forecast {bsvars} | R Documentation |
Forecasting using Structural Vector Autoregression
Description
Samples from the joint predictive density of all of the dependent variables at forecast horizons
from 1 to horizon
specified as an argument of the function.
Usage
forecast(posterior, horizon, exogenous_forecast)
Arguments
posterior |
posterior estimation outcome - an object of either of the classes:
PosteriorBSVAR, PosteriorBSVARMSH, PosteriorBSVARMIX, or PosteriorBSVARSV
obtained by running the |
horizon |
a positive integer, specifying the forecasting horizon. |
exogenous_forecast |
a matrix of dimension |
Value
A list of class Forecasts
containing the
draws from the predictive density and for heteroskedastic models the draws from the predictive density of
structural shocks conditional standard deviations. The output elements include:
- forecasts
an
NxTxS
array with the draws from predictive density- forecasts_sigma
provided only for heteroskedastic models, an
NxTxS
array with the draws from the predictive density of structural shocks conditional standard deviations
Author(s)
Tomasz Woźniak wozniak.tom@pm.me
Examples
# upload data
data(us_fiscal_lsuw)
# specify the model and set seed
set.seed(123)
specification = specify_bsvar$new(us_fiscal_lsuw, p = 1)
# run the burn-in
burn_in = estimate(specification, 10)
# estimate the model
posterior = estimate(burn_in, 20)
# sample from predictive density 1 year ahead
predictive = forecast(posterior, 4)
# workflow with the pipe |>
############################################################
set.seed(123)
us_fiscal_lsuw |>
specify_bsvar$new(p = 1) |>
estimate(S = 10) |>
estimate(S = 20) |>
forecast(horizon = 4) -> predictive