mfbvar: Mixed-Frequency Bayesian VAR Models

Estimation of mixed-frequency Bayesian vector autoregressive (VAR) models with Minnesota or steady-state priors. The package implements a state space-based VAR model that handles mixed frequencies of the data. The model is estimated using Markov Chain Monte Carlo to numerically approximate the posterior distribution, where the prior can be either the Minnesota prior, as used by Schorfheide and Song (2015) <doi:10.1080/07350015.2014.954707>, or the steady-state prior, as advocated by Ankargren, Unosson and Yang (2018) <>.

Version: 0.4.0
Depends: R (≥ 2.10)
Imports: Rcpp (≥ 0.12.7), ggplot2 (≥ 2.2.1), methods, pbapply, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, covr
Published: 2018-12-27
Author: Sebastian Ankargren ORCID iD [cre, aut], Yukai Yang [aut]
Maintainer: Sebastian Ankargren <sebastian.ankargren at>
License: GPL-3
NeedsCompilation: yes
CRAN checks: mfbvar results


Reference manual: mfbvar.pdf
Package source: mfbvar_0.4.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: mfbvar_0.4.0.tgz, r-oldrel: not available


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