Method for simulation from a fitted GO-GARCH model.
gogarchsim(object, n.sim = 1, n.start = 0, m.sim = 1,
startMethod = c("unconditional", "sample"), prereturns = NA, preresiduals = NA,
presigma = NA, mexsimdata = NULL, rseed = NULL, cluster = NULL, ...)
The simulation horizon.
The burn-in sample.
The number of simulations.
Starting values for the simulation. Valid methods are “unconditional” for the expected values given the density, and “sample” for the ending values of the actual data from the fit object.
Allows the starting return data to be provided by the user.
Allows the starting factor residuals to be provided by the user.
Allows the starting conditional factor sigma to be provided by the user.
A list of matrices with the simulated lagged external variables (if any). The list should be of size m.sim and the matrices each have n.sim + n.start rows.
Optional seeding value(s) for the random number generator.
A cluster object created by calling makeCluster
from
the parallel package. If it is not NULL, then this will be used for parallel
estimation (remember to stop the cluster on completion).
.
A '>goGARCHsim
object containing details of the GO-GARCH
simulation.