BVAR: Hierarchical Bayesian Vector Autoregression

Estimation of hierarchical Bayesian vector autoregressive models following Kuschnig & Vashold (2021) <doi:10.18637/jss.v100.i14>. Implements hierarchical prior selection for conjugate priors in the fashion of Giannone, Lenza & Primiceri (2015) <doi:10.1162/REST_a_00483>. Functions to compute and identify impulse responses, calculate forecasts, forecast error variance decompositions and scenarios are available. Several methods to print, plot and summarise results facilitate analysis.

Version:	1.0.5
Depends:	R (≥ 3.3.0)
Imports:	mvtnorm, stats, graphics, utils, grDevices
Suggests:	coda, vars, tinytest
Published:	2024-02-16
DOI:	10.32614/CRAN.package.BVAR
Author:	Nikolas Kuschnig [aut, cre], Lukas Vashold [aut], Nirai Tomass [ctb], Michael McCracken [dtc], Serena Ng [dtc]
Maintainer:	Nikolas Kuschnig <nikolas.kuschnig at wu.ac.at>
BugReports:	https://github.com/nk027/bvar/issues
License:	GPL-3 | file LICENSE
URL:	https://github.com/nk027/bvar
NeedsCompilation:	no
Citation:	BVAR citation info
Materials:	README NEWS
In views:	Bayesian, TimeSeries
CRAN checks:	BVAR results

Documentation:

Reference manual:	BVAR.pdf
Vignettes:	BVAR: Bayesian Vector Autoregressions with Hierarchical Prior Selection in R

Downloads:

Package source:	BVAR_1.0.5.tar.gz
Windows binaries:	r-devel: BVAR_1.0.5.zip, r-release: BVAR_1.0.5.zip, r-oldrel: BVAR_1.0.5.zip
macOS binaries:	r-release (arm64): BVAR_1.0.5.tgz, r-oldrel (arm64): BVAR_1.0.5.tgz, r-release (x86_64): BVAR_1.0.5.tgz, r-oldrel (x86_64): BVAR_1.0.5.tgz
Old sources:	BVAR archive

Reverse dependencies:

Reverse depends:

BVARverse

Linking:

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