Package: mfbvar
Type: Package
Title: Mixed-Frequency Bayesian VAR Models
Version: 0.5.3
Date: 2020-03-18
Authors@R: c(
    person("Sebastian", "Ankargren", email = "sebastian.ankargren@statistics.uu.se", role = c("cre", "aut"), comment = c(ORCID = "0000-0003-4415-8734")),
    person("Yukai", "Yang", email = "yukai.yang@statistics.uu.se", role = c("aut"), comment=c(ORCID="0000-0002-2623-8549")),
    person("Gregor", "Kastner", role = "ctb", comment = c(ORCID="0000-0002-8237-8271")))
Description: 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. The model is 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.
License: GPL-3
LazyData: TRUE
URL: https://github.com/ankargren/mfbvar
BugReports: https://github.com/ankargren/mfbvar/issues
Imports: Rcpp (>= 0.12.7), ggplot2 (>= 3.3.0), methods, lubridate,
        GIGrvg, stochvol (>= 2.0.3), RcppParallel, dplyr, magrittr,
        tibble
LinkingTo: Rcpp, RcppArmadillo, RcppProgress, stochvol (>= 2.0.3),
        RcppParallel
Depends: R (>= 3.5.0)
Suggests: testthat, covr, knitr, ggridges, alfred, factorstochvol,
        purrr
RoxygenNote: 6.1.1
Encoding: UTF-8
SystemRequirements: GNU make
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-03-19 21:22:35 UTC; sebastianankargren
Author: Sebastian Ankargren [cre, aut]
    (<https://orcid.org/0000-0003-4415-8734>),
  Yukai Yang [aut] (<https://orcid.org/0000-0002-2623-8549>),
  Gregor Kastner [ctb] (<https://orcid.org/0000-0002-8237-8271>)
Maintainer: Sebastian Ankargren <sebastian.ankargren@statistics.uu.se>
Repository: CRAN
Date/Publication: 2020-03-19 22:30:06 UTC
Built: R 4.0.0; x86_64-w64-mingw32; 2020-04-10 10:13:26 UTC; windows
Archs: i386, x64
