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Efficient Markov chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of time-varying parameter models with shrinkage priors, both dynamic and static. Details on the algorithms used are provided in Bitto and Frühwirth-Schnatter (2019) <doi:10.1016/j.jeconom.2018.11.006> and Cadonna et al. (2020) <doi:10.3390/econometrics8020020> and Knaus and Frühwirth-Schnatter (2023) <doi:10.48550/arXiv.2312.10487>. For details on the package, please see Knaus et al. (2021) <doi:10.18637/jss.v100.i13>.
Version: | 3.0.1 |
Depends: | R (≥ 3.3.0) |
Imports: | Rcpp, GIGrvg, stochvol (≥ 3.0.3), coda, methods, utils, zoo |
LinkingTo: | Rcpp, RcppArmadillo, GIGrvg, RcppProgress, stochvol, RcppGSL |
Suggests: | testthat, knitr, rmarkdown, R.rsp |
Published: | 2024-02-18 |
DOI: | 10.32614/CRAN.package.shrinkTVP |
Author: | Peter Knaus [aut, cre], Angela Bitto-Nemling [aut], Annalisa Cadonna [aut], Sylvia Frühwirth-Schnatter [aut], Daniel Winkler [ctb], Kemal Dingic [ctb] |
Maintainer: | Peter Knaus <peter.knaus at wu.ac.at> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
Citation: | shrinkTVP citation info |
Materials: | NEWS |
In views: | Bayesian |
CRAN checks: | shrinkTVP results |
Reference manual: | shrinkTVP.pdf |
Vignettes: |
Shrinkage in the Time-Varying Parameter Model Framework Using the R Package shrinkTVP |
Package source: | shrinkTVP_3.0.1.tar.gz |
Windows binaries: | r-devel: shrinkTVP_3.0.1.zip, r-release: shrinkTVP_3.0.1.zip, r-oldrel: shrinkTVP_3.0.1.zip |
macOS binaries: | r-release (arm64): shrinkTVP_3.0.1.tgz, r-oldrel (arm64): shrinkTVP_3.0.1.tgz, r-release (x86_64): shrinkTVP_3.0.1.tgz, r-oldrel (x86_64): shrinkTVP_3.0.1.tgz |
Old sources: | shrinkTVP archive |
Reverse imports: | shrinkDSM, shrinkTVPVAR |
Reverse linking to: | shrinkDSM, shrinkTVPVAR |
Reverse suggests: | tidyfit |
Please use the canonical form https://CRAN.R-project.org/package=shrinkTVP to link to this page.
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.