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shrinkTVP  

Efficient Bayesian Inference for Time-Varying Parameter Models with Shrinkage
View on CRAN: Click here


Download and install shrinkTVP package within the R console
Install from CRAN:
install.packages("shrinkTVP")

Install from Github:
library("remotes")
install_github("cran/shrinkTVP")

Install by package version:
library("remotes")
install_version("shrinkTVP", "3.1.1")



Attach the package and use:
library("shrinkTVP")
Maintained by
Peter Knaus
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-06-19
Latest Update: 2025-06-02
Description:
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>.
How to cite:
Peter Knaus (2019). shrinkTVP: Efficient Bayesian Inference for Time-Varying Parameter Models with Shrinkage. R package version 3.1.1, https://cran.r-project.org/web/packages/shrinkTVP. Accessed 04 Jun. 2026.
Previous versions and publish date:
1.0.0 (2019-06-19 14:10), 1.0.1 (2019-07-15 12:10), 1.0.2 (2019-08-07 16:40), 1.1.0 (2019-10-06 15:30), 1.1.1 (2019-10-06 18:00), 2.0.1 (2020-11-09 22:40), 2.0.2 (2021-05-13 13:50), 2.0.3 (2021-10-21 16:30), 2.0.4 (2021-11-26 17:10), 2.0.5 (2022-02-03 14:20), 2.0.6 (2022-10-19 01:30), 2.0 (2020-11-05 18:30), 2.1.1 (2023-11-22 18:40), 3.0.1 (2024-02-18 20:40), 3.1.0 (2025-06-02 17:40)
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