Efficient Markov chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of time-varying parameter vector autoregressive models with stochastic volatility (TVP-VAR-SV) under shrinkage priors and dynamic shrinkage processes. Details on the TVP-VAR-SV model and the shrinkage priors can be found in Cadonna et al. (2020) <doi:10.3390/econometrics8020020>, details on the software can be found in Knaus et al. (2021) <doi:10.18637/jss.v100.i13>, while details on the dynamic shrinkage process can be found in Knaus and Frühwirth-Schnatter (2023) <doi:10.48550/arXiv.2312.10487>.
Version: 1.0.1 Depends: R (≥ 3.3.0) Imports: Rcpp, shrinkTVP (≥ 3.1.0), stochvol, coda, methods, grDevices, RColorBrewer, lattice, zoo, mvtnorm LinkingTo: Rcpp, RcppProgress, RcppArmadillo, shrinkTVP (≥ 3.1.0), stochvol Suggests: testthat (≥ 3.0.0) Published: 2025-06-03 DOI: 10.32614/CRAN.package.shrinkTVPVAR Author: Peter Knaus [aut, cre] Maintainer: Peter Knaus <peter.knaus at wu.ac.at> License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] NeedsCompilation: yes Materials: NEWS CRAN checks: shrinkTVPVAR results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=shrinkTVPVAR to link to this page.
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