shrinkTVP
Efficient Bayesian Inference for Time-Varying Parameter Models with Shrinkage
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.
- Version3.0.1
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- shrinkTVP citation info
- Last release02/18/2024
Documentation
Team
Peter Knaus
MaintainerShow author detailsDaniel Winkler
Show author detailsRolesContributorSylvia Frühwirth-Schnatter
Angela Bitto-Nemling
Show author detailsRolesAuthorAnnalisa Cadonna
Kemal Dingic
Show author detailsRolesContributor
Insights
Last 30 days
This package has been downloaded 411 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 5 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 5,732 times in the last 365 days. A solid achievement! Enough downloads to get noticed at department meetings. The day with the most downloads was Jul 03, 2024 with 184 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports5 packages
- Suggests4 packages
- Linking To6 packages
- Reverse Imports2 packages
- Reverse Suggests1 package