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shrinkTVPVAR: Efficient Bayesian Inference for TVP-VAR-SV Models with
Shrinkage
Efficient Markov chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of time-varying parameter vector autoregressive models with shrinkage priors. Details on the algorithms used are provided in
Cadonna et al. (2020) <doi:10.3390/econometrics8020020> and Knaus et al. (2021) <doi:10.18637/jss.v100.i13>.
| Version: |
0.1.1 |
| Depends: |
R (≥ 3.3.0) |
| Imports: |
Rcpp, shrinkTVP, stochvol, coda, methods, grDevices, RColorBrewer, lattice, zoo |
| LinkingTo: |
Rcpp, RcppProgress, RcppArmadillo, shrinkTVP, stochvol |
| Suggests: |
testthat (≥ 3.0.0) |
| Published: |
2024-09-16 |
| DOI: |
10.32614/CRAN.package.shrinkTVPVAR |
| Author: |
Peter Knaus  [aut,
cre] |
| Maintainer: |
Peter Knaus <peter.knaus at wu.ac.at> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
yes |
| CRAN checks: |
shrinkTVPVAR results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=shrinkTVPVAR
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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