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.
Version: 3.1.0 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: 2025-06-02 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 Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=shrinkTVP to link to this page.
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