compute_conditional_sd: Computes posterior draws of structural shock conditional...

In bsvars: Bayesian Estimation of Structural Vector Autoregressive Models

Computes posterior draws of structural shock conditional standard deviations

Description

Each of the draws from the posterior estimation of models is transformed into a draw from the posterior distribution of the structural shock conditional standard deviations.

Usage

compute_conditional_sd(posterior)

Arguments

posterior

posterior estimation outcome obtained by running the estimate function. The interpretation depends on the normalisation of the shocks using function normalise_posterior(). Verify if the default settings are appropriate.

Value

An object of class PosteriorSigma, that is, an NxTxS array with attribute PosteriorSigma containing S draws of the structural shock conditional standard deviations.

Author(s)

Tomasz Woźniak [e-mail]

See Also

estimate, normalise_posterior, summary

Examples

# upload data
data(us_fiscal_lsuw)

# specify the model and set seed
set.seed(123)
specification  = specify_bsvar$new(us_fiscal_lsuw, p = 1)

# run the burn-in
burn_in        = estimate(specification, 10)

# estimate the model
posterior      = estimate(burn_in, 20)

# compute structural shocks' conditional standard deviations
sigma          = compute_conditional_sd(posterior)

# workflow with the pipe |>
############################################################
set.seed(123)
us_fiscal_lsuw |>
  specify_bsvar$new(p = 1) |>
  estimate(S = 10) |> 
  estimate(S = 20) |> 
  compute_conditional_sd() -> csd

bsvars documentation built on Oct. 24, 2024, 5:11 p.m.