Package: shrinkTVP 3.0.1

Peter Knaus

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>.

Authors:Peter Knaus [aut, cre], Angela Bitto-Nemling [aut], Annalisa Cadonna [aut], Sylvia Frühwirth-Schnatter [aut], Daniel Winkler [ctb], Kemal Dingic [ctb]

shrinkTVP_3.0.1.tar.gz
shrinkTVP_3.0.1.tar.gz(r-4.5-noble)shrinkTVP_3.0.1.tar.gz(r-4.4-noble)
shrinkTVP_3.0.1.tgz(r-4.4-emscripten)shrinkTVP_3.0.1.tgz(r-4.3-emscripten)
shrinkTVP.pdf |shrinkTVP.html
shrinkTVP/json (API)
NEWS

# Install 'shrinkTVP' in R:
install.packages('shrinkTVP', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • gsl– GNU Scientific Library (GSL)
  • c++– GNU Standard C++ Library v3

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.38 score 2 stars 2 packages 6 scripts 407 downloads 7 exports 9 dependencies

Last updated 10 months agofrom:9e254834d8. Checks:ERROR: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesFAILNov 15 2024
R-4.5-linux-x86_64NOTENov 15 2024

Exports:eval_pred_densforecast_shrinkTVPLPDSshrinkDTVPshrinkTVPsimTVPupdateTVP

Dependencies:codaGIGrvglatticeRcppRcppArmadilloRcppGSLRcppProgressstochvolzoo

Shrinkage in the Time-Varying Parameter Model Framework Using the R Package shrinkTVP

Rendered fromshrinkTVP.ltxusingR.rsp::texon Nov 15 2024.

Last update: 2024-02-19
Started: 2019-08-07