Computes posterior draws of shocks — compute

Each of the draws from the posterior estimation of models from the package bvars is transformed into a draw from the posterior distribution of the structural shocks.

Usage

compute_shocks(posterior)

Arguments

posterior: posterior estimation outcome obtained by running the estimate function.

Value

An object of class PosteriorShocks, that is, an NxTxS array with attribute PosteriorShocks containing S draws of the shocks.

Author

Tomasz Woźniak wozniak.tom@pm.me

Examples

# simple workflow
############################################################
spec = specify_bvar$new(us_macro_chan)        # specify the model
burn = estimate(spec, 5)                      # run the burn-in
#> **************************************************|
#> bvars: Forecasting with Large                     |
#>        Bayesian Vector Autoregressions            |
#> **************************************************|
#>  Gibbs sampler for the BVAR model                 |
#> **************************************************|
#>  Progress of the MCMC simulation for 5 draws
#>     Every draw is saved via MCMC thinning
#>  Press Esc to interrupt the computations
#> **************************************************|
post = estimate(burn, 10)                     # estimate the model
#> **************************************************|
#> bvars: Forecasting with Large                     |
#>        Bayesian Vector Autoregressions            |
#> **************************************************|
#>  Gibbs sampler for the BVAR model                 |
#> **************************************************|
#>  Progress of the MCMC simulation for 10 draws
#>     Every draw is saved via MCMC thinning
#>  Press Esc to interrupt the computations
#> **************************************************|
shoc = compute_shocks(post)                   # compute shocks
plot(shoc)


# workflow with the pipe |>
############################################################
us_macro_chan |>
  specify_bvar$new() |>
  estimate(S = 5) |> 
  estimate(S = 10) |> 
  compute_shocks() |> plot()
#> **************************************************|
#> bvars: Forecasting with Large                     |
#>        Bayesian Vector Autoregressions            |
#> **************************************************|
#>  Gibbs sampler for the BVAR model                 |
#> **************************************************|
#>  Progress of the MCMC simulation for 5 draws
#>     Every draw is saved via MCMC thinning
#>  Press Esc to interrupt the computations
#> **************************************************|
#> **************************************************|
#> bvars: Forecasting with Large                     |
#>        Bayesian Vector Autoregressions            |
#> **************************************************|
#>  Gibbs sampler for the BVAR model                 |
#> **************************************************|
#>  Progress of the MCMC simulation for 10 draws
#>     Every draw is saved via MCMC thinning
#>  Press Esc to interrupt the computations
#> **************************************************|