R: Hierarchical Bayesian Vector Autoregression

# Hierarchical Bayesian Vector Autoregression

## Documentation for package ‘BVAR’ version 1.0.5

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

BVAR-package | BVAR: Hierarchical Bayesian vector autoregression
as.mcmc.bvar | Methods for 'coda' Markov chain Monte Carlo objects
as.mcmc.bvar_chains | Methods for 'coda' Markov chain Monte Carlo objects
BVAR | BVAR: Hierarchical Bayesian vector autoregression
bvar | Hierarchical Bayesian vector autoregression
bv_alpha | Minnesota prior settings
bv_dummy | Dummy prior settings
bv_fcast | Forecast settings
bv_irf | Impulse response settings and identification
bv_lambda | Minnesota prior settings
bv_metropolis | Metropolis-Hastings settings
bv_mh | Metropolis-Hastings settings
bv_minnesota | Minnesota prior settings
bv_mn | Minnesota prior settings
bv_priors | Prior settings
bv_psi | Minnesota prior settings
bv_soc | Dummy prior settings
bv_sur | Dummy prior settings
coda | Methods for 'coda' Markov chain Monte Carlo objects
coef.bvar | Coefficient and VCOV methods for Bayesian VARs
companion | Retrieve companion matrix from a Bayesian VAR
companion.bvar | Retrieve companion matrix from a Bayesian VAR
companion.default | Retrieve companion matrix from a Bayesian VAR
density.bvar | Density methods for Bayesian VARs
fevd | Impulse response and forecast error methods for Bayesian VARs
fevd.bvar | Impulse response and forecast error methods for Bayesian VARs
fevd.default | Impulse response and forecast error methods for Bayesian VARs
fevd<- | Impulse response and forecast error methods for Bayesian VARs
fitted.bvar | Fitted and residual methods for Bayesian VARs
fred_code | FRED transformation and subset helper
fred_md | FRED-MD and FRED-QD: Databases for Macroeconomic Research
fred_qd | FRED-MD and FRED-QD: Databases for Macroeconomic Research
fred_transform | FRED transformation and subset helper
hist_decomp | Historical decomposition
hist_decomp.bvar | Historical decomposition
hist_decomp.default | Historical decomposition
independent_index | Density methods for Bayesian VARs
irf | Impulse response and forecast error methods for Bayesian VARs
irf.bvar | Impulse response and forecast error methods for Bayesian VARs
irf.default | Impulse response and forecast error methods for Bayesian VARs
irf<- | Impulse response and forecast error methods for Bayesian VARs
logLik.bvar | Log-Likelihood method for Bayesian VARs
lps | Model fit in- and out-of-sample
lps.bvar | Model fit in- and out-of-sample
lps.default | Model fit in- and out-of-sample
par_bvar | Parallel hierarchical Bayesian vector autoregression
plot.bvar | Plotting method for Bayesian VARs
plot.bvar_density | Density methods for Bayesian VARs
plot.bvar_fcast | Plotting method for Bayesian VAR predictions
plot.bvar_irf | Plotting method for Bayesian VAR impulse responses
plot.bvar_resid | Fitted and residual methods for Bayesian VARs
predict.bvar | Predict method for Bayesian VARs
predict<- | Predict method for Bayesian VARs
residuals.bvar | Fitted and residual methods for Bayesian VARs
rmse | Model fit in- and out-of-sample
rmse.bvar | Model fit in- and out-of-sample
rmse.default | Model fit in- and out-of-sample
summary.bvar | Summary method for Bayesian VARs
summary.bvar_fcast | Predict method for Bayesian VARs
summary.bvar_irf | Impulse response and forecast error methods for Bayesian VARs
vcov.bvar | Coefficient and VCOV methods for Bayesian VARs
WAIC | Widely applicable information criterion (WAIC) for Bayesian VARs
WAIC.bvar | Widely applicable information criterion (WAIC) for Bayesian VARs
WAIC.default | Widely applicable information criterion (WAIC) for Bayesian VARs