# Bayesian Estimation of Structural Vector Autoregressive Models

## Documentation for package ‘bsvars’ version 2.1.0

- DESCRIPTION file.
- Package NEWS.

## Help Pages

bsvars-package | Bayesian Estimation of Structural Vector Autoregressive Models
bsvars | Bayesian Estimation of Structural Vector Autoregressive Models
compute_conditional_sd | Computes posterior draws of structural shock conditional standard deviations
compute_fitted_values | Computes posterior draws of dependent variables' fitted values
compute_historical_decompositions | Computes posterior draws of historical decompositions
compute_impulse_responses | Computes posterior draws of impulse responses
compute_regime_probabilities | Computes posterior draws of regime probabilities
compute_structural_shocks | Computes posterior draws of structural shocks
compute_variance_decompositions | Computes posterior draws of the forecast error variance decomposition
estimate | Bayesian estimation of Structural Vector Autoregressions via Gibbs sampler
estimate.BSVAR | Bayesian estimation of a homoskedastic Structural Vector Autoregression via Gibbs sampler
estimate.BSVARMIX | Bayesian estimation of a Structural Vector Autoregression with shocks following a finite mixture of normal components via Gibbs sampler
estimate.BSVARMSH | Bayesian estimation of a Structural Vector Autoregression with Markov-switching heteroskedasticity via Gibbs sampler
estimate.BSVARSV | Bayesian estimation of a Structural Vector Autoregression with Stochastic Volatility heteroskedasticity via Gibbs sampler
estimate.PosteriorBSVAR | Bayesian estimation of a homoskedastic Structural Vector Autoregression via Gibbs sampler
estimate.PosteriorBSVARMIX | Bayesian estimation of a Structural Vector Autoregression with shocks following a finite mixture of normal components via Gibbs sampler
estimate.PosteriorBSVARMSH | Bayesian estimation of a Structural Vector Autoregression with Markov-switching heteroskedasticity via Gibbs sampler
estimate.PosteriorBSVARSV | Bayesian estimation of a Structural Vector Autoregression with Stochastic Volatility heteroskedasticity via Gibbs sampler
forecast | Forecasting using Structural Vector Autoregression
forecast.PosteriorBSVAR | Forecasting using Structural Vector Autoregression
forecast.PosteriorBSVARMIX | Forecasting using Structural Vector Autoregression
forecast.PosteriorBSVARMSH | Forecasting using Structural Vector Autoregression
forecast.PosteriorBSVARSV | Forecasting using Structural Vector Autoregression
normalise_posterior | Waggoner & Zha (2003) row signs normalisation of the posterior draws for matrix B
specify_bsvar | R6 Class representing the specification of the homoskedastic BSVAR model
specify_bsvar_mix | R6 Class representing the specification of the BSVAR model with a zero-mean mixture of normals model for structural shocks.
specify_bsvar_msh | R6 Class representing the specification of the BSVAR model with Markov Switching Heteroskedasticity.
specify_bsvar_sv | R6 Class representing the specification of the BSVAR model with Stochastic Volatility heteroskedasticity.
specify_data_matrices | R6 Class Representing DataMatricesBSVAR
specify_identification_bsvars | R6 Class Representing IdentificationBSVARs
specify_posterior_bsvar | R6 Class Representing PosteriorBSVAR
specify_posterior_bsvar_mix | R6 Class Representing PosteriorBSVARMIX
specify_posterior_bsvar_msh | R6 Class Representing PosteriorBSVARMSH
specify_posterior_bsvar_sv | R6 Class Representing PosteriorBSVARSV
specify_prior_bsvar | R6 Class Representing PriorBSVAR
specify_prior_bsvar_mix | R6 Class Representing PriorBSVARMIX
specify_prior_bsvar_msh | R6 Class Representing PriorBSVARMSH
specify_prior_bsvar_sv | R6 Class Representing PriorBSVARSV
specify_starting_values_bsvar | R6 Class Representing StartingValuesBSVAR
specify_starting_values_bsvar_mix | R6 Class Representing StartingValuesBSVARMIX
specify_starting_values_bsvar_msh | R6 Class Representing StartingValuesBSVARMSH
specify_starting_values_bsvar_sv | R6 Class Representing StartingValuesBSVARSV
us_fiscal_ex | A 3-variable system of exogenous variables for the US fiscal model for the period 1948 Q1 - 2023 Q2
us_fiscal_lsuw | A 3-variable US fiscal system for the period 1948 Q1 - 2023 Q2
verify_autoregression | Verifies hypotheses involving autoregressive parameters
verify_autoregression.PosteriorBSVAR | Verifies hypotheses involving autoregressive parameters
verify_autoregression.PosteriorBSVARMIX | Verifies hypotheses involving autoregressive parameters
verify_autoregression.PosteriorBSVARMSH | Verifies hypotheses involving autoregressive parameters
verify_autoregression.PosteriorBSVARSV | Verifies hypotheses involving autoregressive parameters
verify_volatility | Verifies heteroskedasticity of structural shocks equation by equation
verify_volatility.PosteriorBSVAR | Verifies heteroskedasticity of structural shocks equation by equation
verify_volatility.PosteriorBSVARMIX | Verifies heteroskedasticity of structural shocks equation by equation
verify_volatility.PosteriorBSVARMSH | Verifies heteroskedasticity of structural shocks equation by equation
verify_volatility.PosteriorBSVARSV | Verifies heteroskedasticity of structural shocks equation by equation