DESCRIPTION

Package: bsvars
Type: Package
Title: Bayesian Estimation of Structural Vector Autoregressive Models
Version: 1.0.1.9000
Date: 2022-09-30
Authors@R: person("Tomasz", "Woźniak", , "wozniak.tom@pm.me", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0003-2212-2378"))
Description: Efficient algorithms for Bayesian estimation of Structural Vector Autoregressive (SVAR) models via Markov chain Monte Carlo methods. A wide range of SVAR models is considered, including homo- and heteroskedastic specifications and those with non-normal structural shocks. The heteroskedastic SVAR model setup is similar as in Woźniak & Droumaguet (2015) <doi:10.13140/RG.2.2.19492.55687> and Lütkepohl & Woźniak (2020) <doi:10.1016/j.jedc.2020.103862>. The sampler of the structural matrix follows Waggoner & Zha (2003) <doi:10.1016/S0165-1889(02)00168-9>, whereas that for autoregressive parameters follows Chan, Koop, Yu (2022) <https://www.joshuachan.org/papers/OISV.pdf>. The specification of Markov switching heteroskedasticity is inspired by Song & Woźniak (2021) <doi:10.1093/acrefore/9780190625979.013.174>, and that of Stochastic Volatility model by Kastner & Frühwirth-Schnatter (2014) <doi:10.1016/j.csda.2013.01.002>.
License: GPL (>= 3)
Maintainer: Tomasz Woźniak <wozniak.tom@pm.me>
Encoding: UTF-8
Imports: 
    Rcpp (>= 1.0.7),
    RcppProgress (>= 0.1),
    RcppTN,
    GIGrvg,
    R6,
    stochvol
Suggests: 
    tinytest
LinkingTo: Rcpp, RcppProgress, RcppArmadillo, RcppTN
BugReports: https://github.com/donotdespair/bsvars/issues
RoxygenNote: 7.2.3