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bayesianVARs: MCMC Estimation of Bayesian Vectorautoregressions

Efficient Markov Chain Monte Carlo (MCMC) algorithms for the fully Bayesian estimation of vectorautoregressions (VARs) featuring stochastic volatility (SV). Implements state-of-the-art shrinkage priors following Gruber & Kastner (2023) <doi:10.48550/arXiv.2206.04902>. Efficient equation-per-equation estimation following Kastner & Huber (2020) <doi:10.1002/for.2680> and Carrerio et al. (2021) <doi:10.1016/j.jeconom.2021.11.010>.

Version:0.1.5
Depends:R (≥ 3.3.0)
Imports:colorspace,factorstochvol (≥ 1.1.0),GIGrvg (≥ 0.7), graphics,MASS,mvtnorm,Rcpp (≥ 1.0.0),scales, stats,stochvol (≥ 3.0.3), utils
LinkingTo:factorstochvol,Rcpp,RcppArmadillo,RcppProgress,stochvol
Suggests:coda,knitr,rmarkdown,testthat (≥ 3.0.0)
Published:2024-11-13
DOI:10.32614/CRAN.package.bayesianVARs
Author:Luis GruberORCID iD [cph, aut, cre], Gregor KastnerORCID iD [ctb]
Maintainer:Luis Gruber <Luis.Gruber at aau.at>
BugReports:https://github.com/luisgruber/bayesianVARs/issues
License:GPL (≥ 3)
URL:https://github.com/luisgruber/bayesianVARs,https://luisgruber.github.io/bayesianVARs/
NeedsCompilation:yes
Materials:README,NEWS
In views:Bayesian,TimeSeries
CRAN checks:bayesianVARs results

Documentation:

Reference manual:bayesianVARs.html ,bayesianVARs.pdf
Vignettes:Shrinkage Priors for Bayesian Vectorautoregressions featuring Stochastic Volatility Using the **R** Package **bayesianVARs** (source,R code)

Downloads:

Package source: bayesianVARs_0.1.5.tar.gz
Windows binaries: r-devel:bayesianVARs_0.1.5.zip, r-release:bayesianVARs_0.1.5.zip, r-oldrel:bayesianVARs_0.1.5.zip
macOS binaries: r-release (arm64):bayesianVARs_0.1.5.tgz, r-oldrel (arm64):bayesianVARs_0.1.5.tgz, r-release (x86_64):bayesianVARs_0.1.5.tgz, r-oldrel (x86_64):bayesianVARs_0.1.5.tgz
Old sources: bayesianVARs archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=bayesianVARsto link to this page.


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