Bayesian Forecasting with Large Vector Autoregressions

Documentation for package ‘bvars’ version 1.0

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