shrinkTVPVAR: Efficient Bayesian Inference for TVP-VAR-SV Models with Shrinkage (original) (raw)
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 |
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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 |
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