mfbvar: Mixed-Frequency Bayesian VAR Models

Functions and tools for estimation of mixed-frequency Bayesian vector autoregressive (VAR) models. The package implements a state space-based VAR model that handles mixed frequencies of the data as proposed by Schorfheide and Song (2015) <doi:10.1080/07350015.2014.954707>, and extensions thereof developed by Ankargren, Unosson and Yang (2020) <doi:10.1515/jtse-2018-0034>, Ankargren and Joneus (2019) <arXiv:1912.02231>, and Ankargren and Joneus (2020) <doi:10.1016/j.ecosta.2020.05.007>. The models are estimated using Markov Chain Monte Carlo to numerically approximate the posterior distribution. Prior distributions that can be used include normal-inverse Wishart and normal-diffuse priors as well as steady-state priors. Stochastic volatility can be handled by common or factor stochastic volatility models.

Version: 0.5.6
Depends: R (≥ 3.5.0)
Imports: Rcpp (≥ 0.12.7), ggplot2 (≥ 3.3.0), methods, lubridate, GIGrvg, stochvol (≥ 2.0.3), RcppParallel, dplyr, magrittr, tibble, zoo
LinkingTo: Rcpp, RcppArmadillo, RcppProgress, stochvol (≥ 2.0.3), RcppParallel
Suggests: testthat, covr, knitr, ggridges, alfred, factorstochvol
Published: 2021-02-10
Author: Sebastian Ankargren ORCID iD [cre, aut], Yukai Yang ORCID iD [aut], Gregor Kastner ORCID iD [ctb]
Maintainer: Sebastian Ankargren <sebastian.ankargren at statistics.uu.se>
BugReports: https://github.com/ankargren/mfbvar/issues
License: GPL-3
URL: https://github.com/ankargren/mfbvar
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: mfbvar citation info
Materials: README NEWS
In views: TimeSeries
CRAN checks: mfbvar results

Downloads:

Reference manual: mfbvar.pdf
Vignettes: Bayesian Mixed-Frequency VARs
Package source: mfbvar_0.5.6.tar.gz
Windows binaries: r-devel: mfbvar_0.5.6.zip, r-release: mfbvar_0.5.6.zip, r-oldrel: mfbvar_0.5.6.zip
macOS binaries: r-release: mfbvar_0.5.6.tgz, r-oldrel: mfbvar_0.5.6.tgz
Old sources: mfbvar archive

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