compute_variance_decompositions {bsvars} | R Documentation |
Computes posterior draws of the forecast error variance decomposition
Description
Each of the draws from the posterior estimation of a model is transformed into a draw from the posterior distribution of the forecast error variance decomposition.
Usage
compute_variance_decompositions(posterior, horizon)
Arguments
posterior |
posterior estimation outcome - an object of one of the classes:
PosteriorBSVAR, PosteriorBSVARMSH, PosteriorBSVARMIX, or PosteriorBSVARSV
obtained by running the |
horizon |
a positive integer number denoting the forecast horizon for the impulse responses computations. |
Value
An object of class PosteriorFEVD, that is, an NxNx(horizon+1)xS
array with attribute PosteriorFEVD
containing S
draws of the forecast error variance decomposition.
Author(s)
Tomasz Woźniak wozniak.tom@pm.me
References
Kilian, L., & Lütkepohl, H. (2017). Structural VAR Tools, Chapter 4, In: Structural vector autoregressive analysis. Cambridge University Press.
See Also
compute_impulse_responses
, estimate
, normalise_posterior
Examples
# upload data
data(us_fiscal_lsuw)
# specify the model and set seed
set.seed(123)
specification = specify_bsvar$new(us_fiscal_lsuw, p = 2)
# run the burn-in
burn_in = estimate(specification, 10)
# estimate the model
posterior = estimate(burn_in$get_last_draw(), 50)
# compute forecast error variance decomposition 2 years ahead
fevd = compute_variance_decompositions(posterior, horizon = 8)
# workflow with the pipe |>
############################################################
set.seed(123)
us_fiscal_lsuw |>
specify_bsvar$new(p = 2) |>
estimate(S = 10) |>
estimate(S = 50) |>
compute_variance_decompositions(horizon = 8) -> fevd