R Observatory: Metrics for bvars version 1.1

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

bvars

1.1Package record

Bayesian Forecasting with Large Vector Autoregressions

0packages depend

1.7Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Tomasz WoźniakCRAN page ↗GitHub ↗Website ↗Issues ↗

Provides fast and efficient procedures for Bayesian estimation and forecasting using state-of-the-art Vector Autoregressions. This package includes the model proposed by Shang, Wang, Woźniak (2026) doi:10.48550/arXiv.2608.28087 and Chan (2020) doi:10.1080/07350015.2018.1451336, that is, a Bayesian Vector Autoregression with Minnesota priors and a flexible structure of the error term specification. The latter includes: conditional multivariate normal or Student’s t distributions, as well as homoskedastic or heteroskedastic specifications with a common volatility modelled by centred or non-centred Stochastic Volatility. Additionally, the package facilitates predictive analyses using density forecasting and forecast-error variance decompositions. All this is complemented by simple workflows, useful plots and summary functions, and comprehensive documentation. The 'bvars' package aligns with R packages 'bsvars' by Woźniak (2026) doi:10.32614/CRAN.package.bsvars, 'bsvarSIGNs' by Wang & Woźniak (2026) doi:10.32614/CRAN.package.bsvarSIGNs, and 'bpvars' by Woźniak (2026) doi:10.32614/CRAN.package.bpvars regarding objects, workflows, and code structure, and they constitute an integrated toolset.

Changes in 1.1

The package is under intensive development, and more functionality will be provided soon! To see the package ROADMAP towards the next version.

Have a question, or suggestion, or wanna get in touch? Email us at [contact\@bsvars.org](mailto:contact@bsvars.org) forum.

1. Updated package description with the paper by Shang, Wang, Woźniak (2026)

2. Introduced a range of code improvements by Fei Shang in PRs #15-#21

3. Corrected documentation for argument stationary #14

4. Introduced **R6** coding for class Forecasts #11

5. Coded tests for package functions #11

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("bvars", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("bsvars/bvars")

Development version from bsvars/bvars. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-bvars

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-bvars

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-bvars

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 5.1 min · r-devel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK7 OK2026-06-09

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 1.1

READMEYes · 960 wordsVignettesNoNEWSYes · 67% structured · mentions 1.1Citation fileNoWebsiteYes · pkgdown

Help pages: 16 (1 internal)includes a package overview page
Examples that run: 100%15 run in a plain check
Exported functions with examples: 86%
Documented parameters: 100%
Return-value docs: 29%
Help pages citing references: 31%

How these are measured

Downloads

1.7K

CRAN downloads in the past year

Rank #7,905 · ~5/day · ~144/mo

Releases R versions

Daily download trend is not available in this view yet.

32430 days

1.2K90 days

1.7K1 year

Compare downloads with other packages →

Also on118 r2u9 autocran

How downloads are counted

Repository

bsvars/bvars ↗Organization: bsvars

6Stars

3Forks

3Open issues

0Open PRs

2Releases

180Commits

3Commit identities

bvarrstatsminnesota-priorcommon-stochastic-volatilitystudent-t-errors

180 commits · Last activity 2026-10-22 · 0% stars, 30d · Default branch at 1.1.0.9000, ahead of CRAN 1.1 (checked 2026-10-21)

Responsiveness

How these are sampled

PRs merged (all time): 91%
Median days to close, 50 most recently updated closed issues: 12
Median days to close, 50 most recently updated closed PRs: 4

Stars over time

2025-10-20 · 12026-09-20 · 6

How these are measured

PracticesBeta

7 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/bsvars/bvars on 2026-10-21.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Docs source (4)

README.Rmdpkgdown

GitHub Pages site last deployed 2026-09-07 · The repository has a site deploy workflow

pkgdown site last built 2026-09-07

CRAN release process (1)

cran-comments.md

How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies

13 external dependencies (excludes base and recommended)

Installing bvars adds 10 packages (6 with compiled code, 7.4 MB of source tarballs). Heaviest: stochvol 3.2 MB, Rcpp 1.8 MB, bsvars 1.2 MB.

Depends (3)

R >= 4.1.0RcppArmadillo bsvars

Imports (5)

generics Rcpp RcppProgress RcppTN R6

LinkingTo (5)

Rcpp RcppArmadillo RcppProgress RcppTN bsvars

Suggests (1)

tinytest

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (5)

Tomasz Woźniak

Author, Maintainer since 1.0 (2026)

Rui Liu

Author

Andrés Ramirez Hassan

Author

Fei Shang

Contributor · added in 1.1

co-authored the paper by Shang, Wang, Woźniak (2026), introduced major code corrections and improvements

Xiaolei Wang

Contributor · added in 1.1

co-authored the paper by Shang, Wang, Woźniak (2026)

Releases (2)

Pick two releases to compare their code metrics.

1.1Latest
record
2026-09-07 · current release · diff ↗
1.0
record
2026-06-08
R
R 4.6.0 released · 2026-04-24

Package metadata

First published: 2026-06-08
Total releases: 2 / 1 yrs
License: GPL (>= 3) OSI
Minimum R: ≥ 4.1.0
Bundled data: 18 KB / 1 file
Download size: 123 KB

Appears in task views

Time Series Analysis

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("bvars")

Format

Woźniak, T., Liu, R., Ramirez Hassan, A., Shang, F., & Wang, X. (2026). bvars: Bayesian Forecasting with Large Vector Autoregressions (Version 1.1) [Computer software]. https://doi.org/10.32614/CRAN.package.bvars

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for bvars version 1.1 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

Report a problem with this page →