plot.PosteriorSigma function

Plots structural shocks' conditional standard deviations

Plots structural shocks' conditional standard deviations

Plots of structural shocks' conditional standard deviations including their median and percentiles.

## S3 method for class 'PosteriorSigma' plot( x, probability = 0.9, shock_names, col = "#ff69b4", main, xlab, mar.multi = c(1, 4.6, 0, 2.1), oma.multi = c(6, 0, 5, 0), ... )

Arguments

  • x: an object of class PosteriorSigma obtained using the compute_conditional_sd() function containing posterior draws of conditional standard deviations of structural shocks.
  • probability: a parameter determining the interval to be plotted. The interval stretches from the 0.5 * (1 - probability) to 1 - 0.5 * (1 - probability) percentile of the posterior distribution.
  • shock_names: a vector of length N containing names of the structural shocks.
  • col: a colour of the plot line and the ribbon
  • 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.

Examples

data(us_fiscal_lsuw) # upload data set.seed(123) # set seed specification = specify_bsvar_sv$new(us_fiscal_lsuw) # specify model burn_in = estimate(specification, 5) # run the burn-in posterior = estimate(burn_in, 5) # estimate the model # compute structural shocks' conditional standard deviations sigma = compute_conditional_sd(posterior) plot(sigma) # plot conditional sds # workflow with the pipe |> ############################################################ set.seed(123) us_fiscal_lsuw |> specify_bsvar_sv$new(p = 1) |> estimate(S = 5) |> estimate(S = 5) |> compute_conditional_sd() |> plot()

See Also

compute_conditional_sd

Author(s)

Tomasz Woźniak wozniak.tom@pm.me

  • Maintainer: Tomasz Woźniak
  • License: GPL (>= 3)
  • Last published: 2024-10-24