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
 [cre, aut],
Yukai Yang [aut],
Gregor Kastner
[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 |