| 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 |