Package: bayesianVARs 0.1.5

Luis Gruber

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>.

Authors:Luis Gruber [cph, aut, cre], Gregor Kastner [ctb]

bayesianVARs_0.1.5.tar.gz
bayesianVARs_0.1.5.tar.gz(r-4.5-noble)bayesianVARs_0.1.5.tar.gz(r-4.4-noble)
bayesianVARs.pdf |bayesianVARs.html
bayesianVARs/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/luisgruber/bayesianvars/issues

Pkgdown site:https://luisgruber.github.io

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

openblascpp

3.40 score 1 stars 9 scripts 910 downloads 6 exports 23 dependencies

Last updated 1 months agofrom:f4eabc524e. Checks:OK: 1 WARNING: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 14 2024
R-4.5-linux-x86_64WARNINGDec 14 2024

Exports:bvarmy_gigposterior_heatmapspecify_prior_phispecify_prior_sigmastable_bvar

Dependencies:clicodacolorspacecorrplotfactorstochvolfarverGIGrvggluelabelinglatticelifecycleMASSmunsellmvtnormR6RColorBrewerRcppRcppArmadilloRcppProgressrlangscalesstochvolviridisLite

Shrinkage Priors for Bayesian Vectorautoregressions featuring Stochastic Volatility Using the R Package bayesianVARs

Rendered frombayesianVARs-vignette.Rmdusingknitr::rmarkdownon Dec 14 2024.

Last update: 2024-01-18
Started: 2024-01-14

Readme and manuals

Help Manual

Help pageTopics
Extract or Replace Parts of a bayesianVARs_coef object[.bayesianVARs_coef
Extract or Replace Parts of a bayesianVARs_draws object[.bayesianVARs_draws
Markov Chain Monte Carlo Sampling for Bayesian Vectorautoregressionsbvar
Extract VAR coefficientscoef coef.bayesianVARs_bvar
Simulate fitted/predicted historical values for an estimated VAR modelfitted.bayesianVARs_bvar
Draw from generalized inverse Gaussianmy_gig
Pairwise visualization of out-of-sample posterior predictive densities.pairs.bayesianVARs_predict pairs_predict
Plot method for bayesianVARs_bvarplot.bayesianVARs_bvar
Visualization of in-sample fit of an estimated VAR.plot.bayesianVARs_fitted
Fan chartplot.bayesianVARs_predict
Posterior heatmaps for VAR coefficients or variance-covariance matricesposterior_heatmap
Predict method for Bayesian VARspredict.bayesianVARs_bvar
Pretty printing of a bvar objectprint.bayesianVARs_bvar
Print method for bayesianVARs_predict objectsprint.bayesianVARs_predict
Print method for summary.bayesianVARs_bvar objectsprint.summary.bayesianVARs_bvar
Print method for summary.bayesianVARs_predict objectsprint.summary.bayesianVARs_predict
Specify prior on PHIspecify_prior_phi
Specify prior on Sigmaspecify_prior_sigma
Stable posterior drawsstable_bvar
Summary method for bayesianVARs_bvar objectssummary.bayesianVARs_bvar
Summary statistics for bayesianVARs posterior draws.summary.bayesianVARs_draws
Summary method for bayesianVARs_predict objectssummary.bayesianVARs_predict
Data from the US-economyusmacro_growth
Extract posterior draws of the (time-varying) variance-covariance matrix for a VAR modelvcov.bayesianVARs_bvar