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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>. For the multivariate extension, see the 'shrinkTVPVAR' package.

Versions across snapshots

VersionRepositoryFileSize
3.1.1 rolling linux/jammy R-4.5 shrinkTVP_3.1.1.tar.gz 1.1 MiB
3.1.1 rolling linux/noble R-4.5 shrinkTVP_3.1.1.tar.gz 1.1 MiB
3.1.1 rolling source/ R- shrinkTVP_3.1.1.tar.gz 1.0 MiB
3.1.1 latest linux/jammy R-4.5 shrinkTVP_3.1.1.tar.gz 1.1 MiB
3.1.1 latest linux/noble R-4.5 shrinkTVP_3.1.1.tar.gz 1.1 MiB
3.1.1 latest source/ R- shrinkTVP_3.1.1.tar.gz 1.0 MiB
3.1.1 2026-04-26 source/ R- shrinkTVP_3.1.1.tar.gz 1.0 MiB
3.1.1 2026-04-23 source/ R- shrinkTVP_3.1.1.tar.gz 1.0 MiB
3.1.1 2026-04-09 windows/windows R-4.5 shrinkTVP_3.1.1.zip 1.5 MiB
3.0.1 2025-04-20 source/ R- shrinkTVP_3.0.1.tar.gz 1.0 MiB

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