| bvar | Hierarchical Bayesian vector autoregression |
| BVAR-package | BVAR: Hierarchical Bayesian vector autoregression |
| bv_dummy | Dummy prior settings |
| bv_fcast | Forecast settings |
| bv_irf | Impulse response settings and identification |
| bv_metropolis | Metropolis-Hastings settings |
| bv_minnesota | Minnesota prior settings |
| bv_priors | 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 |
| density.bvar | Density methods for Bayesian VARs |
| fitted.bvar | Fitted and residual methods for Bayesian VARs |
| fred_qd | FRED-MD and FRED-QD: Databases for Macroeconomic Research |
| fred_transform | FRED transformation and subset helper |
| hist_decomp.bvar | Historical decomposition |
| irf.bvar | Impulse response and forecast error methods for Bayesian VARs |
| logLik.bvar | Log-Likelihood method for Bayesian VARs |
| par_bvar | Parallel hierarchical Bayesian vector autoregression |
| plot.bvar | Plotting method for Bayesian VARs |
| plot.bvar_fcast | Plotting method for Bayesian VAR predictions |
| plot.bvar_irf | Plotting method for Bayesian VAR impulse responses |
| predict.bvar | Predict method for Bayesian VARs |
| rmse.bvar | Model fit in- and out-of-sample |
| summary.bvar | Summary method for Bayesian VARs |
| WAIC.bvar | Widely applicable information criterion (WAIC) for Bayesian... |
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