProgress, RcppTN
Suggests: knitr, tinytest
URL: https://bsvars.org/bpvars/
BugReports: https://github.com/bsvars/bpvars/issues
LazyData: true
Encoding: UTF-8
VignetteBuilder: knitr
Config/roxygen2/version: 8.0.0
Repository: https://bsvars.r-universe.dev
Date/Publication: 2026-06-16 07:41:40 UTC
RemoteUrl: https://github.com/bsvars/bpvars
RemoteRef: HEAD
RemoteSha: 4e82a1301e6e736ed210e2fa5dab83e8457ffa7b
NeedsCompilation: yes
Packaged: 2026-06-16 12:14:29 UTC; root
Author: Tomasz Woźniak [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-2212-2378>),
  Miguel Sanchez-Martinez [ctb],
  International Labour Organization [cph] (The International Labour
    Organization should not be held responsible for any issues arising
    from the use of the 'bpvars' package or from the results obtained
    with it.)