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Plots forecast error variance decompositions

Source: R/plot.R
plot.PosteriorFEVDPANEL.Rd

Plots of the posterior means of the forecast error variance decompositions.

Usage

# S3 method for class 'PosteriorFEVDPANEL'
plot(
  x,
  which_c,
  cols,
  main,
  xlab,
  mar.multi = c(1, 4.6, 0, 4.6),
  oma.multi = c(6, 0, 5, 0),
  ...
)

Arguments

x

an object of class PosteriorFEVDPANEL obtained using the compute_variance_decompositions() function containing posterior draws of forecast error variance decompositions.

which_c

a positive integer or a character string specifying the country for which the forecast should be plotted.

cols

an N-vector with colours of the plot

main

an alternative main title for the plot

xlab

an alternative x-axis label for the plot

mar.multi

the default mar argument setting in graphics::par. Modify with care!

oma.multi

the default oma argument setting in graphics::par. Modify with care!

...

additional arguments affecting the summary produced.

See also

compute_variance_decompositions.PosteriorBVARPANEL

Author

Tomasz Woźniak wozniak.tom@pm.me

Examples

set.seed(123)
specification  = specify_bvarPANEL$new(ilo_dynamic_panel)

# run the burn-in
burn_in        = estimate(specification, 10)
#> **************************************************|
#> bvarPANELs: Forecasting with Bayesian Hierarchical|
#>             Panel Vector Autoregressions          |
#> **************************************************|
#>  Progress of the MCMC simulation for 10 draws
#>     Every draw is saved via MCMC thinning
#>  Press Esc to interrupt the computations
#> **************************************************|

# estimate the model
posterior      = estimate(burn_in, 20)
#> **************************************************|
#> bvarPANELs: Forecasting with Bayesian Hierarchical|
#>             Panel Vector Autoregressions          |
#> **************************************************|
#>  Progress of the MCMC simulation for 20 draws
#>     Every draw is saved via MCMC thinning
#>  Press Esc to interrupt the computations
#> **************************************************|

# compute forecast error variance decomposition 4 years ahead
fevd           = compute_variance_decompositions(posterior, horizon = 4)
plot(fevd, which_c = "POL")


# workflow with the pipe |>
############################################################
set.seed(123)
ilo_dynamic_panel |>
  specify_bvarPANEL$new() |>
  estimate(S = 10) |> 
  estimate(S = 20) |> 
  compute_variance_decompositions(horizon = 4) |>
  plot(which_c = "POL")
#> **************************************************|
#> bvarPANELs: Forecasting with Bayesian Hierarchical|
#>             Panel Vector Autoregressions          |
#> **************************************************|
#>  Progress of the MCMC simulation for 10 draws
#>     Every draw is saved via MCMC thinning
#>  Press Esc to interrupt the computations
#> **************************************************|
#> **************************************************|
#> bvarPANELs: Forecasting with Bayesian Hierarchical|
#>             Panel Vector Autoregressions          |
#> **************************************************|
#>  Progress of the MCMC simulation for 20 draws
#>     Every draw is saved via MCMC thinning
#>  Press Esc to interrupt the computations
#> **************************************************|