| bvars-package | Bayesian Forecasting with Large Vector Autoregressions |
| bvars | Bayesian Forecasting with Large Vector Autoregressions |
| compute_fitted_values.PosteriorBVAR | Computes posterior draws from data predictive density |
| compute_shocks | Computes posterior draws of shocks |
| compute_shocks.PosteriorBVAR | Computes posterior draws of shocks |
| compute_variance_decompositions.PosteriorBVAR | Computes posterior draws of the forecast error variance decomposition |
| estimate.BVAR | Bayesian Estimation via Gibbs sampler of a Bayesian VAR with a Flexible Error Term Specification |
| estimate.PosteriorBVAR | Bayesian Estimation via Gibbs sampler of a Bayesian VAR with a Flexible Error Term Specification |
| forecast.PosteriorBVAR | Forecasting using Structural Vector Autoregression |
| rmatnorm1 | Samples random numbers from the matrix-variate normal distribution |
| specify_bvar | R6 Class representing the specification of the 'BVAR' model |
| specify_posterior_bvar | R6 Class Representing 'PosteriorBVAR' |
| specify_prior_bvar | R6 Class Representing 'PriorBVAR' |
| specify_starting_values_bvar | R6 Class Representing 'StartingValuesBVAR' |
| summary.PosteriorBVAR | Provides posterior summary of VAR estimation |
| us_macro_chan | A 20-variable US macroeconomic system for the period 1959 Q4 - 2013 Q4 |