Package: shrinkTVPVAR
Type: Package
Title: Efficient Bayesian Inference for TVP-VAR-SV Models with
        Shrinkage
Version: 1.0.1
Authors@R: c(
  person("Peter", "Knaus", email = "peter.knaus@wu.ac.at",
    role = c("aut", "cre"), comment = c(ORCID = "0000-0001-6498-7084")))
Maintainer: Peter Knaus <peter.knaus@wu.ac.at>
Description: Efficient Markov chain Monte Carlo (MCMC) algorithms for
        fully Bayesian estimation of time-varying parameter vector
        autoregressive models with stochastic volatility (TVP-VAR-SV)
        under shrinkage priors and dynamic shrinkage processes. Details
        on the TVP-VAR-SV model and the shrinkage priors can be found
        in Cadonna et al. (2020) <doi:10.3390/econometrics8020020>,
        details on the software can be found in Knaus et al. (2021)
        <doi:10.18637/jss.v100.i13>, while details on the dynamic
        shrinkage process can be found in Knaus and Frühwirth-Schnatter
        (2023) <doi:10.48550/arXiv.2312.10487>.
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 3.3.0)
RoxygenNote: 7.3.2
LinkingTo: Rcpp, RcppProgress, RcppArmadillo, shrinkTVP (>= 3.1.0),
        stochvol
Imports: Rcpp, shrinkTVP (>= 3.1.0), stochvol, coda, methods,
        grDevices, RColorBrewer, lattice, zoo, mvtnorm
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
NeedsCompilation: yes
Packaged: 2026-10-11 10:00:49 UTC; root
Author: Peter Knaus [aut, cre] (ORCID:
        <https://orcid.org/0000-0001-6498-7084>)
Config/pak/sysreqs: libgsl0-dev
Repository: https://neferkareii.r-universe.dev
Date/Publication: 2025-06-03 13:40:07 UTC
RemoteUrl: https://github.com/cran/shrinkTVPVAR
RemoteRef: HEAD
RemoteSha: 7b514425590c877fec5eece1a39395566c69482b