Package index
bsvarSIGNs: Bayesian Estimation of Structural Vector Autoregressions Identified by Sign, Zero, and Narrative Restrictions
Browse package information
-
bsvarSIGNs-package
bsvarSIGNs
- Bayesian Estimation of Structural Vector Autoregressions Identified by Sign, Zero, and Narrative Restrictions
-
optimism
- A 5-variable US business cycle data, from 1955 Q1 to 2004 Q4
-
monetary
- A 6-variable US monetary policy data, from 1965 Jan to 2007 Aug
-
specify_bsvarSIGN
- R6 Class representing the specification of the BSVARSIGN model
-
specify_identification_bsvarSIGN
- R6 Class Representing IdentificationBSVARSIGN
-
specify_narrative()
- vector specifying one narrative restriction
-
specify_posterior_bsvarSIGN
- R6 Class Representing PosteriorBSVARSIGN
-
specify_prior_bsvarSIGN
- R6 Class Representing PriorBSVAR
-
specify_identification_bsvarSIGN
- R6 Class Representing IdentificationBSVARSIGN
-
specify_prior_bsvarSIGN
- R6 Class Representing PriorBSVAR
-
estimate(<BSVARSIGN>)
- Bayesian estimation of a Structural Vector Autoregression with traditional and narrative sign restrictions via Gibbs sampler
-
specify_posterior_bsvarSIGN
- R6 Class Representing PosteriorBSVARSIGN
-
forecast(<PosteriorBSVARSIGN>)
- Forecasting using Structural Vector Autoregression
-
compute_conditional_sd(<PosteriorBSVARSIGN>)
- Computes posterior draws of structural shock conditional standard deviations
-
compute_fitted_values(<PosteriorBSVARSIGN>)
- Computes posterior draws from data predictive density
-
compute_historical_decompositions(<PosteriorBSVARSIGN>)
- Computes posterior draws of historical decompositions
-
compute_impulse_responses(<PosteriorBSVARSIGN>)
- Computes posterior draws of impulse responses
-
compute_structural_shocks(<PosteriorBSVARSIGN>)
- Computes posterior draws of structural shocks
-
compute_variance_decompositions(<PosteriorBSVARSIGN>)
- Computes posterior draws of the forecast error variance decomposition
Posterior summaries
Analyse the posterior summaries of the posterior estimation outcomes using function summary()
Plot your results
Prepare beautiful and informative plots for your analyses using function plot()