Package: BGVAR 2.6.0

BGVAR: Bayesian Global Vector Autoregressions

Estimation of Bayesian Global Vector Autoregressions (BGVAR) with different prior setups and the possibility to introduce stochastic volatility. Built-in priors include the Minnesota, the stochastic search variable selection and Normal-Gamma (NG) prior. For a reference see also Crespo Cuaresma, J., Feldkircher, M. and F. Huber (2016) "Forecasting with Global Vector Autoregressive Models: a Bayesian Approach", Journal of Applied Econometrics, Vol. 31(7), pp. 1371-1391 <doi:10.1002/jae.2504>. Post-processing functions allow for doing predictions, structurally identify the model with short-run or sign-restrictions and compute impulse response functions, historical decompositions and forecast error variance decompositions. Plotting functions are also available. The package has a companion paper: Boeck, M., Feldkircher, M. and F. Huber (2022) "BGVAR: Bayesian Global Vector Autoregressions with Shrinkage Priors in R", Journal of Statistical Software, Vol. 104(9), pp. 1-28 <doi:10.18637/jss.v104.i09>.

Authors:Maximilian Boeck [aut, cre], Martin Feldkircher [aut], Florian Huber [aut], Darjus Hosszejni [ctb]

BGVAR_2.6.0.tar.gz
BGVAR_2.6.0.zip(r-4.7)BGVAR_2.6.0.zip(r-4.6)BGVAR_2.6.0.zip(r-4.5)
BGVAR_2.6.0.tgz(r-4.6-x86_64)BGVAR_2.6.0.tgz(r-4.6-arm64)BGVAR_2.6.0.tgz(r-4.5-x86_64)BGVAR_2.6.0.tgz(r-4.5-arm64)
BGVAR_2.6.0.tar.gz(r-4.7-arm64)BGVAR_2.6.0.tar.gz(r-4.7-x86_64)BGVAR_2.6.0.tar.gz(r-4.6-arm64)BGVAR_2.6.0.tar.gz(r-4.6-x86_64)
BGVAR_2.6.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
BGVAR/json (API)

# Install 'BGVAR' in R:

install.packages('BGVAR', repos = c('https://mboeck11.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mboeck11/bgvar/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

Datasets:

dominant - PesaranData
EB.weights - Monthly EU / G8 countries macroeconomic dataset
eerData - Example data set to replicate Feldkircher and Huber
monthlyData - Monthly EU / G8 countries macroeconomic dataset
OC.weights - Monthly EU / G8 countries macroeconomic dataset
pesaranData - PesaranData
pesaranDiff - PesaranData
tA - PesaranData
testdata - Example data set to show functionality of the package
USexpectations - Example data set to replicate Feldkircher and Huber
W - Monthly EU / G8 countries macroeconomic dataset
W.8016 - PesaranData
W.list - Example data set to replicate Feldkircher and Huber
W.test - Example data set to show functionality of the package
W.trade0012 - Example data set to replicate Feldkircher and Huber

On CRAN:

openblas cpp

7.29 score 35 stars 185 scripts 626 downloads 16 exports 38 dependencies

Last updated from:6f3f74e4c6. Checks:13 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	205
linux-devel-x86_64	OK	211
source / vignettes	OK	372
linux-release-arm64	OK	203
linux-release-x86_64	OK	207
macos-release-arm64	OK	180
macos-release-x86_64	OK	371
macos-oldrel-arm64	OK	210
macos-oldrel-x86_64	OK	286
windows-devel	OK	191
windows-release	OK	194
windows-oldrel	OK	173
wasm-release	OK	184

Exports:add_shockinfo avg.pair.cc bgvar conv.diag dic excel_to_list fevd get_shockinfo gfevd hd irf list_to_matrix lps matrix_to_list resid.corr.test rmse

Dependencies:abind bayesm cellranger cli coda cpp11 crayon evaluate GIGrvg glue highr hms knitr lattice lifecycle magrittr MASS Matrix pillar pkgconfig prettyunits progress R6 Rcpp RcppArmadillo RcppParallel RcppProgress readxl rematch rlang stochvol tibble utf8 vctrs xfun xts yaml zoo

BGVAR: Bayesian Global Vector Autoregression

Rendered fromexamples.Rmdusingknitr::rmarkdown

Last update: 2024-07-03
Started: 2020-05-26

Help page	Topics
BGVAR: Bayesian Global Vector Autoregressions	BGVAR-package
Adding shocks to 'shockinfo' argument	add_shockinfo
Average Pairwise Cross-Sectional Correlations	avg.pair.cc
Estimation of Bayesian GVAR	bgvar
Extract Model Coefficients of Bayesian GVAR	coef coef.bgvar coefficients.bgvar
MCMC Convergence Diagnostics	conv.diag
Deviance Information Criterion	dic dic.bgvar
Example data set to replicate Feldkircher and Huber (2016)	eerData USexpectations W.list W.trade0012
Read Data from Excel	excel_to_list
Forecast Error Variance Decomposition	fevd fevd.bgvar.irf
Extract Fitted Values of Bayesian GVAR	fitted fitted.bgvar
Create 'shockinfo' argument	get_shockinfo
Generalized Forecast Error Variance Decomposition	gfevd gfevd.bgvar
Historical Decomposition	hd hd.bgvar.irf
Impulse Response Function	irf irf.bgvar
Convert Input List to Matrix	list_to_matrix
Extract Log-likelihood of Bayesian GVAR	logLik logLik.bgvar
Compute Log-Predictive Scores	lps lps.bgvar.pred
Convert Input Matrix to List	matrix_to_list
Monthly EU / G8 countries macroeconomic dataset	EB.weights monthlyData OC.weights W
pesaranData	dominant pesaranData pesaranDiff tA W.8016
Graphical Summary of Output Created with 'bgvar'	plot plot.bgvar plot.bgvar.fevd plot.bgvar.irf plot.bgvar.pred plot.bgvar.resid
Predictions	predict predict.bgvar
Residual Autocorrelation Test	resid.corr.test
Extract Residuals of Bayesian GVAR	resid.bgvar residuals residuals.bgvar
Compute Root Mean Squared Errors	rmse rmse.bgvar.pred
Summary of Bayesian GVAR	summary summary.bgvar
Example data set to show functionality of the package	testdata W.test
Extract Variance-covariance Matrix of Bayesian GVAR	vcov vcov.bgvar

Package: BGVAR 2.6.0

BGVAR: Bayesian Global Vector Autoregressions

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Help Manual

Usage by other packages (reverse dependencies)