DESCRIPTION

Package: mfbvar
Type: Package
Title: Mixed-Frequency Bayesian VAR Models 
Version: 0.5.6
Date: 2021-02-09
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: 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.
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, 
    zoo
LinkingTo:
    Rcpp, 
    RcppArmadillo, 
    RcppProgress, 
    stochvol (>= 2.0.3), 
    RcppParallel
Depends: R (>= 3.5.0)
Suggests: testthat, covr, knitr, ggridges, alfred, factorstochvol
RoxygenNote: 7.1.1
Encoding: UTF-8
SystemRequirements: GNU make
VignetteBuilder: knitr